Pydantic AI
Pydantic AI is a Python framework for building typed large language model (LLM) agents with Pydantic-validated inputs and outputs, structured output support, tool calling, and broad model provider support.
The core abstraction is an agent that coordinates instructions, type-checked structured outputs, and function tools. Developers define tools from normal Python functions with type hints, and the framework includes a lightweight dependency injection system for passing runtime services such as HTTP clients or database connections into prompts, tools, and validators.
The project integrates with Pydantic Logfire for OpenTelemetry-based tracing and monitoring and ships a companion Pydantic Evals package for code-first evaluation. An optional Pydantic AI Gateway provides unified access to multiple model providers, real-time cost controls, and LLM observability while keeping each request in the provider’s native format.
Official website: pydantic.dev/docs/ai
Related Resources
Tutorial
Pydantic AI: Build Type-Safe LLM Agents in Python
Learn how to use Pydantic AI to build type-safe LLM agents in Python with structured outputs, function calling, and dependency injection patterns.
For additional information on related topics, take a look at the following resources:
