Awesome Pydantic AI

An opinionated list of awesome Pydantic AI frameworks, libraries, software and resources.

Pydantic AI is a Python agent framework designed to make it easier to build production-grade applications with Generative AI. It brings the "FastAPI feeling" to AI development with type safety, dependency injection, and structured outputs.

Contents

• Official Resources
• Frameworks & Libraries
• Templates & Boilerplates
• Examples & Tutorials
• Observability
• Articles & Blog Posts
• Case Studies
• Contributing

Official Resources

• Pydantic AI Documentation - Official documentation with guides, API reference, and examples.
• Pydantic AI Repository - Official GitHub repository. Agent framework with model-agnostic architecture, type safety, dependency injection, tool integration, and structured outputs.

Frameworks & Libraries

• pai-agent-sdk - Application framework for building AI agents with Pydantic AI. Provides full developer control without abstraction overhead, featuring environment-based architecture, resumable sessions, hierarchical subagents, and human-in-the-loop approval workflows.
• pydantic-deep - Python framework for building production-grade autonomous agents. Extends Pydantic AI with agent orchestration, task planning, subagent delegation, context management, and multiple backend support.
• pydantic-ai-middleware - Lightweight middleware library providing clean before/after hooks without imposed guardrail structure. Supports input/output processing, tool management, error handling, rate limiting, and audit logging.
• pydantic-ai-backend - File storage, sandbox backends, and console toolset for pydantic-ai agents. Includes LocalBackend, StateBackend, DockerSandbox, and pre-configured Docker runtimes.
• pydantic-ai-todo - Standalone task planning library for pydantic-ai agents. Provides read_todos and write_todos tools with flexible storage backends.
• subagents-pydantic-ai - Multi-agent orchestration library with dual-mode execution (sync/async), dynamic agent creation, and parent-child communication via ask_parent tool.
• summarization-pydantic-ai - Automatic conversation summarization and context management. Provides SummarizationProcessor for LLM-based summaries and SlidingWindowProcessor for zero-cost message trimming.
• pydantic-ai-filesystem-sandbox - Secure filesystem sandbox toolset with LLM-friendly errors. Provides sandboxing, read/write control, granular permissions, and human-in-the-loop approval workflows.
• pydantic-ai-skills - Standardized framework for building and managing Agent Skills. Features progressive disclosure, type-safe design, multi-directory support, and Anthropic Agent Skills compatibility.
• pydantic-ai-toolguard - Deny-first tool authorization capability for pydantic-ai agents. Implements glob-based permission rules, parameter conditions, schedule windows, rate limiting, approval workflows, and append-only audit logging. Built on the AgentsID permission specification.
• pydantic-collab - Multi-agent orchestration framework for building agent teams. Agents collaborate via handoffs, consultations (tool calls), and shared memory on top of pre-built and custom network topologies, Logfire observability included.

Templates & Boilerplates

• full-stack-fastapi-nextjs-llm-template - Production-ready project generator for AI/LLM applications. Combines FastAPI backend with Next.js 15 frontend, WebSocket streaming, JWT auth, multiple database options, and 20+ enterprise integrations.

Examples & Tutorials

• pydantic-ai-examples - Curated collection of examples demonstrating Pydantic AI usage including direct model requests, sentiment classification, dynamic classification, local models with Ollama, and conversation history management.
• pydantic-ai-rlm - Recursive Language Models with Pydantic AI.
• Pydantic AI Walkthrough - Interactive notebook covering agents, structured outputs, tool use, dependency injection, and building a Gradio chat UI with Pydantic AI. Created by Nicolai Thomsen.
• Pydantic AI: Build Type-Safe LLM Agents in Python - RealPython tutorial on creating language model agents with validated structured outputs, function calling, and dependency injection.

Observability

• Pydantic Logfire - Observability platform for Python applications built by the Pydantic team. Provides logging, tracing, metrics with SQL query interface, OpenTelemetry foundation, and native Pydantic integration.

Articles & Blog Posts

• Building Production-Grade AI Agents: How We Brought Deep Agent Patterns to Pydantic - Introduction to pydantic-deep framework and deep agent architectural patterns for production AI systems.
• Production-Ready Template for AI/LLM Applications: FastAPI + Next.js + 20+ Integrations - Guide to fastapi-fullstack CLI tool that generates complete full-stack AI applications with enterprise integrations.

Case Studies

• Mixam: AI Agent for Order Recommendation - How Mixam, a global self-publishing company, used Pydantic AI to create an AI agent that helps customers navigate complex printing specifications.
• Sophos: Unified Observability with Logfire - How Sophos implemented Pydantic Logfire for unified observability across their AI-powered security solutions, achieving end-to-end visibility and proactive issue detection.
• Boosted.ai: Monitoring AI Investment Research - How Boosted.ai uses Pydantic Logfire to monitor 50,000+ concurrent AI workflows processing billions of tokens daily, reducing issue diagnosis time significantly.

Contributing

Contributions are welcome! Please read the contribution guidelines first.

License

This work is licensed under a Creative Commons Attribution 4.0 International License.