pydantic-ai

# PydanticAI — Typed AI Agents in Python ## Overview PydanticAI is a Python agent framework from the Pydantic team that brings the same type-safety and validation guarantees as Pydantic to LLM-based applications. It supports structured outputs (validated with Pydantic models), dependency injection for testability, streamed responses, multi-turn conversations, and tool use — across OpenAI, Anthropic, Google Gemini, Groq, Mistral, and Ollama. Use this skill when building production AI agents, chatbots, or LLM pipelines where correctness and testability matter. ## When to Use This Skill - Use when building Python AI agents that call tools and return structured data - Use when you need validated, typed LLM outputs (not raw strings) - Use when you want to write unit tests for agent logic without hitting a real LLM - Use when switching between LLM providers without rewriting agent code - Use when the user asks about `Agent`, `@agent.tool`, `RunContext`, `ModelRetry`, or `result_type` ## How It Works ### Step 1: Installation ```bash pip install pydantic-ai # Install extras for specific providers pip install 'pydantic-ai[openai]' # OpenAI / Azure OpenAI pip install 'pydantic-ai[anthropic]' # Anthropic Claude pip install 'pydantic-ai[gemini]' # Google Gemini pip install 'pydantic-ai[groq]' # Groq pip install 'pydantic-ai[vertexai]' # Google Vertex AI ``` ### Step 2: A Minimal Agent ```python from pydantic_ai import Agent # Simple agent — returns a...