The agent engineering platform.

Build resilient agents.

The batteries-included agent harness.

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.

🚀 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

📚 《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

The batteries included agent harness.

What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation.

🚀 JoySafeter: An enterprise AI Agent Platform—Not just chatting. building、running、testing, and tracing autonomous Agent Teams with visual orchestration...

Convert sessions across harnesses to a unified trajectory format - designed to be consumed by agents (e.g. for memory formation, dreaming, search)

LambChat — Enterprise Agent Infra for governed AI agents. Skills + MCP powered, Loop Agent ready, multi-tenant by design.

🔎 深度研搜对话式多智能体 AI Agents，最适合系统学习 DeepAgents 的实战项目｜AI Deep Research Agent 实战 · LangGraph + RAGFlow + Tavily + FastAPI + WebSocket 从0到工程化落地。前后端完整代码全栈可跑，Docker 环境一键部署，配套 ai-agents-from-zero 免费教程与章节代码分支。适合系统学习大模型应用、多智能体 Agent 和企业级 AI 工程落地

Visualize live LangGraph execution and see how your agent thinks as it runs.

Multi-language agent runtime and library for execution scope management, lifecycle events, and middleware on tool and LLM calls.

S3, PostgreSQL, Azure Blob, GCS, MongoDB, and Redis remote backends for LangChain Deep Agents

Learn GenAI and Agentic AI from Zero to Production

Open-source sandboxes for AI agents — run untrusted, AI-generated code safely on your own machine.

An open-source AI-powered frontend development platform built on DeepAgents and LangGraph. Generate complete React applications through natural language conversations.

Food tour planner using LangChain DeepAgents, Google Maps API, and Tavily research. Explore multi-agent coordination patterns: task delegation via SubAgentMiddleware, planning with TodoListMiddleware

Task Planning and Tracking toolset for Pydantic AI agents, enabling hierarchical task management with subtasks, PostgreSQL storage for multi-tenancy, and an event system for webhooks and callbacks.