---
id: pydantic-ai
version: "2.30.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# pydantic-ai — AI Agent Framework, the Pydantic way

License: permissive · Maintenance: active · Downloads: 16.5M/mo

## What it is and what it does

Pydantic AI is a framework for building AI agents in Python that prioritizes type safety, validation, and developer ergonomics. It abstracts away the complexity of working with multiple LLM providers—supporting OpenAI, Anthropic, Gemini, DeepSeek, and many others—while keeping your code clean and IDE-friendly through Pydantic's validation layer and Python type hints. The framework lets you define agents with tools, dynamic instructions, structured outputs, and composable capabilities (like web search or thinking) without sacrificing clarity.

The package is designed for production use, offering features like durable execution (preserving agent state across failures), human-in-the-loop tool approval, real-time voice agents, and tight integration with Pydantic Logfire for observability and performance monitoring. It ships with a single lightweight runtime dependency and requires Python 3.10 or later. The framework treats validation as a first-class concern—outputs are validated immediately, and type hints guide both your IDE and the LLM itself, moving entire categories of errors from runtime to write-time.

Use it for:

- Build a customer support agent with tools for database lookups and structured responses, using dependency injection for type-safe data access.
- Create a multi-step workflow agent that searches the web, reasons through results, and streams structured findings in real time.
- Deploy a voice-based agent using native realtime models with the same tools and observability as text-based agents.
- Implement durable agents that resume from checkpoints after transient API failures or application restarts.
- Define complex agent logic as a graph using type hints, avoiding spaghetti-code control flow in intricate workflows.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Pydantic AI is a Python framework for building production-grade AI agents and workflows with LLMs, emphasizing type safety, model-agnostic provider support, and structured validation.

Yes. Pydantic AI is actively maintained, has no known vulnerabilities, installs with minimal friction, and is licensed permissively (MIT). It's appropriate for production use if you're building LLM-powered applications and want type safety, multi-provider support, and observability built in from the start. The framework's design philosophy aligns with FastAPI's ergonomics, making it a natural choice for teams already using Pydantic.

## Install

pip install pydantic-ai
uv add pydantic-ai
poetry add pydantic-ai

## Installing pydantic-ai

Before you install: Low install friction with a single lightweight runtime dependency (pydantic-ai-slim). Active maintenance with recent releases and 19295 repository stars indicate strong community adoption and ongoing development.

License in practice: MIT license permits unrestricted commercial and private use, modification, and distribution with minimal legal constraints.

Quickstart:

pip install pydantic-ai

from pydantic_ai import Agent

agent = Agent('anthropic:claude-sonnet-4-6', instructions='Be concise.')
result = agent.run_sync('Your question here')
print(result.output)

Requires Python 3.10 or later. An LLM provider API key (e.g., Anthropic, OpenAI) must be configured in your environment.

Verify before relying:

- Exact performance characteristics and latency profiles for different model providers and agent configurations.
- Detailed cost comparison or benchmarking against other agent frameworks in production scenarios.
- Specific limitations or edge cases when using custom models or less common provider integrations.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 16.5M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python ai agent framework, llm application development, type-safe generative ai, pydantic validation for llms, multi-model provider support, structured ai output, agentic workflow builder, llm-agents, type-safe, multi-provider

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