diff --git a/wren-ai-service/tools/providers-setup/Dockerfile b/wren-ai-service/tools/providers-setup/Dockerfile new file mode 100644 index 0000000000..ff4fefb942 --- /dev/null +++ b/wren-ai-service/tools/providers-setup/Dockerfile @@ -0,0 +1,58 @@ +# Use official slim Python 3.12 base image +FROM python:3.12.0-slim + +# ------------------------------- +# System Dependencies for Poetry +# ------------------------------- +# Install minimal system packages: curl (for downloading), build tools (for native extensions) +RUN apt-get update && apt-get install -y --no-install-recommends \ + curl build-essential gcc \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* + +# ------------------------------- +# Install Poetry (Python package manager) +# ------------------------------- +ENV POETRY_VERSION=1.8.2 +ENV POETRY_HOME="/opt/poetry" +ENV PATH="$POETRY_HOME/bin:$PATH" +ENV POETRY_VIRTUALENVS_CREATE=false +# Don't use virtualenvs inside the container + +RUN curl -sSL https://install.python-poetry.org | python3 - \ + && ln -s $POETRY_HOME/bin/poetry /usr/local/bin/poetry + +# ------------------------------- +# Set working directory for app +# ------------------------------- +WORKDIR /app + +# ------------------------------- +# Install Python dependencies via Poetry +# ------------------------------- +# Copy only dependency files first to leverage Docker layer caching +COPY pyproject.toml poetry.lock ./ +RUN poetry install --no-interaction --no-ansi + +# ------------------------------- +# Copy remaining app code +# ------------------------------- +COPY . . + +# ------------------------------- +# Environment variables for Streamlit +# ------------------------------- +ENV PYTHONUNBUFFERED=1 +ENV STREAMLIT_SERVER_HEADLESS=true +ENV STREAMLIT_SERVER_PORT=8501 +ENV STREAMLIT_SERVER_ENABLECORS=false + +# ------------------------------- +# Expose Streamlit port +# ------------------------------- +EXPOSE 8501 + +# ------------------------------- +# Default command to run the Streamlit app +# ------------------------------- +CMD ["streamlit", "run", "app.py"] diff --git a/wren-ai-service/tools/providers-setup/app.py b/wren-ai-service/tools/providers-setup/app.py new file mode 100644 index 0000000000..d208ac2348 --- /dev/null +++ b/wren-ai-service/tools/providers-setup/app.py @@ -0,0 +1,89 @@ +from config_loader import load_config_yaml_blocks, group_blocks +from session_state import ConfigState +from ui_components import ( + render_llm_config, + render_embedder_config, + render_import_yaml, + render_pipeline_config, + render_preview, + render_apikey, + render_generate_button +) +import streamlit as st + +# Set Streamlit page layout +st.set_page_config( + layout="wide", # Use a wide layout for better horizontal space + initial_sidebar_state="expanded" # Expand sidebar by default +) + +# Load and group configuration blocks from YAML +yaml_list = load_config_yaml_blocks() +blocks = group_blocks(yaml_list) + +# Retrieve individual configuration sections +llm_block = blocks.get("llm", {}) +embedder_block = blocks.get("embedder", {}) +document_store_block = blocks.get("document_store", {}) +engine_blocks = blocks.get("engine", []) +pipeline_block = blocks.get("pipeline", {}) +settings_block = blocks.get("settings", {}) + + +# Validate required blocks (type + content) +missing_blocks = [] + +if not isinstance(llm_block, dict) or not llm_block: + missing_blocks.append("LLM") +if not isinstance(embedder_block, dict) or not embedder_block: + missing_blocks.append("Embedder") +if not isinstance(document_store_block, dict) or not document_store_block: + missing_blocks.append("Document Store") +if not isinstance(pipeline_block, dict) or not pipeline_block: + missing_blocks.append("Pipeline") + +if missing_blocks: + st.warning( + f"⚠️ Missing or empty configuration blocks: {', '.join(missing_blocks)}. " + "Default values will be used where applicable." + ) + +# Initialize session state with default or imported config values +ConfigState.init(llm_block, embedder_block, document_store_block, pipeline_block) + +# ---------------------- +# Streamlit UI rendering +# ---------------------- +st.title("Custom Provider Config Generator") + +# Layout: two columns – left for inputs, right for preview/export +col1, col2 = st.columns([1.5, 1]) + +with col1: + + # API key input section + st.subheader("API_KEY Configuration") + render_apikey() + + # Upload and parse YAML file into session state + st.subheader("LLM Configuration") + render_import_yaml() + + # LLM model configuration UI + render_llm_config() + + # Embedding model configuration UI + st.subheader("Embedder Configuration") + render_embedder_config() + + # Pipeline flow configuration UI + st.subheader("Pipeline Configuration") + render_pipeline_config() + + # Generate config.yaml and save configuration button + render_generate_button(engine_blocks, settings_block) + +with col2: + # Final preview and export of the combined configuration as YAML + render_preview(engine_blocks, settings_block) + diff --git a/wren-ai-service/tools/providers-setup/config_loader.py b/wren-ai-service/tools/providers-setup/config_loader.py new file mode 100644 index 0000000000..eae91f7a13 --- /dev/null +++ b/wren-ai-service/tools/providers-setup/config_loader.py @@ -0,0 +1,127 @@ +import requests +import yaml +from session_state import ConfigState +from pathlib import Path +import constants as cst +from typing import Any, Dict, List +import streamlit as st + +def load_config_yaml_blocks() -> List[Dict[str, Any]]: + """ + Load the config.yaml from local disk if available; + otherwise, fetch it from the GitHub URL without downloading it. + """ + CONFIG_IN_PATH = cst.get_config_path() + if CONFIG_IN_PATH.exists(): + try: + return load_yaml_list(CONFIG_IN_PATH) + except Exception as e: + st.error(f"❌ Failed to parse local config.yaml: {e}") + return [] + else: + return fetch_yaml_from_url(cst.CONFIG_URL) + +def load_selected_example_yaml(selected_example: str) -> List[Dict[str, Any]]: + """ + Fetch a selected YAML example file from GitHub and return it as a list of blocks. + """ + selected_url = cst.CONFIG_EXAMPLES_SELECTED_URL + selected_example + try: + response = requests.get(selected_url, timeout=cst.REQUEST_TIMEOUT) + response.raise_for_status() + return list(yaml.safe_load_all(response.text)) + except requests.RequestException as e: + st.error(f"❌ Error loading config from GitHub: {e}") + return [] + +def fetch_yaml_from_url(url: str) -> List[Dict[str, Any]]: + """ + Fetch and parse a YAML list from a remote URL. + Returns an empty list if fetch or parsing fails. + """ + try: + response = requests.get(url, timeout=cst.REQUEST_TIMEOUT) + response.raise_for_status() + config_list = list(yaml.safe_load_all(response.text)) + + if not config_list: + raise ValueError(f"⚠️ Received empty YAML content from: {url}") + + return config_list + + except (requests.RequestException, ValueError, yaml.YAMLError) as e: + st.error(f"❌ Error loading config from {url}: {e}") + return [] + +def extract_config_blocks(config_list: List[Dict[str, Any]]) -> Dict[str, Any]: + """ + Extract the first block of each type from the config list. + """ + grouped = group_blocks(config_list) + + def get_first_or_empty(key: str) -> Dict[str, Any]: + val = grouped.get(key, {}) + if isinstance(val, list): + return val[0] if val else {} + return val or {} + + return { + "llm": get_first_or_empty("llm"), + "embedder": get_first_or_empty("embedder"), + "document_store": get_first_or_empty("document_store"), + "pipeline": get_first_or_empty("pipeline"), + } + +def load_yaml_list(path: Path) -> List[Dict[str, Any]]: + """ + Load and parse all YAML documents from a file path. + """ + with path.open("r", encoding="utf-8") as f: + return list(yaml.safe_load_all(f)) + +def group_blocks(blocks: List[Dict[str, Any]]) -> Dict[str, Any]: + """ + Group YAML blocks by their 'type' field. + If multiple blocks share the same type, they are stored as a list. + """ + save_blocks = {} + for block in blocks: + key = block.get("type") or ("settings" if "settings" in block else None) + if not key: + continue + if key in save_blocks: + if isinstance(save_blocks[key], list): + save_blocks[key].append(block) + else: + save_blocks[key] = [save_blocks[key], block] + else: + save_blocks[key] = block + return save_blocks + +def fetch_example_yaml_filenames() -> List[str]: + """ + Fetch the filenames of all .yaml example configs from the GitHub directory + (does not download the content). + """ + try: + response = requests.get(cst.CONFIG_EXAMPLES_URL, timeout=cst.REQUEST_TIMEOUT) + response.raise_for_status() + file_list = response.json() + return [f["name"] for f in file_list if f["name"].endswith(".yaml")] + except requests.RequestException as e: + st.error(f"Error fetching config example filenames: {e}") + return [] + +def apply_config_blocks(config_blocks: List[Dict[str, Any]]): + """ + Group and apply config blocks by updating the Streamlit session state via ConfigState. + """ + grouped = extract_config_blocks(config_blocks) + + ConfigState.init( + grouped["llm"], + grouped["embedder"], + grouped["document_store"], + grouped["pipeline"], + force=True + ) diff --git a/wren-ai-service/tools/providers-setup/constants.py b/wren-ai-service/tools/providers-setup/constants.py new file mode 100644 index 0000000000..84a07aa4d7 --- /dev/null +++ b/wren-ai-service/tools/providers-setup/constants.py @@ -0,0 +1,87 @@ +from pathlib import Path +import os +import requests + +# ------------------------------- +# Fetch Latest Release Version +# ------------------------------- + +def get_latest_config_version(): + """ + Retrieve the latest release tag from the WrenAI GitHub repository. + + Returns: + str: The latest version tag (e.g., "0.20.2") if successful, + or "main" as a fallback if the request fails. + """ + url = "https://api.github.com/repos/Canner/WrenAI/releases/latest" + try: + response = requests.get(url, timeout=10) + if response.status_code == 200: + data = response.json() + return data["tag_name"] + else: + print(f"Failed to get latest release: {response.status_code}") + except Exception as e: + print(f"Error fetching latest config version: {e}") + + return "main" # Fallback to 'main' branch if the request fails + + +# ------------------------------- +# Constants for Config Loading +# ------------------------------- + +CONFIG_VERSION = get_latest_config_version() + +# URL for the default config YAML (used if no local config is found) +CONFIG_URL = f"https://raw.githubusercontent.com/Canner/WrenAI/{CONFIG_VERSION}/docker/config.example.yaml" + +# GitHub API URL to list config examples (only metadata) +CONFIG_EXAMPLES_URL = ( + f"https://api.github.com/repos/Canner/WrenAI/contents/wren-ai-service/docs/config_examples?ref={CONFIG_VERSION}" +) + +# Base URL to fetch individual example YAML files by filename +CONFIG_EXAMPLES_SELECTED_URL = ( + f"https://raw.githubusercontent.com/Canner/WrenAI/{CONFIG_VERSION}/wren-ai-service/docs/config_examples/" +) + +# ------------------------------- +# Local Config Paths +# ------------------------------- + +volume_app_data = Path("/app/data") + +# Global HTTP request timeout in seconds +REQUEST_TIMEOUT = 10 + +def get_config_done_path(): + # Docker environment: mounted config.done + docker_path = volume_app_data / "config.done" + local_path = Path.home() / ".wrenai" / "config.done" + + if docker_path.exists(): + return docker_path + else: + return local_path + +def get_config_path(): + # Docker environment: mounted config.yaml + docker_path = volume_app_data / "config.yaml" + local_path = Path.home() / ".wrenai" / "config.yaml" + + if docker_path.exists(): + return docker_path + else: + return local_path + +# Path to the .env file +def get_env_path(): + docker_path = volume_app_data / ".env" + local_path = Path.home() / ".wrenAI" / ".env" + + if docker_path.exists(): + return docker_path + else: + return local_path \ No newline at end of file diff --git a/wren-ai-service/tools/providers-setup/dry_run_test.py b/wren-ai-service/tools/providers-setup/dry_run_test.py new file mode 100644 index 0000000000..e119edfbc7 --- /dev/null +++ b/wren-ai-service/tools/providers-setup/dry_run_test.py @@ -0,0 +1,72 @@ +from litellm import completion, embedding +from