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langchain-ai/langgraph-persistence

在您的LangGraph需要持久化状态、记住对话、回溯历史或配置子图检查点作用域时调用此技能。涵盖检查点器、线程ID、时间旅行、存储和子图持久化模式。

langgraph-persistence 是什么?

该技能专注于LangGraph中的状态持久化和历史回溯功能,适用于需要长期记忆、对话恢复或状态管理的AI代理场景。它支持多种持久化模式,包括使用检查点器(Checkpointers)保存状态快照、通过线程ID(thread_id)管理独立会话、以及通过时间旅行(Time Travel)功能回溯到历史节点。此外,技能还涵盖了子图(Subgraph)的独立持久化,允许开发者对复杂工作流的特定部分进行隔离管理。配合内置的存储(Store)功能,可以高效处理跨会话的状态数据。该技能广泛兼容LangGraph平台,并提供了明确的API和配置选项,帮助开发者灵活控制持久化行为。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/skills/langgraph-persistence

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langgraph-persistence 是做什么的?

当您的LangGraph需要持久化状态、记住对话、回溯历史或配置子图检查点作用域时,调用此技能。涵盖检查点器、线程ID、时间旅行、存储和子图持久化模式。

Individual skills in this repo

This repo contains 11 individual skills — each has its own dedicated page.

langchain-ai/deep-agents-core

INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.

langchain-ai/deep-agents-memory

INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.

langchain-ai/deep-agents-orchestration

INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.

langchain-ai/framework-selection

INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.

langchain-ai/langchain-dependencies

INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.

langchain-ai/langchain-fundamentals

Create LangChain agents with create_agent, define tools, and use middleware for human-in-the-loop and error handling.

langchain-ai/langchain-middleware

INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.

langchain-ai/langchain-rag

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

langchain-ai/langgraph-fundamentals

INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.

langchain-ai/langgraph-human-in-the-loop

INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.

langchain-ai/swarm

Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.

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