A comprehensive guide and reference for building agents using LangGraph 1.0, including ReAct agents, state graphs, and tool integrations.
npx skills add https://github.com/luochang212/dive-into-langgraph --skill dive-into-langgraph
LangGraph 是由 LangChain 团队开发的开源 Agent 框架。v1.0 是稳定版本,框架能力全面升级,支持中间件、状态图、多智能体等高级功能。本 skill 内容由《LangGraph 1.0 完全指南》提供。
LangGraph 1.0 完全指南:
基础依赖:
pip install \
langgraph \
"langchain[openai]" \
langchain-community \
langchain-mcp-adapters \
python-dotenv \
pydantic
使用模型供应商的大模型需要设置环境变量,推荐使用阿里云百炼(DashScope)的模型:
# 阿里云百炼 (DashScope)
# 获取地址: https://bailian.console.aliyun.com/
DASHSCOPE_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
DASHSCOPE_API_KEY=your_api_key_here
# 火山方舟 (ARK)
# 获取地址: https://console.volcengine.com/ark/
ARK_BASE_URL=https://ark.cn-beijing.volces.com/api/v3
ARK_API_KEY=your_api_key_here
# 或者其他模型供应商...
请将环境变量添加到 .env 文件,并填入你的 API key。
| 序号 | 章节 | 内容简介 | 在线阅读 | 离线阅读 |
|------|------|----------|----------|----------|
| 1 | 快速入门 | 创建你的第一个 ReAct Agent | 在线 | 本地 |
| 2 | 状态图 | 使用 StateGraph 创建工作流 | 在线 | 本地 |
| 3 | 中间件 | 预算控制、消息截断、敏感词过滤、PII 检测 | 在线 | 本地 |
| 4 | 人机交互 | 使用 HITL 中间件实现人机交互 | 在线 | 本地 |
| 5 | 记忆 | 短期记忆、长期记忆 | 在线 | 本地 |
| 6 | 上下文工程 | 使用 State、Store、Runtime 管理上下文 | 在线 | 本地 |
| 7 | MCP Server | 创建 MCP Server 并接入 LangGraph | 在线 | 本地 |
| 8 | 监督者模式 | 两种方法:tool-calling、langgraph-supervisor | 在线 | 本地 |
| 9 | 并行 | 节点并发、@task 装饰器、Map-reduce、Sub-graphs | 在线 | 本地 |
| 10 | RAG | 向量检索、关键词检索、混合检索 | 在线 | 本地 |
| 11 | 网络搜索 | DashScope、Tavily 和 DDGS | 在线 | 本地 |
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take luochang212/dive-into-langgraph from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.