How to Build Type-Safe AI Agents with Pydantic AI
Pydantic AI is a Python framework for building AI agents with the same type-safety and validation you expect from Pydantic. This tutorial shows you how…
What is Pydantic AI? Pydantic AI is an open-source Python framework for building generative AI applications with a focus on type safety and developer experience. Created by the team behind Pydantic, it lets you define agents, tools, and outputs as typed Python objects, so validation, serialization, and IDE autocompletion work out of the box. It supports multiple model providers, streaming responses, durable execution via Temporal, and observability through Pydantic Logfire.
Product Features
- Type-safe structured outputs validated by Pydantic models
- Model-agnostic support for OpenAI, Anthropic, Gemini, Groq, and Ollama
- Dependency injection system for tools, prompts, and tests
- Streaming responses with partial validation of structured data
- Built-in logging, tracing, and integration with Logfire
- Graph-based control flow for complex multi-agent workflows
Product Highlights
- Maintained by the Pydantic team with a clean, Pythonic API
- Catches LLM output errors at runtime through strict validation
- Excellent testing support thanks to dependency injection
- Free and open-source with a growing ecosystem
Use Cases
- Building robust structured-output extraction pipelines
- Creating typed agent workflows for customer support automation
- Integrating LLM reasoning into existing FastAPI services
- Generating and validating complex JSON for downstream systems
- Prototyping multi-agent graphs with predictable behavior
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