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When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer of the OpenAI SDK, the Anthropic SDK, LangChain, LlamaIndex, AutoGPT, Transformers, CrewAI, Instructor, and many more).
Features
- Built by the team behind Pydantic (the validation layer of the OpenAI SDK, the Anthropic SDK, LangChain, LlamaIndex, AutoGPT, Transformers, CrewAI, Instructor and many more)
- Model-agnostic — currently OpenAI, Gemini, Anthropic, and Groq are supported. And there is a simple interface to implement support for other models
- Control flow and agent composition is done with vanilla Python, allowing you to make use of the same Python development best practices you'd use in any other (non-AI) project
- Structured response validation with Pydantic
- Streamed responses, including validation of streamed structured responses with Pydantic
- Novel, type-safe dependency injection system, useful for testing and eval-driven iterative development
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