RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

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

Neo4j graph construction from unstructured data using LLMs

A simple, easy-to-hack GraphRAG implementation

Reliable LLM Memory for AI Applications and AI Agents

Dify in ComfyUI includes Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llms with similar openai/gemini interfaces, such as o1,ollama, qwen, GLM, deepseek, moonshot,doubao. Adapted to local llms, vlm, gguf such as llama-3.2, Linkage neo4j KG, graphRAG / RAG / html 2 img

A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG).

GraphRAG4OpenWebUI integrates Microsoft's GraphRAG technology into Open WebUI, providing a versatile information retrieval API. It combines local, global, and web searches for advanced Q&A systems and search engines. This tool simplifies graph-based retrieval integration in open web environments.

OriginTrail Decentralized Knowledge Graph network node

https://TiDB.AI is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage and LlamaIndex. Open source and free to use.

参考GraphRag使用 Semantic Kernel 来实现的dotnet版本，可以使用NuGet开箱即用集成到项目中

添加🚀流式 Web 服务到 GraphRAG，兼容 OpenAI SDK，支持可访问的实体链接🔗，支持建议问题，兼容本地嵌入模型，修复诸多问题。Add streaming web server to GraphRAG, compatible with OpenAI SDK, support accessible entity link, support advice question, compatible with local embedding model, fix lots of issues.

Neo4j GraphRAG for Python

GraphRAG-Ollama-UI GraphRAG4OpenWebUI 融合版（有gradio webui配置生成RAG索引，有fastapi提供RAG API服务）

Unleash the Power of GraphRAG with Autonomous Knowledge Agents 🚀

A web-based tool for visualizing and exploring artifacts from Microsoft's GraphRAG.

Facilitate the creation of graph-based Retrieval-Augmented Generation (RAG), seamless integration with OpenAI to enable advanced data querying and knowledge graph construction.

See how to augment LLMs with real-time data for dynamic, context-aware apps - Rag Agents GraphRAG.

The long-term memory for your Superagents 🥷and LLMs 🤖. Built with GraphRAG, Knowledge graphs and autonomous ai agents

GraphRAG / From Local to Global: A Graph RAG Approach to Query-Focused Summarization