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Dylan Huang
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Merge branch 'main' into remove-catch-all-except-in-agent-rollout-processor
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README.md

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[![PyPI - Version](https://img.shields.io/pypi/v/eval-protocol)](https://pypi.org/project/eval-protocol/)
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EP is an open specification, Python SDK, pytest wrapper, and suite of tools that
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provides a standardized way to write evaluations for large language model (LLM)
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applications. Start with simple single-turn evals for model selection and prompt
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engineering, then scale up to complex multi-turn reinforcement learning (RL) for
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agents using Model Context Protocol (MCP). EP ensures consistent patterns for
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writing evals, storing traces, and saving results—enabling you to build
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sophisticated agent evaluations that work across real-world scenarios, from
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markdown generation tasks to customer service agents with tool calling
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capabilities.
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**Eval Protocol (EP) is the open-source standard and toolkit for practicing Eval-Driven Development.**
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Building with AI is different. Traditional software is deterministic, but AI systems are probabilistic. How do you ship new features without causing silent regressions? How do you prove a new prompt is actually better?
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The answer is a new engineering discipline: **Eval-Driven Development (EDD)**. It adapts the rigor of Test-Driven Development for the uncertain world of AI. With EDD, you define your AI's desired behavior as a suite of executable tests, creating a safety net that allows you to innovate with confidence.
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EP provides a consistent way to write evals, store traces, and analyze results.
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<p align="center">
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<img src="https://raw.githubusercontent.com/eval-protocol/python-sdk/refs/heads/main/assets/ui.png" alt="UI" />

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