Build resilient language agents as cyclic state graphs.
An AI-powered multi-agent codebase migration assistant built with LangGraph and Streamlit that plans file-by-file refactoring tasks, performs human-in-the-loop (HITL) risk review, fans out parallel refactoring workers, and aggregates...
Learn how to build a trust layer for multi-agent systems that enables secure delegation, trust scoring, and policy enforcement between AI agents.
A deep research assistant that plans, searches the web, writes to a virtual filesystem, and renders each tool call as a live card in a workspace pane. Built with CopilotKit, Deep Agents, AG-UI, and Tavily on top of Next.js + LangGraph...
Drop files — documents or source code — into a chatbot. The agent extracts entities, concepts, and relationships (or modules, classes, functions, and dependencies), then renders an interactive knowledge graph you can explore.
Generative UI system that translates natural language prompts into live, interactive shadcn/ui components and exportable React code using schema-driven composition.
A chat-driven kanban board where you and the agent work the same task list. Built with CopilotKit, AG-UI, and LangGraph on top of Next.js.
AI Blog Search is an Agentic RAG application designed to enhance information retrieval from AI-related blog posts. This system leverages LangChain, LangGraph, and Google's Gemini model to fetch, process, and analyze blog content,...
A sophisticated Retrieval-Augmented Generation (RAG) system that implements a corrective multi-stage workflow using LangGraph. This system combines document retrieval, relevance grading, query transformation, and web search to provide...
A RAG Agentic system built with Cohere's new model Command-r7b-12-2024, Qdrant for vector storage, Langchain for RAG and LangGraph for orchestration. This application allows users to upload documents, ask questions about them, and get...
A Streamlit application that demonstrates an advanced implementation of RAG Agent with intelligent query routing. The system combines multiple specialized databases with smart fallback mechanisms to ensure reliable and accurate...
The agent engineering platform.
AI agents can now use real Android and iOS apps, just like a human.
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.
An open-source reference implementation of Langgraph for AI and LLM workflows.
The batteries-included agent harness.
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
AI PDF chatbot agent built with LangChain & LangGraph.
Open-source NotebookLM alternative. Research the open web with live data(Reddit, YT, IG, TikTok, Indeed, Google Search, Maps etc) through one platform, API or MCP server. Join our Discord.
可私有部署的多租户知识智能体平台：统一 RAG、知识图谱、多智能体、MCP/Skills、沙盒与权限管理。Self-hosted knowledge agent platform for RAG, knowledge graphs and multi-agent workflows.
Autonomous Hacking Agent for Red Team.
🚀 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.
35 production-grade agentic AI architectures (Reflexion, LATS, GraphRAG, MemGPT, Voyager, BrowserAgent, ...) — a Python library and runnable textbook with multi-provider LLM support and a 17-task benchmark leaderboard.
Full toolkit for running an AI agent service built with LangGraph, FastAPI and Streamlit.
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
PipesHub is an open-source platform for securely connecting enterprise knowledge to AI. Give AI agents trusted context and your team permission-aware search with verified citations across your business systems.
A collection of scientific methods, processes, algorithms, and systems to build stories & models.
An open-source reference implementation of Langchain Mcp Adapters for AI and LLM workflows.
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear debate, risk assessment。.
