GitHub repo leaderboard by stars, growth rate and activity.
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
可私有部署的多租户知识智能体平台:统一 RAG、知识图谱、多智能体、MCP/Skills、沙盒与权限管理。Self-hosted knowledge agent platform for RAG, knowledge graphs and multi-agent workflows.
Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.
Everything you need to know to build your own RAG application
| # | Repo | Language | Stars | 30-day trend | Last updated |
|---|---|---|---|---|---|
| 1 | Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills. | Python | 36,338 | last pushed 23 hours ago | |
| 2 | An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations. | Python | 31,258 | last pushed 12 months ago | |
| 3 | This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial. | Jupyter Notebook | 29,424 | last pushed 6 days ago | |
| 4 | Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems. | Python | 26,461 | last pushed 2 days ago | |
| 5 | Code search MCP for Claude Code. Make entire codebase the context for any coding agent. | TypeScript | 12,508 | last pushed 2 months ago | |
| 6 | Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training. | C++ | 9,232 | last pushed 4 months ago | |
| 7 | Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python. | Python | 8,259 | last pushed 10 months ago | |
| 8 | 可私有部署的多租户知识智能体平台:统一 RAG、知识图谱、多智能体、MCP/Skills、沙盒与权限管理。Self-hosted knowledge agent platform for RAG, knowledge graphs and multi-agent workflows. | Python | 6,886 | last pushed 2 days ago | |
| 9 | Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes. | Python | 5,859 | last pushed 23 hours ago | |
| 10 | Everything you need to know to build your own RAG application | Jupyter Notebook | 4,156 | last pushed 1 month ago |
All · 11,474