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PydanticAI
Agent AI

PydanticAI

Type-safe Python agent framework built by the creators of Pydantic

4.9
freeintermediateTrendingVerifiedSince 2026-02
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About PydanticAI

PydanticAI is a lightweight, production-grade Python agent framework created by the core Pydantic team. It brings strict type validation, structured outputs, and clean dependency injection to generative AI development, ensuring models strictly adhere to domain schemas.

Designed to eliminate messy string parsing and unreliable tool outputs, PydanticAI treats LLM interactions as type-checked functions. It supports model agnosticism across OpenAI, Anthropic, Gemini, and Ollama, offering native telemetry via OpenTelemetry and seamless integration with Logfire.

How It Works
1

Define agent input/output expectations using standard Pydantic BaseModel schemas.

2

Register typed Python tools and functions that the agent can autonomously call.

3

Inject dynamic system state and contextual dependencies at runtime.

4

Execute structured prompt runs with automatic retry loops on validation failure.

5

Monitor latency, token costs, and tool execution traces in production via OpenTelemetry.

Platforms
linuxmacoswindowsAPI
Best For
python developersdata scientistsai engineers
Screenshot
PydanticAI screenshot

Capabilities & Features

Free Tier
API Access
No Signup Required
Open Source
Works Offline
Customizable
Multimodal
Image Input
File Upload
Code Execution
Plugins
Memory
Collaboration
White Label
Self-Hostable
Voice InputImage OutputVideo InputVideo OutputAudio OutputWeb SearchBrowser Extension

Common Use Cases

1

structured-outputs

2

type-safe-agents

3

tool-calling

4

production-llm

Frequently Asked Questions

Is PydanticAI free to use?

Yes, PydanticAI is completely free and open-source under the MIT license.

Can I use PydanticAI with local models?

Yes, PydanticAI supports local LLMs via Ollama, vLLM, and any OpenAI-compatible API endpoint.

How does PydanticAI handle malformed model outputs?

If an LLM returns JSON that fails schema validation, PydanticAI automatically reflects the validation error back to the model for self-correction up to a configurable retry limit.

Pricing Modelfree

Free Plan

100% Free / Open Source (MIT Licensed)

Paid Plan

None (Fully free open source software).

Get Started

Direct link · Verified & reader-supported

Pros & Cons

Strict type safety and automatic validation for all model responses.

Zero vendor lock-in with unified interfaces across OpenAI, Anthropic, Gemini, and local SLMs.

Lightweight architecture with minimal dependencies compared to monolithic frameworks.

Native integration with Pydantic Logfire for granular observability.

Maintained by the trusted core engineering team behind Pydantic.

Requires familiarity with modern typed Python (3.10+) and Pydantic v2.

Focuses on core agent primitives rather than pre-built UI components.

2026 Migration & Procurement Guide

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