RAG Libraries

Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.

FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.

Open-source search and retrieval database for AI applications.

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

An open-source RAG-based tool for chatting with your documents.

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

Haystack — a leading open-source project in the AI/LLM ecosystem.

"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

Retrieval and Retrieval-augmented LLMs

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

[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

AI memory OS for LLM and Agent systems(moltbot,clawdbot,openclaw), enabling persistent Skill memory for cross-task skill reuse and evolution.

🧑‍🚀 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

Local Deep Research achieves ~95% on SimpleQA benchmark (tested with GPT-4.1-mini). Supports local and cloud LLMs (Ollama, Google, Anthropic, ...). Searches 10+ sources - arXiv, PubMed, web, and your private documents. Everything Local & Encrypted.

Everything you need to know to build your own RAG application

Harness LLMs with Multi-Agent Programming

Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.