Pydantic AI

Pydantic AI is an open-source Python framework that focuses on using data validation and type safety to simplify the development of agents driven by large language models and complex workflows, aiming to improve the controllability and development efficiency of AI applications.

Primarily suited for engineers, researchers, or teams developing AI applications with Python, especially those who value code quality, type safety, and need to handle structured outputs, multi-step tasks, or production-grade deployment.

The framework enforces strict input/output specifications for AI components using predefined Pydantic data models, leveraging built-in type checking and validation to automatically process data, and provides clear error messages for outputs that don't meet expectations.

It is model-agnostic, supporting LLMs from mainstream cloud providers such as OpenAI and Anthropic, and it also supports connecting to locally deployed models via Ollama.

The core Pydantic AI framework is open source and free to use. Enterprise features in its ecosystem (such as AI Gateway) may have separate licenses or service terms.

Pydantic AI emphasizes delivering a structured development experience through a strong type system and concise API, and can be seen as an alternative or higher-level layer to LangChain, especially suitable for projects that value type safety and code maintainability.