在 自定义工作流 架构中，您可以使用 LangGraph 定义自己的定制执行流程。您可以完全控制图结构——包括顺序步骤、条件分支、循环和并行执行。

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主要特点

  • 完全控制图结构
  • 将确定性逻辑与智能体行为混合
  • 支持顺序步骤、条件分支、循环和并行执行
  • 将其他模式作为节点嵌入您的工作流

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何时使用

当标准模式（子智能体、技能等）不符合您的要求时、当您需要将确定性逻辑与智能体行为混合时，或者当您的用例需要复杂的路由或多阶段处理时，请使用自定义工作流。 工作流中的每个节点可以是简单函数、LLM 调用，或者是带有 工具 的完整 智能体 。您还可以在自定义工作流中组合其他架构——例如，将多智能体系统作为单个节点嵌入。 有关自定义工作流的完整示例，请参阅以下教程。

教程：构建带路由的多源知识库

路由器模式 是自定义工作流的一个示例。本教程将介绍如何构建一个路由器，它并行查询 GitHub、Notion 和 Slack，然后综合结果。

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基本实现

核心洞察是您可以在任何 LangGraph 节点内直接调用 LangChain 智能体，将自定义工作流的灵活性与预构建智能体的便利性结合起来： 
import { createAgent } from "langchain";
import { StateGraph, START, END } from "@langchain/langgraph";

const agent = createAgent({ model: "openai:gpt-4o", tools: [...] });

async function agentNode(state: typeof State.State) {
  // A LangGraph node that invokes a LangChain agent
  const result = await agent.invoke({
    messages: [{ role: "user", content: state.query }]
  });
  return { answer: result.messages.at(-1)?.content };
}

// Build a simple workflow
const workflow = new StateGraph(State)
  .addNode("agent", agentNode)
  .addEdge(START, "agent")
  .addEdge("agent", END)
  .compile();

​
Example: RAG pipeline

A common use case is combining retrieval with an agent. This example builds a WNBA stats assistant that retrieves from a knowledge base and can fetch live news.
The workflow demonstrates three types of nodes:
  • Model node (Rewrite): Rewrites the user query for better retrieval using structured output .
  • Deterministic node (Retrieve): Performs vector similarity search — no LLM involved.
  • Agent node (Agent): Reasons over retrieved context and can fetch additional information via tools.
You can use LangGraph state to pass information between workflow steps. This allows each part of your workflow to read and update structured fields, making it easy to share data and context across nodes. 
import { StateGraph, Annotation, START, END } from "@langchain/langgraph";
import { createAgent, tool } from "langchain";
import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai";
import { MemoryVectorStore } from "langchain/vectorstores/memory";
import * as z from "zod";

const State = Annotation.Root({
  question: Annotation<string>(),
  rewrittenQuery: Annotation<string>(),
  documents: Annotation<string[]>(),
  answer: Annotation<string>(),
});

// WNBA knowledge base with rosters, game results, and player stats
const embeddings = new OpenAIEmbeddings();
const vectorStore = await MemoryVectorStore.fromTexts(
  [
    // Rosters
    "New York Liberty 2024 roster: Breanna Stewart, Sabrina Ionescu, Jonquel Jones, Courtney Vandersloot.",
    "Las Vegas Aces 2024 roster: A'ja Wilson, Kelsey Plum, Jackie Young, Chelsea Gray.",
    "Indiana Fever 2024 roster: Caitlin Clark, Aliyah Boston, Kelsey Mitchell, NaLyssa Smith.",
    // Game results
    "2024 WNBA Finals: New York Liberty defeated Minnesota Lynx 3-2 to win the championship.",
    "June 15, 2024: Indiana Fever 85, Chicago Sky 79. Caitlin Clark had 23 points and 8 assists.",
    "August 20, 2024: Las Vegas Aces 92, Phoenix Mercury 84. A'ja Wilson scored 35 points.",
    // Player stats
    "A'ja Wilson 2024 season stats: 26.9 PPG, 11.9 RPG, 2.6 BPG. Won MVP award.",
    "Caitlin Clark 2024 rookie stats: 19.2 PPG, 8.4 APG, 5.7 RPG. Won Rookie of the Year.",
    "Breanna Stewart 2024 stats: 20.4 PPG, 8.5 RPG, 3.5 APG.",
  ],
  [{}, {}, {}, {}, {}, {}, {}, {}, {}],
  embeddings
);
const retriever = vectorStore.asRetriever({ k: 5 });

const getLatestNews = tool(
  async ({ query }) => {
    // Your news API here
    return "Latest: The WNBA announced expanded playoff format for 2025...";
  },
  {
    name: "get_latest_news",
    description: "Get the latest WNBA news and updates",
    schema: z.object({ query: z.string() })
  }
);

const agent = createAgent({
  model: "openai:gpt-4o",
  tools: [getLatestNews],
});

const model = new ChatOpenAI({ model: "gpt-4o" });

const RewrittenQuery = z.object({ query: z.string() });

async function rewriteQuery(state: typeof State.State) {
  const systemPrompt = `Rewrite this query to retrieve relevant WNBA information.
The knowledge base contains: team rosters, game results with scores, and player statistics (PPG, RPG, APG).
Focus on specific player names, team names, or stat categories mentioned.`;
  const response = await model.withStructuredOutput(RewrittenQuery).invoke([
    { role: "system", content: systemPrompt },
    { role: "user", content: state.question }
  ]);
  return { rewrittenQuery: response.query };
}

async function retrieve(state: typeof State.State) {
  const docs = await retriever.invoke(state.rewrittenQuery);
  return { documents: docs.map(doc => doc.pageContent) };
}

async function callAgent(state: typeof State.State) {
  const context = state.documents.join("\n\n");
  const prompt = `Context:\n${context}\n\nQuestion: ${state.question}`;
  const response = await agent.invoke({ messages: [{ role: "user", content: prompt }] });
  return { answer: response.messages.at(-1)?.contentBlocks };
}

const workflow = new StateGraph(State)
  .addNode("rewrite", rewriteQuery)
  .addNode("retrieve", retrieve)
  .addNode("agent", callAgent)
  .addEdge(START, "rewrite")
  .addEdge("rewrite", "retrieve")
  .addEdge("retrieve", "agent")
  .addEdge("agent", END)
  .compile();

const result = await workflow.invoke({ question: "Who won the 2024 WNBA Championship?" });
console.log(result.answer);
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