标签：RAG

Postgres with GPUs for ML/AI apps.

Open-source framework for building agentic apps in JavaScript, Go, Dart, and Python, built and used in production by Google

Open-source context retrieval layer for AI agents

HelixDB is an OLTP graph database with native vector and full-text search built in Rust on Object Storage.

Learn AI and LLMs from scratch using free resources

2bit quants, kernels and runtime for consumer devices.

Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.

Context Graph for AI Native SDLC

AI-powered virtual executive team — a single coherent executive persona backed by 8 specialist agents (FastAPI + Next.js).

⚡️next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting computer-use, browser-use and coding agent, demo: https://demo.openagentai.org

A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines

Your Personal Librarian Agent. Ask anything on your computer, organize files, remember important info and files.

An AI-powered custom node for ComfyUI designed to enhance workflow automation and provide intelligent assistance

MineContext is your proactive context-aware AI partner（Context-Engineering+ChatGPT Pulse）

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.

The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

Superduper: End-to-end framework for building custom AI applications and agents.

Neo4j graph construction from unstructured data using LLMs

《大模型白盒子构建指南》：一个全手搓的Tiny-Universe

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

Eko (Eko Keeps Operating) - Build Production-ready Agentic Workflow with Natural Language - eko.fellou.ai

OpenKB: Open LLM Knowledge Base

🦛 CHONK docs with Chonkie ✨ — The lightweight ingestion library for fast, efficient and robust RAG pipelines

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

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

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

The Ruby AI framework.

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

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

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

Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.

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

A curated collection of practical AI projects implementing OCR systems, RAG, AI agents, and other AI use cases.

The open-source context layer for AI agents. PipesHub turns your company's knowledge (Slack, Drive, Jira, GitHub, Microsoft 365 and 50+ connectors) into a permission-aware workspace that agents can search, grep, navigate and cite. MCP, SDKs and built-in agents. Self-hosted.

Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.

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

[ICML'26] SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

A personal knowledge base that builds and maintains itself. Drop in sources — Claude (or Codex/Gemini) reads them, extracts knowledge, and maintains a persistent interlinked wiki. Works with Claude Code, Codex, OpenCode, Gemini CLI. No API key needed.

A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.

Your Cheat Sheet for AI Engineering Interview – Questions and Answers.

⚡FlashRAG: A Python Toolkit for Efficient RAG Research (WWW2025 Resource)

An open-source research agent system for your Zotero library.

[KDD'2026] "VideoRAG: Chat with Your Videos"

Open-source inference server and production cluster for all the models your agent needs.