AI observability platform for production LLM and agent systems.
OpenTelemetry Instrumentation for AI Observability
AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for better code understanding and developer onboarding.
Production-ready Full-Stack AI Agent Template -- FastAPI + Next.js with 5 AI frameworks (PydanticAI, LangChain, LangGraph, CrewAI, DeepAgents), WebSocket streaming, tool approval UI, auth, multi-DB, observability, and 20+ integrations.
Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling
Python Deep Agent framework built on top of Pydantic-AI, designed to help you quickly build production-grade autonomous AI agents with planning, filesystem operations, subagent delegation, skills, and structured outputs--in just 10 lines of code.
Unlock 650+ MCP servers tools in your favorite agentic framework.
Running local Language Language Models (LLM) to perform Retrieval-Augmented Generation (RAG)
This package implements Agent Skills (https://agentskills.io) support with progressive disclosure for Pydantic AI. Supports filesystem and programmatic skills.
Drop-in tools that give AI agents reliable, permission-aware access to external systems.
The SDK to build AI agents as distributed, orchestratable microservices
Code examples for Building Effective Agents ported and adapted to use Pydantic AI
CLI for creating and evolving modular full stack Python applications over time, built on tools you already know.
Production-ready template for building AI applications with Pydantic AI, FastAPI, PostgreSQL, Redis, LiteLLM, and comprehensive monitoring. Includes admin panel, CI/CD, testing, and observability out of the box.
A library/CLI for running Agentic Slack bots with durable execution and bounded concurrency.
Python boilerplate for creating AI agents, MCP servers, API microservices and monolith services. All in one!
AI web parser library + CLI
A FastAPI extension for integrating common AI agent frameworks.
File Storage & Sandbox Backends for Pydantic AI: console tools for file operations, Docker-isolated sandboxes for safe execution, and permission system with presets for access control. Enables secure multi-user handling and testing in agents via in-memory, local, or containerized storage.
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