session_state import ConfigState +import streamlit as st +import os + +def llm_completion_test(llm_from): + """ + Test LLM completion using the selected model configuration. + Sends a static prompt and verifies the returned message content. + + Args: + llm_from (dict): Dictionary with model parameters (model name, etc.) + + Returns: + (bool, str): Tuple of success flag and either response content or error message + """ + save_api_key() + try: + response_completion = completion( + model=llm_from["model"], + messages=[{"role": "user", "content": "hi, who are you"}] + ) + + choices = response_completion.get("choices") + if choices and choices[0].get("message", {}).get("content"): + return True, response_completion["choices"][0]["message"]["content"] + else: + return False, "No valid response content" + + except Exception as e: + return False, str(e) + + +def llm_embedding_test(): + """ + Test embedding model using a static input. + Verifies that an embedding vector is returned and is valid. + + Returns: + (bool, str): Tuple of success flag and message or error string + """ + save_api_key() + try: + embedder_block = st.session_state[ConfigState.EMBEDDER_KEY] + embedding_model_name = embedder_block.get("models", [])[0].get("model") + + response_embedding = embedding( + model=embedding_model_name, + input=["Hello world"], + ) + + data = response_embedding.get("data") + if data and data[0].get("embedding"): + embedding_vector = data[0]["embedding"] + if isinstance(embedding_vector, list) and len(embedding_vector) > 0: + return True, f"Embedding length: {len(embedding_vector)}" + else: + return False, "Embedding vector is empty or invalid" + else: + return False, "No embedding data returned" + + except Exception as e: + return False, str(e) + + +def save_api_key(): + """ + Set all saved API keys from session state into environment variables. + Enables external libraries like LiteLLM to access required credentials. + """ + for service, api_key in st.session_state[ConfigState.API_KEY].items(): + os.environ[service] = api_key diff --git a/wren-ai-service/tools/providers-setup/poetry.lock b/wren-ai-service/tools/providers-setup/poetry.lock new file mode 100644 index 0000000000..4bce764fef --- /dev/null +++ b/wren-ai-service/tools/providers-setup/poetry.lock @@ -0,0 +1,2512 @@ +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. + +[[package]] +name = "aiohappyeyeballs" +version = "2.6.1" +description = "Happy Eyeballs for asyncio" +optional = false +python-versions = 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+litellm = ">=1.68.0,<2.0.0" + +[build-system] +requires = ["poetry-core>=2.0.0,<3.0.0"] +build-backend = "poetry.core.masonry.api" diff --git a/wren-ai-service/tools/providers-setup/session_state.py b/wren-ai-service/tools/providers-setup/session_state.py new file mode 100644 index 0000000000..c0c60e2142 --- /dev/null +++ b/wren-ai-service/tools/providers-setup/session_state.py @@ -0,0 +1,173 @@ +import streamlit as st +from pathlib import Path +import uuid + +class ConfigState: + # Session state keys + LLM_FORMS_KEY = "llm_forms" + LLM_MODELS_KEY = "llm_models" + EMBEDDER_KEY = "embedding_model" + DOC_STORE_KEY = "document_store" + PIPELINE_KEY = "pipeline" + API_KEY = "api_key" + API_KEY_FORM = "api_key_form" + EXAMPLE_CONFIG_NAMES_KEY = "example_yaml_names" + + @classmethod + def init(cls, llm_block, embedder_block, document_store_block, pipeline_block, force=False): + """ + Initialize all configuration-related session states. + Set force=True to overwrite existing values. + """ + cls.init_llm_forms(llm_block, force=force) + cls.init_embedder(embedder_block, force=force) + cls.init_document_store(document_store_block, force=force) + cls.init_pipeline(pipeline_block, force=force) + cls.init_apikey() + cls.init_example_configs() + + @classmethod + def init_llm_forms(cls, llm_block, force=False): + """ + Initialize LLM form and model configuration in session state. + This sets up editable forms for each model and compiles a cleaned model list. + """ + if not force and cls.LLM_FORMS_KEY in st.session_state and st.session_state[cls.LLM_FORMS_KEY]: + return + + st.session_state[cls.LLM_FORMS_KEY] = [] + st.session_state[cls.LLM_MODELS_KEY] = [] + + for model_item in llm_block.get("models", []): + form_entry = { + "id": str(uuid.uuid4()), + "model": model_item.get("model", ""), + "alias": model_item.get("alias", ""), + "api_base": model_item.get("api_base", "https://api.openai.com/v1"), + "timeout": int(llm_block.get("timeout", 120)), + "kwargs": [ + {"key": k, "value": v} + for k, v in model_item.get("kwargs", {}).items() + ] + } + + st.session_state[cls.LLM_FORMS_KEY].append(form_entry) + + # Flatten kwargs and prepare cleaned model block + model_entry = { + "id": form_entry["id"], + "model": form_entry["model"], + **({'alias': form_entry["alias"]} if form_entry["alias"] else {}), + "api_base": form_entry["api_base"], + "timeout": form_entry["timeout"], + "kwargs": {k["key"]: k["value"] for k in form_entry["kwargs"] if k["key"]}, + } + + st.session_state[cls.LLM_MODELS_KEY].append(model_entry) + + @classmethod + def init_embedder(cls, embedder_block, force=False): + """ + Initialize embedding model configuration. + Ensures all models have an 'api_base' field set. + """ + if not force and cls.EMBEDDER_KEY in st.session_state and st.session_state[cls.EMBEDDER_KEY]: + return + + st.session_state[cls.EMBEDDER_KEY] = None + + if embedder_block.get("models"): + for model in embedder_block["models"]: + if "api_base" not in model: + model["api_base"] = "https://api.openai.com/v1" + + st.session_state[cls.EMBEDDER_KEY] = { + "type": "embedder", + "provider": embedder_block.get("provider"), + "models": embedder_block["models"], + } + + @classmethod + def init_document_store(cls, document_store_block, force=False): + """ + Initialize document store configuration. + Provides default values for missing fields like timeout and dimension. + """ + if not force and cls.DOC_STORE_KEY in st.session_state and st.session_state[cls.DOC_STORE_KEY]: + return + + st.session_state[cls.DOC_STORE_KEY] = { + "type": "document_store", + "provider": document_store_block.get("provider"), + "location": document_store_block.get("location"), + "embedding_model_dim": document_store_block.get("embedding_model_dim", 3072), + "timeout": document_store_block.get("timeout", 120), + "recreate_index": document_store_block.get("recreate_index", False), + } + + @classmethod + def init_pipeline(cls, pipeline_block, force=False): + """ + Initialize pipeline configuration block. + """ + if not force and cls.PIPELINE_KEY in st.session_state and st.session_state[cls.PIPELINE_KEY]: + return + + st.session_state[cls.PIPELINE_KEY] = { + "type": "pipeline", + "pipes": pipeline_block.get("pipes", []), + } + + @classmethod + def init_apikey(cls, force=False): + """ + Initialize the API key input state from the .env file. + + Loads keys from /app/data/.env where the key name ends with 'API_KEY' + (excluding POSTHOG_API_KEY), and stores them in both: + - A dictionary for runtime access (cls.API_KEY) + - A list of dictionaries for editable form rendering (cls.API_KEY_FORM) + + Args: + force (bool): If True, clears and reloads the state even if already initialized. + """ + env_path = Path("/app/data/.env") + + # Initialize or force reload API keys + if force or cls.API_KEY_FORM not in st.session_state: + st.session_state[cls.API_KEY_FORM] = [] + st.session_state[cls.API_KEY] = {} + + if env_path.exists(): + with open(env_path, "r", encoding="utf-8") as f: + for line in f: + line = line.strip() + + # Skip blank lines and comments + if not line or line.startswith("#") or "=" not in line: + continue + + key, _, value = line.partition("=") + key = key.strip() + value = value.strip() + + # Only load keys that end with 'API_KEY', excluding 'POSTHOG_API_KEY' + if key.endswith("API_KEY") and key != "POSTHOG_API_KEY": + st.session_state[cls.API_KEY_FORM].append({ + "id": str(uuid.uuid4()), + "key": key, + "value": value, + "is_saved": True + }) + st.session_state[cls.API_KEY][key] = value + + @classmethod + def init_example_configs(cls, force=False): + """ + Fetch and store the list of available example YAML filenames from GitHub. + Delayed import is used to avoid circular dependency. + """ + from config_loader import fetch_example_yaml_filenames + st.session_state[cls.EXAMPLE_CONFIG_NAMES_KEY] = fetch_example_yaml_filenames() + + # Additional CRUD methods for LLM, Embedder, etc. can be added below. diff --git a/wren-ai-service/tools/providers-setup/ui_components.py b/wren-ai-service/tools/providers-setup/ui_components.py new file mode 100644 index 0000000000..8d4d67d6cc --- /dev/null +++ b/wren-ai-service/tools/providers-setup/ui_components.py @@ -0,0 +1,543 @@ +import streamlit as st +import uuid +from session_state import ConfigState +from config_loader import load_selected_example_yaml, apply_config_blocks +from dry_run_test import llm_completion_test, llm_embedding_test +import yaml +import os + +def render_import_yaml(): + """ + Render the configuration YAML import section. + Supports loading example YAMLs from GitHub or uploading a custom YAML. + """ + with st.expander("Import Configuration YAML", expanded=False): + # Load example YAML filenames from GitHub + example_names = ["None"] + st.session_state.get("example_yaml_names", []) + selected_examples_yaml = st.selectbox("Select example config YAML", options=example_names) + + # Load selected example YAML + if selected_examples_yaml != "None" and st.button("Import.yaml", key="import__examples_yaml"): + blocks = load_selected_example_yaml(selected_examples_yaml) + apply_config_blocks(blocks) + st.success("YAML import succeeded. Settings updated.") + + # Upload custom YAML + uploaded_file = st.file_uploader("Upload your own YAML file", type=["yaml", "yml"]) + if uploaded_file is not None and st.button("Import.yaml", key="import_own_yaml"): + try: + blocks = list(yaml.safe_load_all(uploaded_file)) + apply_config_blocks(blocks) + except Exception as e: + st.error(f"Failed to import YAML file: {e}") + + +def render_apikey(): + """ + Render the API Key configuration section. + Supports adding, editing, saving, and deleting multiple API keys. + """ + with st.expander("API Key", expanded=False): + from constants import get_env_path + CONFIG_ENV_PATH = get_env_path() + add_api_key = st.session_state[ConfigState.API_KEY] + add_api_key_form = st.session_state[ConfigState.API_KEY_FORM] + + if st.button("➕ API KEY", key="add_api_key_form"): + add_api_key_form.append({"id": str(uuid.uuid4()), "key": "", "value": "", "is_saved": False}) + + for apikey in add_api_key_form: + kcol, vcol, rcol = st.columns([4, 6, 2]) + + with kcol: + apikey["key"] = st.text_input("apikey_service (LLMAI_API_KEY)", key=f"api_key_{apikey['id']}", value=apikey["key"], disabled=apikey.get("is_saved", False)) + + with vcol: + apikey["value"] = st.text_input("apikey", key=f"api_val_{apikey['id']}", value=apikey["value"], type="password", disabled=apikey.get("is_saved", False)) + + with rcol: + st.markdown("
", unsafe_allow_html=True) + if st.button("DEL", key=f"del_apikey_{apikey['id']}"): + # Attempt to remove the API key from the .env file if it exists + key_to_delete = apikey["key"] + + if CONFIG_ENV_PATH.exists(): + with open(CONFIG_ENV_PATH, "r", encoding="utf-8") as f: + lines = f.readlines() + + # Remove the line that starts with the specified key + new_lines = [line for line in lines if not line.strip().startswith(f"{key_to_delete}=")] + + with open(CONFIG_ENV_PATH, "w", encoding="utf-8") as f: + f.writelines(new_lines) + + # Remove the key from both the environment and session state + os.environ.pop(apikey["key"], None) + add_api_key.pop(apikey["key"], None) + add_api_key_form[:] = [item for item in add_api_key_form if item["id"] != apikey["id"]] + + st.rerun() + + if st.button("SAVE", key="save_apikey"): + keys = [] + if len(add_api_key_form) == 0: + st.error("No API key has been added.") + return + + for fields in add_api_key_form: + if not fields["key"] or not fields["value"]: + st.error("Each API key and value must be filled out.") + return + keys.append(fields["key"]) + + if len(keys) != len(set(keys)): + st.error("API key names must be unique. Duplicate