Add SWE-Swiss SFT environment#1337
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Validation evidence for the bounty review: This PR targets the existing-data path for https://algora.io/PrimeIntellect-ai/bounties/FHr4fCjVPjFDmFED. |
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Summary
messagesrows into Verifiersprompt/question/answer/infoexamples, supporting both JSON-string and list message formatsBounty: https://algora.io/PrimeIntellect-ai/bounties/FHr4fCjVPjFDmFED
Submitted as the custom Algora bounty claim for the SWE-Swiss training-data environment lane.
Scope note: this targets the existing SWE-Swiss training-data environment path, not the full auto-generation pipeline tier. It keeps runtime requirements light and does not require a sandboxed repository checkout.
Validation
uv run pytest tests/test_swe_swiss_sft_environment.py -quv run ruff check environments/swe_swiss_sft tests/test_swe_swiss_sft_environment.pyuv run ruff format --check environments/swe_swiss_sft tests/test_swe_swiss_sft_environment.pygit diff --checkSWE-Swiss/SWESwiss-SFT-Repair-4Kintoprompt,question,answer, andinfocolumnsNote
Low Risk
Low risk: adds a new standalone environment package plus tests and docs, without modifying core verifier/runtime logic. Main risk is dataset-shape assumptions (
messagesformatting) affecting usability for some SWE-Swiss dataset variants.Overview
Adds a new installable
swe-swiss-sftSingleTurn environment backed by Hugging Face SWE-Swiss SFT datasets, converting each row’smessagestranscript intoprompt/question/answerexamples (supports list or JSON-stringmessages).Introduces a lightweight reward (
SequenceMatcher-based normalized text similarity) and exposes configurable dataset/split/example-limit/shuffle arguments viaload_environment, with accompanying environment README, packaging (pyproject.tomlentry point), a brief mention inenvironments/README.md, and new unit tests covering parsing, dataset loading, reward behavior, and lazy environment construction.Reviewed by Cursor Bugbot for commit 16e512b. Bugbot is set up for automated code reviews on this repo. Configure here.