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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

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

[EMNLP2025] LightRAG: Simple and Fast Retrieval-Augmented Generation

Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

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.

"RAG-Anything: All-in-One RAG Framework"

Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

Unified framework for building enterprise RAG pipelines with small, specialized models

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

Agent S: an open agentic framework that uses computers like a human

Retrieval and Retrieval-augmented LLMs

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.

Open-source context retrieval layer for AI agents

The open source platform for AI-native application development.

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

AutoRAG: Now your agent can find anything in your computer. It gets smarter if you are using it frequently.

RAG (Retrieval Augmented Generation) Framework for building modular, open source applications for production by TrueFoundry

Everything you need to know to build your own RAG application

Harness LLMs with Multi-Agent Programming

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

⚡FlashRAG: A Python Toolkit for Efficient RAG Research (WWW2025 Resource)

Open-source inference server and production cluster for all the models your agent needs.

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.

All-in-one platform for search, recommendations, RAG, and analytics offered via API