RAG / 向量检索排行

基于LangChain、FastAPI和React的RAG项目，主分支为基于RAG的智能笔记助手，base-rag分支为开箱即用的基础RAG项目供学习使用

Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

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

Java 8+ agentic SDK: unified LLM access (OpenAI/Anthropic/DashScope/Doubao/DeepSeek...), Tool Calling, MCP, RAG, Agent Runtime, and a built-in Coding Agent CLI/TUI/ACP.

《动手学SpringAI》包含SSE流/Agent智能体/知识图谱RAG/FunctionCall/历史消息/图片生成/图片理解/Embedding/VectorDatabase/RAG

Fully neural approach for text chunking

RuoYi-AI user frontend for AI conversations, agent interactions, and knowledge-base Q&A.

Turn local files into searchable context for AI agents.

Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.

Paper-Agent 是一个面向科研人员和学生的智能论文检索与调研工具。项目基于多智能体协作架构（LangGraph），通过自然语言处理（NLP）、自动化搜索，帮助用户高效查找学术论文、分析文献内容，并进行论文调研。Paper-Agent 支持多平台集成、关键词搜索、自动分析、论文调研，提升了学术研究的效率。适用于论文写作、学术调研、科研项目管理等多种场景，是学术调研的理想助手。

Talk with your notes in Claude. RAG over your Apple Notes using Model Context Protocol.

Retrieval-augmented generation (RAG) template powered by the AI SDK.

Build your own ChatPDF and run it locally

WenShape文枢(原NOVIX写作):深度上下文感知的智能体小说创作系统/A Deep Context-Aware Agent-Based Novel Creation System

A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.

Serverless Modal + FastAPI + React + ColPali + Qdrant + GPT4o Vision RAG (V-RAG) Demo

Open Source LLM toolkit to build trustworthy LLM applications. TigerArmor (AI safety), TigerRAG (embedding, RAG), TigerTune (fine-tuning)

Turn any document into clean, AI-ready Markdown. Local-first desktop app: reads scanned PDFs, batches folders, runs offline, and uses far fewer tokens than vision models.

RAG evaluation without the need for "golden answers"

The Official Repo for "Quick Start Guide to Large Language Models"