在使用做出基于模型的决策的非确定性系统(例如,由 LLM 驱动的智能体)时,详细检查其决策过程可能很有用:
  1. 理解推理:分析导致成功结果的步骤。
  2. 调试错误:识别错误发生的位置和原因。
  3. 探索替代方案:测试不同的路径以发现更好的解决方案。
LangGraph 提供时光旅行功能来支持这些用例。具体来说,您可以从先前的检查点恢复执行 — 要么重放相同的状态,要么修改它以探索替代方案。在所有情况下,恢复过去的执行都会在历史中产生新的分叉。 要在 LangGraph 中使用时光旅行
  1. 运行图,使用 invokestream 方法和初始输入。
  2. 识别现有线程中的检查点:使用 @[getStateHistory] 方法检索特定 thread_id 的执行历史并找到所需的 checkpoint_id。 或者,在您希望执行暂停的节点之前设置断点。然后您可以找到记录到该断点的最新检查点。
  3. 更新图状态(可选):使用 @[updateState] 方法在检查点修改图的状态并从替代状态恢复执行。
  4. 从检查点恢复执行:使用 invokestream 方法,输入为 null,配置包含适当的 thread_idcheckpoint_id
有关时光旅行的概念概述,请参阅时光旅行

在工作流程中

此示例构建了一个简单的 LangGraph 工作流程,该工作流程生成一个笑话主题并使用 LLM 编写笑话。它演示如何运行图、检索过去的执行检查点、可选地修改状态以及从选择的检查点恢复执行以探索替代结果。

设置

首先我们需要安装所需的包
npm install @langchain/langgraph @langchain/anthropic
接下来,我们需要为 Anthropic(我们将使用的 LLM)设置 API 密钥
process.env.ANTHROPIC_API_KEY = "YOUR_API_KEY";
注册 LangSmith 以快速发现问题并提高 LangGraph 项目的性能。LangSmith 让您使用跟踪数据来调试、测试和监控使用 LangGraph 构建的 LLM 应用程序。
import { v4 as uuidv4 } from "uuid";
import * as z from "zod";
import { StateGraph, START, END } from "@langchain/langgraph";
import { ChatAnthropic } from "@langchain/anthropic";
import { MemorySaver } from "@langchain/langgraph";

const State = z.object({
  topic: z.string().optional(),
  joke: z.string().optional(),
});

const model = new ChatAnthropic({
  model: "claude-sonnet-4-5-20250929",
  temperature: 0,
});

// Build workflow
const workflow = new StateGraph(State)
  // Add nodes
  .addNode("generateTopic", async (state) => {
    // LLM call to generate a topic for the joke
    const msg = await model.invoke("Give me a funny topic for a joke");
    return { topic: msg.content };
  })
  .addNode("writeJoke", async (state) => {
    // LLM call to write a joke based on the topic
    const msg = await model.invoke(`Write a short joke about ${state.topic}`);
    return { joke: msg.content };
  })
  // Add edges to connect nodes
  .addEdge(START, "generateTopic")
  .addEdge("generateTopic", "writeJoke")
  .addEdge("writeJoke", END);

// Compile
const checkpointer = new MemorySaver();
const graph = workflow.compile({ checkpointer });

1. Run the graph

const config = {
  configurable: {
    thread_id: uuidv4(),
  },
};

const state = await graph.invoke({}, config);

console.log(state.topic);
console.log();
console.log(state.joke);
Output:
How about "The Secret Life of Socks in the Dryer"? You know, exploring the mysterious phenomenon of how socks go into the laundry as pairs but come out as singles. Where do they go? Are they starting new lives elsewhere? Is there a sock paradise we don't know about? There's a lot of comedic potential in the everyday mystery that unites us all!

# The Secret Life of Socks in the Dryer

I finally discovered where all my missing socks go after the dryer. Turns out they're not missing at all—they've just eloped with someone else's socks from the laundromat to start new lives together.

My blue argyle is now living in Bermuda with a red polka dot, posting vacation photos on Sockstagram and sending me lint as alimony.

2. Identify a checkpoint

// The states are returned in reverse chronological order.
const states = [];
for await (const state of graph.getStateHistory(config)) {
  states.push(state);
}

for (const state of states) {
  console.log(state.next);
  console.log(state.config.configurable?.checkpoint_id);
  console.log();
}
Output:
[]
1f02ac4a-ec9f-6524-8002-8f7b0bbeed0e

['writeJoke']
1f02ac4a-ce2a-6494-8001-cb2e2d651227

['generateTopic']
1f02ac4a-a4e0-630d-8000-b73c254ba748

['__start__']
1f02ac4a-a4dd-665e-bfff-e6c8c44315d9
// This is the state before last (states are listed in chronological order)
const selectedState = states[1];
console.log(selectedState.next);
console.log(selectedState.values);
Output:
['writeJoke']
{'topic': 'How about "The Secret Life of Socks in the Dryer"? You know, exploring the mysterious phenomenon of how socks go into the laundry as pairs but come out as singles. Where do they go? Are they starting new lives elsewhere? Is there a sock paradise we don\\'t know about? There\\'s a lot of comedic potential in the everyday mystery that unites us all!'}

3. Update the state

updateState will create a new checkpoint. The new checkpoint will be associated with the same thread, but a new checkpoint ID.
const newConfig = await graph.updateState(selectedState.config, {
  topic: "chickens",
});
console.log(newConfig);
Output:
{'configurable': {'thread_id': 'c62e2e03-c27b-4cb6-8cea-ea9bfedae006', 'checkpoint_ns': '', 'checkpoint_id': '1f02ac4a-ecee-600b-8002-a1d21df32e4c'}}

4. Resume execution from the checkpoint

await graph.invoke(null, newConfig);
Output:
{
  'topic': 'chickens',
  'joke': 'Why did the chicken join a band?\n\nBecause it had excellent drumsticks!'
}

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