#Retrieval-augmented-generation
Showing 60 of 340 repositories tagged #retrieval-augmented-generation, ranked by stars
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.
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
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
📑 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]: 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.
🧑🚀 全世界最好的LLM资料总结（多模态生成、Agent、辅助编程、AI审稿、数据处理、模型训练、模型推理、o1 模型、MCP、小语言模型、视觉语言模型） | Summary of the world's best LLM resources.
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
Open-source context retrieval layer for AI agents
The open source platform for AI-native application development.
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
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
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Harness LLMs with Multi-Agent Programming
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
[KDD'2026] "VideoRAG: Chat with Your Videos"
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.
All-in-one platform for search, recommendations, RAG, and analytics offered via API
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
Awesome-GraphRAG: A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation.
Distributed vector search for AI-native applications
The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs
NestJS Helper + AI Chatbot Development
Open-source inference server and production cluster for all the models your agent needs.
[ACL2026] "MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
[EMNLP 2025 Oral] MemoryOS is designed to provide a memory operating system for personalized AI agents.
List of software that allows searching the web with the assistance of AI: https://hf.co/spaces/felladrin/awesome-ai-web-search
Comprehensive guide to learn RAG from basics to advanced.
Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models
😎 Awesome list of Retrieval-Augmented Generation (RAG) applications in Generative AI.
The SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime for agentic AI. Secure, modular, and production-ready, it lets developers build, run, and manage intelligent agents across local, cloud, and edge environments.
TrustRAG：The RAG Framework within Reliable input,Trusted output
🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.
TypeScript AI AI Function Calling Framework enhanced by compiler skills.
Embeddable vector database for Go with Chroma-like interface and zero third-party dependencies. In-memory with optional persistence.
Ship RAG based LLM web apps in seconds.
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.
A complete guide to start and improve your LLM skills in 2026 with little background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
Parsing-free RAG supported by VLMs
Rust library for generating vector embeddings, reranking locally!
RAG-Fusion: multi-query generation + Reciprocal Rank Fusion for better retrieval-augmented generation. Includes evaluation harness with NFCorpus/BEIR.
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations!