Pydantic AI

Type-safe agent framework from the Pydantic team

Live preview of ai.pydantic.dev

Overview

Pydantic AI is what you reach for when you want agent code to read like a normal Python service. Inputs are typed, outputs are validated Pydantic models, dependencies are injected. No magic strings, no JSON guessing.

It's model-agnostic from day one: same code runs against OpenAI, Anthropic, Google, Groq, or local models. We use it for backend services where the agent is one component of a larger system and needs to behave like a function with predictable I/O.

The Logfire integration gives you tracing without bolting on a separate observability stack.

Key Features

Type-Safe

Pydantic models everywhere: inputs, outputs, tools

Model Agnostic

Switch between providers without rewriting the agent

Dependency Injection

Pass DBs and clients into agents cleanly

Structured Outputs

Validated responses without parsing prompts

Logfire Tracing

Built-in observability via Pydantic Logfire

Python-Native

Reads like normal Python, no DSL

Why We Recommend Pydantic AI

Type safety is the cheapest way to keep agent code maintainable as it grows. Pydantic AI bakes it in from the first line.

Quick Info

Need help with Pydantic AI?

Our engineers work with Pydantic AI daily and can help you integrate it into your stack.

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