Retrieval-augmented generation (RAG) makes a language model answer from your own documents. The text is split into chunks, turned into vectors and stored in an index, and the most relevant chunks are added to the prompt when a question comes in. The projects here cover the whole pipeline or one part of it: document parsing, vector search, or a complete question-answering app.
Answer quality in RAG depends mostly on retrieval, not on the model. Compare how each project handles difficult documents such as PDFs, tables and scans, whether it supports hybrid search that combines keywords with vectors and re-ranking, and whether it shows which sources an answer came from.
BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
Incremental engine for long horizon agents 🌟 Star if you like it!
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings.
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/
A curated list of 120+ LLM libraries category wise.
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.
A collection of sample agents built with Agent Development Kit (ADK)
Production ready toolkit to run AI locally
https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习｜数据合成
https://arxiv.org/abs/2606.28344. The end of web parsing. The beginning of scalable pixel-native search. link: https://pixelrag.ai/
Crawlee—A web scraping and browser automation library for Python to build reliable crawlers. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Parsel, BeautifulSoup, Playwright, and raw HTTP. Both headful and headless mode. With proxy rotation.
Polyglot document intelligence with a Rust core: extract text, metadata, images, tables, and structured data from 106 formats across 140 file extensions, plus code intelligence for 371 languages. Fifteen bindings, with CLI, REST API, and MCP server.
智能闲鱼客服机器人系统：专为闲鱼平台打造的AI值守解决方案，实现闲鱼平台7×24小时自动化值守，支持多专家协同决策、智能议价和上下文感知对话。
Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.
High accuracy RAG for answering questions from scientific documents with citations
~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.
PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.
程序员鱼皮的编程宝典 ⭐️ 2026年最全编程学习路线图！包含Java学习路线、前端学习路线、Python学习路线、C++学习路线、算法学习路线、计算机基础学习路线、AI应用开发学习路线、AI Agent开发学习路线等。提供编程入门教程、AI大模型应用开发教程、RAG开发实战、MCP开发教程、Prompt工程指南、LLM应用开发、技术知识分享、学习资源推荐、项目实战教程、热门面试题、求职经验、简历优化、编程自学指南等内容，适用于所有零基础学编程、学习AI开发、转行程序员、计算机专业学生、求职找工作的同学 💎 编程学习，就来编程导航！
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
谷歌新书Agent设计模式(agentic design patterns)最佳中文版，持续优化。附：在线阅读、pdf和epub电子书下载。
World's first open-source enterprise world model.
Build autonomous AI agents in Python.