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 modular graph-based Retrieval-Augmented Generation (RAG) system

Source code of LinearRAG at ICLR'26

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

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

the official repo for E^ 2GraphRAG: Streamlining Graph-based RAG for High Efficiency and Effectiveness

🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/

Interview challenge for building a Payment Gateway - Python version

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…

Iterative Multi-Granular RAG with Contextual Hierarchical Graph

"MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"

Open Source, Distributed, RESTful Search Engine

Fast math typesetting for the web.

Pure Ruby LDAP library

Simplified HTTP request client.