The Open Standard for Generative UI
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Python tool for converting files and office documents to Markdown.
The agent engineering platform.
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM]
【低代码v2.0,一句话即可生成整个系统】企业级AI低代码平台,一键生成前后端代码甚至整个系统。 AI Skills 一句话画流程、设计表单、生成报表、大屏。内置 AI应用平台涵盖:AI聊天、知识库、流程编排、MCP插件等,兼容主流大模型。引领AI低代码「Skills 生成 → 在线配置 → 代码生成 → 手工合并->AI修改」开发模式,解决 Java 项目 90% 重复工作,提高效率又不失灵活。
Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active
Build resilient agents.
🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.
This repository contains the Hugging Face Agents Course.
The batteries-included agent harness.
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Run agents like Hermes, LangChain Deep Agents, and OpenClaw more securely inside NVIDIA OpenShell with managed inference
程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程,分享 OpenClaw 保姆级教程、大模型玩法(DeepSeek / GPT / Gemini / Claude / GLM)、最新 AI 资讯、Prompt 提示词大全、AI 知识百科(Agent Skills / RAG / MCP / A2A)、AI 编程教程(Harness Engineering)、AI 工具用法(Cursor / Claude Code / TRAE / Codex / Copilot)、AI 开发框架教程(Spring AI / LangChain)、AI 产品变现指南,帮你快速掌握 AI 技术,走在时代前沿。本项目为开源文档 aiguide,已升级为鱼皮 AI 导航网站
The agent engineering platform
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
OpenWiki is a CLI that writes and maintains agent documentation for your codebase.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
The open-source hub to build & deploy GPT/LLM Agents ⚡️
The ultimate LLM/AI application development framework in Go.
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.
[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
🔍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/
AI Observability & Evaluation
ChatGPT 中文指南🔥,ChatGPT 中文调教指南,指令指南,应用开发指南,精选资源清单,更好的使用 chatGPT 让你的生产力 up up up! 🚀
An Open-Source Asynchronous Coding Agent
LangChain for Go, the easiest way to write LLM-based programs in Go
😎 Awesome list of tools and projects with the awesome LangChain framework
Fully local web research and report writing assistant
Semantic cache for LLMs. Fully integrated with LangChain and llama_index.
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
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Autonomous Hacking Agent for Red Team
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.
⚡️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
🚀 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
Langchain + Docker + Neo4j + Ollama
Neo4j graph construction from unstructured data using LLMs
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
Everything you need to know to build your own RAG application
Easiest and laziest way for building multi-agent LLMs applications.
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.
Knowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
Framework to build resilient language agents as graphs.
AI agents can now use real Android and iOS apps, just like a human.
🦜💬 Web app for interacting with any LangGraph agent (PY & TS) via a chat interface.
The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable.
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📲 An agent for sourcing, curating, and scheduling social media posts with human-in-the-loop.
📚 《Deep Agents 实战》—— LangChain 官方大使出品,基于 LangChain / LangGraph 生态,从零构建生产级 AI Agent 的完整指南
A production-ready FastAPI template for building AI agent applications with LangGraph integration. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services.