keys found.") + return + + # Convert key-value form into a dictionary + processed_keys = {item["key"]: item["value"] for item in add_api_key_form} + + add_api_key.clear() + add_api_key.update(processed_keys) + + for item in add_api_key_form: + item["is_saved"] = True + + # ✅ Overwrite or append keys to /app/data/.env + existing_lines = [] + + # Read existing lines if the .env file exists + if CONFIG_ENV_PATH.exists(): + with open(CONFIG_ENV_PATH, "r", encoding="utf-8") as f: + existing_lines = f.readlines() + + new_lines = [] + seen_keys = set() + + # First, update values of keys that already exist in the .env file + for line in existing_lines: + if "=" in line: + k, _, v = line.partition("=") + k = k.strip() + if k in processed_keys: + new_lines.append(f"{k}={processed_keys[k]}\n") + seen_keys.add(k) + else: + new_lines.append(line) + else: + new_lines.append(line) + + # Then, append any new keys that were not seen in the existing file + for k, v in processed_keys.items(): + if k not in seen_keys: + new_lines.append(f"{k}={v}\n") + + # Write updated lines back to the .env file + with open(CONFIG_ENV_PATH, "w", encoding="utf-8") as f: + f.writelines(new_lines) + + st.success("API keys saved to .env.") + + st.rerun() + +def render_llm_config(): + """ + Render the LLM configuration section. + Allows creating, editing, validating, testing, and saving LLM model entries. + """ + if "form_titles" not in st.session_state: + st.session_state.form_titles = {} + + if st.button("➕ Add model", key="btn_add_model"): + st.session_state[ConfigState.LLM_FORMS_KEY].append({ + "id": str(uuid.uuid4()), + "model": "new-model", + "alias": "", + "api_base": "", + "timeout": 120, + "kwargs": [] + }) + + for form in st.session_state[ConfigState.LLM_FORMS_KEY]: + form_id = form["id"] + if form["model"]: + st.session_state.form_titles[form_id] = form["model"] + title = st.session_state.form_titles.get(form_id, "new-model") + + with st.expander(title, expanded=False): + form["model"] = st.text_input("Model name", key=f"model_name_{form_id}", value=form["model"]) + form["alias"] = st.text_input("Alias (Optional)", key=f"alias_{form_id}", value=form["alias"]) + form["api_base"] = st.text_input("API Base URL", key=f"api_base_{form_id}", value=form["api_base"]) + form["timeout"] = st.text_input("Timeout", key=f"timeout_{form_id}", value=form["timeout"]) + + if st.button("➕ Add KWArg Field", key=f"add_kwarg_{form_id}"): + form["kwargs"].append({"key": "", "value": ""}) + + for kw_idx, pair in enumerate(form["kwargs"]): + kcol, vcol, rcol = st.columns([4, 4, 3]) + with kcol: + pair["key"] = st.text_input("Key", key=f"kw_key_{form_id}_{kw_idx}", value=pair["key"]) + with vcol: + pair["value"] = st.text_input("Value", key=f"kw_val_{form_id}_{kw_idx}", value=pair["value"]) + with rcol: + st.markdown("
", unsafe_allow_html=True) + if st.button("DEL", key=f"del_kw_{form_id}_{kw_idx}"): + form["kwargs"].pop(kw_idx) + st.rerun() + + if st.button("💾 Save this model", key=f"save_{form_id}"): + return_state, msg = save_llm_model(form, form_id) + if return_state: + st.success(msg) + + if st.button("🗑️ Remove this form", key=f"remove_form_{form_id}"): + remove_llm_model(form_id) + st.rerun() + + if st.button("test_llm_model", key=f"test_llm_{form_id}"): + if not st.session_state[ConfigState.API_KEY]: + st.error("No API key has been saved.") + return + + llm_state, llm_msg = llm_completion_test(form) + if llm_state: + st.success("Test Success") + else: + st.error(llm_msg) + + + +def render_embedder_config(): + """ + Render the embedding model configuration section. + Displays current provider settings and allows users to override the model name, + alias, timeout, and base URL. Supports testing and saving. + """ + embedding_models = st.session_state[ConfigState.EMBEDDER_KEY].get("models", []) + default_name = embedding_models[0].get("model") or "text-embedding-3-large" + + with st.expander(f"{default_name}", expanded=False): + st.markdown(f"**type:** `embedder`") + st.markdown(f"**provider:** `{st.session_state[ConfigState.EMBEDDER_KEY].get('provider')}`") + + embedding_api_base = embedding_models[0].get("api_base", "https://api.openai.com/v1") if embedding_models else "" + + embedding_model_name = st.text_input("Embedding Model Name", key="embedding_model_name", value=default_name) + embedding_model_alias = st.text_input("Alias (optional, e.g. default)", key="embedding_model_alias", value="default") + embedding_model_api_base = st.text_input("API Base URL", key="embedding_model_api_base", value=embedding_api_base) + embedding_model_timeout = st.text_input("Timeout (default: 120)", key="embedding_model_timeout", value="120") + + # Dimension of the embedding model output vector, used by document store for index creation + document_store_dim = st.text_input("Embedding_model_dim (placed in doucument_store)", key="embedding_model_dim", value="3072") + + custom_embedding_setting = [{ + "model": embedding_model_name, + "alias": embedding_model_alias, + "timeout": embedding_model_timeout, + "api_base": embedding_model_api_base + }] + + if st.button("💾 save", key="save_embedding_model"): + errors = [] + if not embedding_model_name: + errors.append("Embedding Model Name is required.") + if not embedding_model_timeout: + errors.append("Timeout is required.") + else: + try: + int(embedding_model_timeout) + except ValueError: + errors.append("Timeout must be an integer.") + + if not document_store_dim: + errors.append("Embedding model dim is required.") + else: + try: + int(document_store_dim) + except ValueError: + errors.append("Embedding model dim must be an integer.") + + if errors: + for error in errors: + st.error(error) + else: + st.session_state.embedding_model = { + "type": "embedder", + "provider": st.session_state[ConfigState.EMBEDDER_KEY].get("provider"), + "models": custom_embedding_setting + } + + st.session_state.document_store = { + "type": "document_store", + "provider": st.session_state[ConfigState.DOC_STORE_KEY].get("provider"), + "location": st.session_state[ConfigState.DOC_STORE_KEY].get("location"), + "embedding_model_dim": document_store_dim, + "timeout": st.session_state[ConfigState.DOC_STORE_KEY].get("timeout"), + "recreate_index": st.session_state[ConfigState.DOC_STORE_KEY].get("recreate_index") + } + + st.success("Updated