RAG / 向量检索排行

53AI Hub is an open-source AI portal and knowledge base for managing enterprise knowledge, AI agents, prompts, and AI tools, seamlessly integrating with Coze, Dify, FastGPT, RAGFlow. 一个AI知识库与Agent门户

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.

A bio-inspired cognitive memory engine — a new paradigm for Graph RAG.

Enhanced LanceDB memory plugin for OpenClaw — Hybrid Retrieval (Vector + BM25), Cross-Encoder Rerank, Multi-Scope Isolation, Management CLI

Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.

The easiest way to use Agentic RAG in any enterprise

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

Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make your own persistent autonomous agent on top!

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴

Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services

MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.

AdalFlow: The library to build & auto-optimize LLM applications.

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

Everything you need to know to build your own RAG application

Harness LLMs with Multi-Agent Programming

🚀 2026 最系统的 AI Agent 速成指南｜智能体实战教程 · 完整学习路径 + 实战项目 + 面试题库 · 对标大模型应用开发工程师岗位 · 覆盖LangChain / LangGraph / Coze / Dify / MCP / skills / LLM / RAG / 提示词 · 企业级部署与微调 · 从0到企业级落地 + 从学习到上线项目 + 面试准备一体化

A simple, easy-to-hack GraphRAG implementation

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

Easiest and laziest way for building multi-agent LLMs applications.