RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

A programming framework for agentic AI

DeerFlow is a community-driven Deep Research framework, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

A model-driven approach to building AI agents in just a few lines of code.

AG2 (formerly AutoGen): The Open-Source AgentOS. Join us at: https://discord.gg/sNGSwQME3x

DeepAnalyze is the first agentic LLM for autonomous data science. 🎈你的AI数据分析师，自动分析大量数据，一键生成专业分析报告！

An Efficient and User-Friendly Scaling Library for Reinforcement Learning with Large Language Models

Seamlessly integrate LLMs as Python functions

Awesome list of 300+ agentic AI resources

An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.

Linkedin Automation Tool: Visit Profile, Connect, Message with AI

A set of tools that gives agents powerful capabilities.

Windows Agent Arena (WAA) 🪟 is a scalable OS platform for testing and benchmarking of multi-modal AI agents.

Agent samples built using the Strands Agents SDK.

Agentic RAG R1 Framework via Reinforcement Learning

An example agent demonstrating streaming, tool use, and interactivity from your terminal. This agent builder can help you to build your own agents and tools.

MCPMark is a comprehensive, stress-testing MCP benchmark designed to evaluate model and agent capabilities in real-world MCP use.

TapeAgents is a framework that facilitates all stages of the LLM Agent development lifecycle

PowerMem: Your AI-Powered Long-Term Memory — Accurate, Agile, Affordable.