LangChain Instrumentation - LangWatch

Quick setup? Instead of following these steps manually, copy a prompt into your coding agent and it will set this up for you automatically.

LangWatch integrates with Langchain to provide detailed observability into your chains, agents, LLM calls, and tool usage.

Installation

npm i langwatch @langchain/openai @langchain/core

pnpm add langwatch @langchain/openai @langchain/core

yarn add langwatch @langchain/openai @langchain/core

bun add langwatch @langchain/openai @langchain/core

Usage

The LangWatch API key is configured by default via the LANGWATCH_API_KEY environment variable.

Use LangWatchCallbackHandler to capture Langchain events as spans within your trace.

import { setupObservability } from "langwatch/observability/node";
import { LangWatchCallbackHandler } from "langwatch/observability/instrumentation/langchain";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage } from "@langchain/core/messages";

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

async function main(message: string): Promise<string> {
  const chatModel = new ChatOpenAI({ model: "gpt-5" }).withConfig({
    callbacks: [new LangWatchCallbackHandler()],
  });

  const result = await chatModel.invoke([new HumanMessage(message)]);
  return result.content as string;
}

console.log(await main("Hey, tell me a joke"));

The LangWatchCallbackHandler captures Langchain events and converts them into detailed LangWatch spans. Pass the callback handler to your Langchain components via the callbacks option in withConfig().

Capturing RAG - Learn how to capture RAG data from LangChain retrievers and tools
Capturing Metadata and Attributes - Add custom metadata and attributes to your traces and spans
Capturing Evaluations & Guardrails - Log evaluations and implement guardrails in your LangChain applications