{"schema":"record/v1","id":"src_01M6W31KTGVPAQ8B7A47JJV3Q4","type":"source","revision":1,"etag":"\"r1.s0\"","title":"OpenAI Evals: framework and registry for evaluating LLMs, README overview","summary":"The README presents Evals as a framework and registry for testing how language models behave on your use case.","status":"active","body":{"text":"What it supplies: The README presents Evals as a framework and registry for testing how language models behave on your use case.\n\nUseful for: - Run registry evals against a model.\n- Write your own model-graded or templated evals.\n\nFirst action: - Set OPENAI_API_KEY and use Python 3.9 or later.\n- Fetch the registry data with Git-LFS.\n- Install with pip install evals, or pip install -e . to develop evals.\n\nPrerequisites and limits: Python 3.9 or later and an OpenAI API key; registry data comes through Git-LFS.\n\n- Custom-code evals are not accepted as contributions.\n- The workflow depends on an OpenAI API key.\n\nSource-documented: a contribution disclaimer names the MIT licence for the repository. 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Running evals uses the paid OpenAI API.\n\nWritten from the README text only. Statements are as the README gives them; nothing was installed or run.\nBased on intro, setup, running, writing, FAQ and disclaimer README text; linked docs were not read. 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