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Update the pydantic-evals README.md (#1313)
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pydantic_evals/README.md

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# Pydantic Evals
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Pydantic core evals logic with minimal required dependencies.
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[![CI](https://github.com/pydantic/pydantic-ai/actions/workflows/ci.yml/badge.svg?event=push)](https://github.com/pydantic/pydantic-ai/actions/workflows/ci.yml?query=branch%3Amain)
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[![Coverage](https://coverage-badge.samuelcolvin.workers.dev/pydantic/pydantic-ai.svg)](https://coverage-badge.samuelcolvin.workers.dev/redirect/pydantic/pydantic-ai)
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[![PyPI](https://img.shields.io/pypi/v/pydantic-evals.svg)](https://pypi.python.org/pypi/pydantic-evals)
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[![python versions](https://img.shields.io/pypi/pyversions/pydantic-evals.svg)](https://github.com/pydantic/pydantic-ai)
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[![license](https://img.shields.io/github/license/pydantic/pydantic-ai.svg)](https://github.com/pydantic/pydantic-ai/blob/main/LICENSE)
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(Need to add more here..)
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This is a library for evaluating non-deterministic (or "stochastic") functions in Python. It provides a simple,
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Pythonic interface for defining and running stochastic functions, and analyzing the results of running those functions.
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While this library is developed as part of [PydanticAI](https://ai.pydantic.dev), it only uses PydanticAI for a small
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subset of generative functionality internally, and it is designed to be used with arbitrary "stochastic function"
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implementations. In particular, it can be used with other (non-PydanticAI) AI libraries, agent frameworks, etc.
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As with PydanticAI, this library prioritizes type safety and use of common Python syntax over esoteric, domain-specific
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use of Python syntax.
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Full documentation is available at [ai.pydantic.dev/evals](https://ai.pydantic.dev/evals).
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[//]: # (TODO: Add a basic example here.)
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[//]: # (TODO: Add a note about how you can view the results in the terminal or in any OTel sink, e.g. Logfire.)

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