# Pydantic AI — Production AI Agent Framework

> Build production-ready AI agents in Python with type-safe structured outputs, dependency injection, and multi-model support. By the creators of Pydantic.

## Install

Save the content below to `.claude/skills/` or append to your `CLAUDE.md`:

## Quick Use

```bash
pip install pydantic-ai
```

```python
from pydantic_ai import Agent

agent = Agent('claude-sonnet-4-20250514', system_prompt='Be concise.')
result = agent.run_sync('What is the capital of France?')
print(result.output)  # "Paris"
```

## What is Pydantic AI?

Pydantic AI is a Python agent framework built by the Pydantic team. It brings type safety, structured outputs, and dependency injection to AI agent development — making agents as reliable and testable as regular Python code.

**Answer-Ready**: Pydantic AI is a production-grade AI agent framework by the Pydantic team that provides type-safe structured outputs, dependency injection, streaming, and multi-model support for building reliable AI agents in Python.

**Best for**: Python developers building production AI agents who need type safety and testability. **Works with**: Claude, GPT, Gemini, Groq, Mistral, Ollama. **Setup time**: Under 2 minutes.

## Core Features

### 1. Structured Outputs with Pydantic Models

```python
from pydantic import BaseModel
from pydantic_ai import Agent

class CityInfo(BaseModel):
    name: str
    country: str
    population: int

agent = Agent('claude-sonnet-4-20250514', result_type=CityInfo)
result = agent.run_sync('Tell me about Tokyo')
print(result.output)
# CityInfo(name='Tokyo', country='Japan', population=13960000)
```

### 2. Tool Definitions

```python
from pydantic_ai import Agent, RunContext

agent = Agent('claude-sonnet-4-20250514')

@agent.tool
async def get_weather(ctx: RunContext[str], city: str) -> str:
    # Fetch weather data
    return f"Sunny, 22C in {city}"

result = agent.run_sync('Weather in London?')
```

### 3. Dependency Injection

```python
from dataclasses import dataclass

@dataclass
class Deps:
    db: Database
    user_id: str

agent = Agent('claude-sonnet-4-20250514', deps_type=Deps)

@agent.tool
async def get_orders(ctx: RunContext[Deps]) -> list:
    return await ctx.deps.db.get_orders(ctx.deps.user_id)

result = agent.run_sync('Show my orders', deps=Deps(db=db, user_id='123'))
```

### 4. Streaming

```python
async with agent.run_stream('Write a poem') as response:
    async for text in response.stream_text():
        print(text, end='', flush=True)
```

### 5. Multi-Model Support

```python
from pydantic_ai.models import OpenAIModel, AnthropicModel

agent = Agent(OpenAIModel('gpt-4o'))         # OpenAI
agent = Agent(AnthropicModel('claude-sonnet-4-20250514'))  # Anthropic
agent = Agent('gemini-1.5-pro')              # Google
agent = Agent(OpenAIModel('llama3', base_url='http://localhost:11434/v1'))  # Ollama
```

## FAQ

**Q: How does it compare to LangChain?**
A: Pydantic AI is more opinionated and type-safe. LangChain is broader but more complex. Pydantic AI focuses on making agents testable and production-ready.

**Q: Can I use it with Claude?**
A: Yes, Anthropic Claude is a first-class supported provider.

**Q: Is it production ready?**
A: Yes, built by the Pydantic team (whose validation library is used by 80% of Python AI projects).

## Source & Thanks

> Created by [Pydantic Team](https://github.com/pydantic). Licensed under MIT.
>
> [pydantic/pydantic-ai](https://github.com/pydantic/pydantic-ai) — 10k+ stars

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## 快速使用

```bash
pip install pydantic-ai
```

三行代码创建类型安全的 AI 代理。

## 什么是 Pydantic AI？

Pydantic AI 是 Pydantic 团队打造的 Python 代理框架，将类型安全、结构化输出和依赖注入引入 AI 代理开发。

**一句话总结**：Pydantic AI 是生产级 AI 代理框架，提供类型安全的结构化输出、依赖注入、流式输出和多模型支持。

**适合人群**：需要类型安全和可测试性的 Python 开发者。**支持模型**：Claude、GPT、Gemini、Groq、Ollama。

## 核心功能

### 1. Pydantic 结构化输出
用 Pydantic 模型定义输出，自动验证。

### 2. 工具定义
用装饰器定义工具函数，代理自动调用。

### 3. 依赖注入
注入数据库、用户上下文等依赖，方便测试。

### 4. 流式输出
异步流式返回文本或结构化数据。

## 常见问题

**Q: 和 LangChain 比较？**
A: Pydantic AI 更专注类型安全和可测试性，LangChain 更广泛但更复杂。

**Q: 生产就绪？**
A: 是，Pydantic 团队出品（其验证库被 80% Python AI 项目使用）。

## 来源与致谢

> [pydantic/pydantic-ai](https://github.com/pydantic/pydantic-ai) — 10k+ stars, MIT

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Source: https://tokrepo.com/en/workflows/97ebc107-3f1e-4957-ae96-119c42092096
Author: Skill Factory