PydanticAI
New
Build type-safe AI agents in Python — Pydantic models validate every input, output, and tool call so runtime surprises stay in development, not production.
Agents
★ 4.5(2,200 reviews)freeOverview
PydanticAI is a Python agent framework from the team behind Pydantic, designed for building production-grade AI applications with type safety at every layer. Agents, tools, and structured outputs are all defined with Pydantic models — giving you validation, autocomplete, and runtime error catching that no other agent framework matches. Built on logfire for tracing and integrates with any LLM provider via a clean dependency injection pattern.
Key Features
- Full type safety across agents, tools, and structured outputs via Pydantic
- Dependency injection pattern for clean, testable agent code
- Structured output validation with automatic retry on schema violations
- Built-in logfire integration for production tracing and observability
- Provider-agnostic: works with OpenAI, Anthropic, Gemini, Groq, and more
- Streaming support with typed partial responses
Pros
- • Best type safety in the Python agent ecosystem by far
- • Familiar Pydantic patterns make the framework intuitive for most Python devs
- • Testability-first design makes agents far easier to unit test than alternatives
Cons
- • Python-only — TypeScript teams should look at Mastra or Vercel AI SDK
- • Newer than LangChain — smaller ecosystem of community examples
- • Logfire observability platform is paid beyond the free tier
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