embedder model configuration") + st.rerun() + + if st.button("test_embedding_model", key="test_embedding_model"): + if not st.session_state[ConfigState.API_KEY]: + st.error("No API key has been saved.") + return + + embedding_state, embedding_msg = llm_embedding_test() + if embedding_state: + st.success("Success") + else: + st.error(embedding_msg) + + +# DELETE +# def render_document_store_config(): +# """ +# Render the document store configuration section. +# Displays current settings and allows updating index location, dimensions, timeout, etc. +# """ +# with st.expander("Document Store Configuration", expanded=False): +# st.markdown(f"**type:** `document_store`") +# st.markdown(f"**provider:** `{st.session_state[ConfigState.DOC_STORE_KEY].get('provider')}`") +# st.markdown(f"**location:** `{st.session_state[ConfigState.DOC_STORE_KEY].get('location')}`") + +# document_store_timeout = st.text_input("Timeout (default: 120)", key="document_store_timeout", value="120") +# st.markdown(f"**timeout:** `120`") +# st.markdown(f"**recreate_index:** `{st.session_state[ConfigState.DOC_STORE_KEY].get('recreate_index')}`") + +# document_store_dim = st.text_input("Embedding_model_dim", value="3072") + +# if st.button("💾 save", key="save_document_store"): +# errors = [] +# if not document_store_dim: +# errors.append("Embedding model dim is required.") +# else: +# try: +# int(document_store_dim) +# except ValueError: +# errors.append("Embedding model dim must be an integer.") + +# if not document_store_timeout: +# errors.append("Timeout is required.") +# else: +# try: +# int(document_store_timeout) +# except ValueError: +# errors.append("Timeout must be an integer.") + +# if errors: +# for error in errors: +# st.error(error) +# else: +# st.session_state.document_store = { +# "type": "document_store", +# "provider": st.session_state[ConfigState.DOC_STORE_KEY].get("provider"), +# "location": st.session_state[ConfigState.DOC_STORE_KEY].get("location"), +# "embedding_model_dim": document_store_dim, +# "timeout": document_store_timeout, +# "recreate_index": st.session_state[ConfigState.DOC_STORE_KEY].get("recreate_index") +# } +# st.success("Updated document store configuration") + +def render_pipeline_config(): + """ + Render the pipeline configuration section. + Allows selecting LLM models for each defined pipeline step. + """ + pipeline_llm_options = [] + all_pipelines = st.session_state[ConfigState.PIPELINE_KEY].get("pipes", []) + + # set all LLM models options + for model in st.session_state[ConfigState.LLM_MODELS_KEY]: + if model.get("alias"): + pipeline_llm_options.append("litellm_llm." + model["alias"]) + elif model.get("model"): + pipeline_llm_options.append("litellm_llm." + model["model"]) + + # enumerate all pipelines, record original index + for original_idx, pipe in enumerate(all_pipelines): + if not pipe.get("llm"): + continue + + pipe_name = pipe.get("name", f"Unnamed Pipeline {original_idx}") + with st.expander(f"🔧 Pipeline: {pipe_name}", expanded=False): + for key, value in pipe.items(): + if key == "llm": + selected_llm = st.selectbox( + "LLM Model", + options=pipeline_llm_options, + index=pipeline_llm_options.index(value) if value in pipeline_llm_options else 0, + key=f"llm_{original_idx}" + ) + else: + st.markdown(f"**{key}:** `{value}`") + + if st.button("💾 Save this llm", key=f"save_{pipe_name}"): + # ✅ use original index to update llm + st.session_state[ConfigState.PIPELINE_KEY]["pipes"][original_idx]["llm"] = selected_llm + st.success(f"✅ Updated pipeline `{pipe_name}` LLM to `{selected_llm}`") + + + +def render_preview(engine_blocks, settings_block): + """ + Render the preview section and display all configured components + """ + st.subheader("Current Configuration (Preview)") + + preview_blocks, _ = get_config_blocks(engine_blocks, settings_block) + st.json(preview_blocks) + +def render_generate_button(engine_blocks, settings_block): + """ + Render the generate button section and handle saving configuration to files. + Writes the final configuration to config.yaml and creates config.done marker file. + """ + if st.button("Save configuration", key="generate_config_yaml"): + from constants import get_config_path, get_config_done_path + CONFIG_OUT_PATH = get_config_path() + CONFIG_DONE_PATH = get_config_done_path() + _, generate_blocks = get_config_blocks(engine_blocks, settings_block) + + try: + with open(CONFIG_OUT_PATH, "w", encoding="utf-8") as f: + yaml.dump_all(generate_blocks, f, sort_keys=False, allow_unicode=True) + st.success(f"Config saved to {CONFIG_OUT_PATH.resolve()}") + + with open(CONFIG_DONE_PATH, "w", encoding="utf-8") as f: + f.write("true\n") + st.success("✅ Configuration completed. Please return to the CLI.") + except Exception as e: + st.error(f"❌ Failed to generate config: {e}") + + + +def save_llm_model(form, form_id): + """ + Validate and save a single LLM model form to session state. + Checks for required fields, converts kwargs, and handles alias uniqueness. + """ + errors = validate_llm_form(form) + if errors: + for error in errors: + st.error(error) + return False, None + + # Convert list of kwargs to dictionary + kwargs_dict = {} + for p in form["kwargs"]: + if p["key"]: + try: + kwargs_dict[p["key"]] = eval(p["value"]) + except Exception: + kwargs_dict[p["key"]] = p["value"] + + # Prevent duplicate aliases + if form["alias"]: + existing_aliases = [ + m.get("alias") for m in st.session_state[ConfigState.LLM_MODELS_KEY] + if m.get("id") != form_id and "alias" in m + ] + if form["alias"] in existing_aliases: + st.error(f"Duplicate alias name: {form['alias']}.") + return False, None + + saved_entry = { + "model": form["model"], + **({"alias": form["alias"]} if form["alias"] else {}), + "api_base": form["api_base"], + "timeout": form["timeout"], + "kwargs": kwargs_dict, + } + + existing_ids = [m.get("id") for m in st.session_state[ConfigState.LLM_MODELS_KEY]] + if form_id in existing_ids: + index = existing_ids.index(form_id) + st.session_state[ConfigState.LLM_MODELS_KEY][index] = {**saved_entry, "id": form_id} + return True, f"Updated model: {form['model']}" + else: + st.session_state[ConfigState.LLM_MODELS_KEY].append({**saved_entry, "id": form_id}) + return True, f"Added new model: {form['model']}" + + +def remove_llm_model(form_id): + """ + Remove a model and its form from session state by ID. + """ + st.session_state[ConfigState.LLM_FORMS_KEY] = [ + f for f in st.session_state[ConfigState.LLM_FORMS_KEY] if f["id"] != form_id + ] + st.session_state[ConfigState.LLM_MODELS_KEY] = [ + m for m in st.session_state[ConfigState.LLM_MODELS_KEY] if m.get("id") != form_id + ] + + +def validate_llm_form(form): + """ + Validate a single LLM form for completeness and formatting. + Returns a list of error messages if validation fails. + """ + errors = [] + + if not form.get("model"): + errors.append("Model name is required.") + if not form.get("api_base"): + errors.append("API Base URL is required.") + if not form.get("timeout"): + errors.append("Timeout is required.") + else: + try: + int(form["timeout"]) + except ValueError: + errors.append("Timeout must be an integer.") + + for idx, pair in enumerate(form.get("kwargs", [])): + if pair.get("key") and not pair.get("value"): + errors.append(f"KWArg field {idx+1}: Value is required when key is provided.") + if pair.get("value") and not pair.get("key"): + errors.append(f"KWArg field {idx+1}: Key is required when value is provided.") + + return errors + + +def get_config_blocks(engine_blocks, settings_block): + """ + Returns preview blocks for display and generate blocks for saving. + """ + llm_preview = { + "type": "llm", + "provider": "litellm_llm", + "models": [ + {k: v for k, v in model.items() if k != "id"} + for model in st.session_state.get(ConfigState.LLM_MODELS_KEY, []) + ] + } + + embedder_preview = st.session_state.get(ConfigState.EMBEDDER_KEY) + document_store_preview = st.session_state.get(ConfigState.DOC_STORE_KEY) + + pipeline_preview = { + "type": "pipeline", + "pipes": [form for form in st.session_state.get(ConfigState.PIPELINE_KEY, {}).get("pipes", []) if form.get("llm")] + } + + generate_pipeline_block = { + "type": "pipeline", + "pipes": st.session_state.get(ConfigState.PIPELINE_KEY, {}).get("pipes", []) + } + + preview_blocks = [llm_preview, embedder_preview, document_store_preview, pipeline_preview] + generate_blocks = [ + llm_preview, + embedder_preview, + *[ + {"type": "engine", "provider": engine.get("provider"), "endpoint": engine.get("endpoint")} + for engine in engine_blocks + ], + document_store_preview, + generate_pipeline_block, + {"settings": settings_block} + ] + + return preview_blocks, generate_blocks diff --git a/wren-launcher/commands/launch.go b/wren-launcher/commands/launch.go index 4addda7ff1..6f4d179059 100644 --- a/wren-launcher/commands/launch.go +++ b/wren-launcher/commands/launch.go @@ -246,6 +246,51 @@ func Launch() { panic(err) } + if strings.ToLower(llmProvider) == "custom" { + + // chech if ~/.wrenai is exist + wrenDir, err := utils.TryGetWrenAIDir() + if err != nil || wrenDir == "" { + pterm.Warning.Println("⚠️ ~/.wrenai not found. Skipping custom UI setup for now.") + return + } + + containerName := "wrenai-providers-setup" + + // Find available port for Streamlit UI + streamlitPort := utils.FindAvailablePort(8501) + pterm.Info.Println("Using port", streamlitPort, "for Streamlit UI") + + // Remove any existing container (whether running or stopped) + if err := utils.RemoveContainerIfExists(containerName); err != nil { + pterm.Warning.Println("⚠️ Failed to remove existing container:", err) + } + + // Build and start the Streamlit UI container + err = utils.RunStreamlitUIContainer() + if err != nil { + pterm.Error.Println("❌ Failed to start Streamlit UI:", err) + return + } + + pterm.Info.Println(fmt.Sprintf("🚀 providers-setup UI container started at http://localhost:%d", streamlitPort)) + + // Wait for user to complete configuration in the UI + pterm.Info.Println("⌛ Waiting for user to finish UI configuration...") + for { + if utils.IsCustomConfigReady() { + pterm.Info.Println("✅ Detected config.done. Proceeding...") + break + } + time.Sleep(3 * time.Second) + } + + // Clean up container after config is complete + if err := utils.RemoveContainerIfExists(containerName); err != nil { + pterm.Warning.Println("⚠️ Failed to remove existing container:", err) + } + } + // launch Wren AI pterm.Info.Println("Launching Wren AI") const projectName string = "wrenai" diff --git a/wren-launcher/utils/docker.go b/wren-launcher/utils/docker.go index 681c3c8b5f..7608b3b015 100644 --- a/wren-launcher/utils/docker.go +++ b/wren-launcher/utils/docker.go @@ -6,6 +6,7 @@ import ( "io" "net/http" "os" + "os/exec" "path" "regexp" "strings" @@ -24,7 +25,7 @@ import ( const ( // please change the version when the version is updated - WREN_PRODUCT_VERSION string = "0.22.2" + WREN_PRODUCT_VERSION string = "0.22.2" DOCKER_COMPOSE_YAML_URL string = "https://raw.githubusercontent.com/Canner/WrenAI/" + WREN_PRODUCT_VERSION + "/docker/docker-compose.yaml" DOCKER_COMPOSE_ENV_URL string = "https://raw.githubusercontent.com/Canner/WrenAI/" + WREN_PRODUCT_VERSION + "/docker/.env.example" AI_SERVICE_CONFIG_URL string = "https://raw.githubusercontent.com/Canner/WrenAI/" + WREN_PRODUCT_VERSION + "/docker/config.example.yaml" @@ -294,14 +295,52 @@ func PrepareDockerFiles(openaiApiKey string, openaiGenerationModel string, hostP return err } } else if strings.ToLower(llmProvider) == "custom" { - // if .env file does not exist, return error - if _, err := os.Stat(getEnvFilePath(projectDir)); os.IsNotExist(err) { - return fmt.Errorf(".env file does not exist, please download the env file from %s to ~/.wrenai, rename it to .env and fill in the required information", DOCKER_COMPOSE_ENV_URL) + + // Generate or load existing USER_UUID + userUUID, err := prepareUserUUID(projectDir) + if err != nil { + return err } - // if config.yaml file does not exist, return error - if _, err := os.Stat(getConfigFilePath(projectDir)); os.IsNotExist(err) { - return fmt.Errorf("config.yaml file does not exist, please download the config.yaml file from %s to ~/.wrenai, rename it to config.yaml and fill in the required information", AI_SERVICE_CONFIG_URL) + // Ensure .env exists (download if missing) + envFilePath := getEnvFilePath(projectDir) + if _, err := os.Stat(envFilePath); os.IsNotExist(err) { + pterm.Println(".env file not found, downloading from default URL...") + err = downloadFile(envFilePath, DOCKER_COMPOSE_ENV_URL) + if err != nil { + return fmt.Errorf("failed to download .env: %v", err) + } + + // Read downloaded .env content + contentBytes, err := os.ReadFile(envFilePath) + if err != nil { + return fmt.Errorf("failed to read .env: %v", err) + } + str := string(contentBytes) + + // Replace or append USER_UUID + reg := regexp.MustCompile(`(?m)^USER_UUID=.*$`) + if reg.MatchString(str) { + str = reg.ReplaceAllString(str, "USER_UUID="+userUUID) + } else { + str = str + "\nUSER_UUID=" + userUUID + "\n" + } + + // Save updated .env file + err = os.WriteFile(envFilePath, []byte(str), 0644) + if err != nil { + return fmt.Errorf("failed to write updated .env: %v", err) + } + } + + // Ensure config.yaml exists (download if missing) + configFilePath := getConfigFilePath(projectDir) + if _, err := os.Stat(configFilePath); os.IsNotExist(err) { + pterm.Println("config.yaml not found, downloading from default URL...") + err = downloadFile(configFilePath, AI_SERVICE_CONFIG_URL) + if err != nil { + return fmt.Errorf("failed to download config.yaml: %v", err) + } } } @@ -509,3 +548,146 @@ func CheckAIServiceStarted(url string) error { } return nil } + +func TryGetWrenAIDir() (string, error) { + homeDir, err := os.UserHomeDir() + if err != nil { + return "", err + } + wrenDir := path.Join(homeDir, ".wrenai") + + info, err := os.Stat(wrenDir) + if err != nil || !info.IsDir() { + return "", nil + } + return wrenDir, nil +} + +func ensureFileExists(filePath string, defaultContent []byte) error { + if _, err := os.Stat(filePath); os.IsNotExist(err) { + return os.WriteFile(filePath, defaultContent, 0644) + } + return nil +} + +// RunStreamlitUIContainer builds and runs the Streamlit UI container. +// It ensures that config.yaml, .env, and config.done are mounted, +// and initializes config.done with 'false' for setup flow control. +func RunStreamlitUIContainer() error { + + // Build the Docker image for the Streamlit UI + if err := buildStreamlitImage(); err != nil { + return err + } + + // Get ~/.wrenai directory + wrenAIDir, err := TryGetWrenAIDir() + if err != nil { + return fmt.Errorf("failed to get ~/.wrenai: %v", err) + } + + // Initialize config.done with 'false' + donePath, err := prepareConfigDoneFile(wrenAIDir) + if err != nil { + return fmt.Errorf("failed to write to config.done: %v", err) + } + + // Mount user config.yaml and .env for the UI to read/write + configPath, envPath, _ := getMountPaths(wrenAIDir) + _ = ensureFileExists(configPath, []byte("# Create a temporary yaml file")) + _ = ensureFileExists(envPath, []byte("# Put your API keys here\n")) + + // run docker and mount volume + if err := runStreamlitContainer(configPath, envPath, donePath); err != nil { + return err + } + + return nil +} + +func buildStreamlitImage() error { + cmd := exec.Command("docker", "build", "-t", "wrenai-providers-setup", "../wren-ai-service/tools/providers-setup") + output, err := cmd.CombinedOutput() + if err != nil { + return fmt.Errorf("build failed: %v\n%s", err, output) + } + return nil +} + +// prepareConfigDoneFile creates or overwrites the config.done file, +// marking the UI configuration state as "not finished" by default ("false"). +// Returns the full path to config.done and any error. +func prepareConfigDoneFile(wrenAIDir string) (string, error) { + donePath := path.Join(wrenAIDir, "config.done") + err := os.WriteFile(donePath, []byte("false"), 0644) + if err != nil { + return "", fmt.Errorf("❌ Failed to write config.done: %v", err) + } + return donePath, nil +} + +func getMountPaths(wrenDir string) (string, string, string) { + return path.Join(wrenDir, "config.yaml"), + path.Join(wrenDir, ".env"), + path.Join(wrenDir, "config.done") +} + +// runStreamlitContainer starts the Streamlit UI Docker container with the given bind-mount paths. +// It maps port 8501 and runs the container in detached mode. +// Returns an error if the container fails to start. +func runStreamlitContainer(configPath, envPath, donePath string) error { + cmd := exec.Command("docker", "run", "--rm", "-d", + "-p", "8501:8501", + "--name", "wrenai-providers-setup", + "-v", configPath+":/app/data/config.yaml", + "-v", envPath+":/app/data/.env", + "-v", donePath+":/app/data/config.done", + "wrenai-providers-setup", + ) + + output, err := cmd.CombinedOutput() + if err != nil { + return fmt.Errorf("❌ Failed to run providers-setup UI container: %v\n%s", err, output) + } + return nil +} + +// RemoveContainerIfExists forcibly removes the specified Docker container +// if it currently exists (running or stopped). Logs the removal result. +func RemoveContainerIfExists(name string) error { + // Check if the container exists (inspect will fail if not) + err := exec.Command("docker", "inspect", name).Run() + if err != nil { + pterm.Info.Println("🔍 Container does not exist, skipping:", name) + return nil + } + + // Remove container forcefully + cmd := exec.Command("docker", "rm", "-f", name) + out, err := cmd.CombinedOutput() + if err != nil { + return fmt.Errorf("❌ Failed to force-remove container: %v\n%s", err, string(out)) + } + + pterm.Info.Println("🧹 Container forcibly removed:", name) + return nil +} + +// IsCustomConfigReady checks whether the config.done file contains 'true', +// indicating that the Streamlit configuration process is complete. +func IsCustomConfigReady() bool { + wrenAIDir, err := TryGetWrenAIDir() + if err != nil { + return false + } + + configDonePath := path.Join(wrenAIDir, "config.done") + data, err := os.ReadFile(configDonePath) + if err != nil { + return false + } + + // Trim whitespace and compare case-insensitively + trimmed := strings.TrimSpace(string(data)) + return strings.EqualFold(trimmed, "true") +}