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A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
AdalFlow: The library to build & auto-optimize LLM applications.
🦛 CHONK docs with Chonkie ✨ — The lightweight ingestion library for fast, efficient and robust RAG pipelines
Everything you need to know to build your own RAG application
Harness LLMs with Multi-Agent Programming
AI-powered virtual executive team — a single coherent executive persona backed by 8 specialist agents (FastAPI + Next.js).
A curated collection of practical AI projects implementing OCR systems, RAG, AI agents, and other AI use cases.
A simple, easy-to-hack GraphRAG implementation
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.
企业级 Agentic RAG 智能体 - 全链路覆盖文档解析、多路检索、意图识别、问题重写、会话记忆、MCP 工具调用与深度思考。面向真实业务场景,从 0 到 1 完整工程实现。
Easiest and laziest way for building multi-agent LLMs applications.
[ICML'26] SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal
Portable AI agent runtime for the JVM. One @Agent class runs on Spring AI, LangChain4j, Anthropic, or 9 more behind one SPI. Token streaming, tool calls, human approvals, and governance over WebSocket, SSE, gRPC, or WebTransport/HTTP3. Speaks MCP, A2A, and AG-UI.
Streamer-Sales 销冠 —— 卖货主播 LLM 大模型🛒🎁,一个能够根据给定的商品特点从激发用户购买意愿角度出发进行商品解说的卖货主播大模型。🚀⭐内含详细的数据生成流程❗ 📦另外还集成了 LMDeploy 加速推理🚀、RAG检索增强生成 📚、TTS文字转语音🔊、数字人生成 🦸、 Agent 使用网络查询实时信息🌐、ASR 语音转文字🎙️、Vue 生态搭建前端🍍、FastAPI 搭建后端🗝️、Docker-compose 打包部署🐋
Open-source multimodal retrieval engine (Morphik Core)
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
Interact with your SQL database, Natural Language to SQL using LLMs
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.
AI Agent that handles engineering tasks end-to-end: integrates with developers’ tools, plans, executes, and iterates until it achieves a successful result.
AnyCrawl 🚀: A Node.js/TypeScript crawler that turns websites into LLM-ready data and extracts structured SERP results from Google/Bing/Baidu/etc. Native multi-threading for bulk processing.
Your Cheat Sheet for AI Engineering Interview – Questions and Answers.
A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.
🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents
A native macOS app that allows users to chat with a local LLM that can respond with information from files, folders and websites on your Mac without installing any other software. Powered by llama.cpp.
RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology.
Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.
Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents
开箱即用的AI标书编写工具,标书AI生成工具,投标工具箱、知识库、标书查重、废标项检查,完全开源免费,欢迎使用