Master Pydantic AI with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Install Pydantic AI via pip and set up your Python environment with type checking enabled Define your first agent using Pydantic models for input/output validation Configure LLM provider credentials and test basic agent interactions Add tools to your agent with proper type annotations and validation schemas Implement conversation flows with structured outputs and error handling Set up testing framework and write unit tests for agent behavior validation
💡 Quick Start: Follow these 1 steps in order to get up and running with Pydantic AI quickly.
Explore the key features that make Pydantic AI powerful for ai agent framework workflows.
Pydantic AI is used to build Python-based generative AI agents and workflows with typed dependencies, validated tool calls, structured outputs, model-provider abstraction, observability, evals, streaming, and production workflow features.
No. It is designed to work across multiple model providers and OpenAI-compatible endpoints. Teams should check the current documentation for the exact list of supported providers and any provider-specific limitations.
Yes. Agents can declare an output type, commonly a Pydantic model. The framework validates returned structured data and can prompt the model to retry when validation fails.
Yes. It integrates with Pydantic Logfire for tracing, debugging, cost tracking, behavior monitoring, and eval-based performance monitoring. The docs also state that other OpenTelemetry-compatible observability platforms can be used.
The framework itself is listed as free/open-source in the available project information. Running applications still requires paying any relevant model provider costs, infrastructure costs, and any paid observability or gateway services a team chooses to use.
Now that you know how to use Pydantic AI, it's time to put this knowledge into practice.
Sign up and follow the tutorial steps
Check pros, cons, and user feedback
See how it stacks against alternatives
Follow our tutorial and master this powerful ai agent framework tool in minutes.
Tutorial updated March 2026