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LangWatch integrates with LangGraph to provide detailed observability into your state graphs, node executions, and workflow patterns.

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Installation

npm i langwatch @langchain/openai @langchain/core @langchain/langgraph zod

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Usage

The LangWatch API key is configured by default via the LANGWATCH_API_KEY environment variable.
Use LangWatchCallbackHandler with your LangGraph state graph to capture node executions and workflow patterns. 
import { setupObservability } from "langwatch/observability/node";
import { LangWatchCallbackHandler } from "langwatch/observability/instrumentation/langchain";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, SystemMessage } from "@langchain/core/messages";
import { StateGraph, START, END } from "@langchain/langgraph";
import { MemorySaver } from "@langchain/langgraph";
import { z } from "zod";

setupObservability({ serviceName: "<project_name>" });

const GraphState = z.object({
  question: z.string(),
  final_answer: z.string().default(""),
});
type GraphStateType = z.infer<typeof GraphState>;

async function main(message: string): Promise<string> {
  const llm = new ChatOpenAI({ model: "gpt-5" });

  const generate = async (state: GraphStateType) => {
    const result = await llm.invoke([
      new SystemMessage("You are a helpful assistant."),
      new HumanMessage(state.question),
    ]);
    return { final_answer: result.content as string };
  };

  const app = new StateGraph(GraphState)
    .addNode("generate", generate)
    .addEdge(START, "generate")
    .addEdge("generate", END)
    .compile({ checkpointer: new MemorySaver() })
    .withConfig({ callbacks: [new LangWatchCallbackHandler()] });

  const out = await app.invoke(
    { question: message },
    { configurable: { thread_id: crypto.randomUUID() } },
  );
  return out.final_answer;
}

console.log(await main("Hey, tell me a joke"));
The LangWatchCallbackHandler captures LangGraph node executions and workflow patterns. Pass the callback handler to your compiled graph via withConfig().