LangChain

Setup

Install Braintrust alongside the LangChain JS packages.

pnpm add braintrust @braintrust/langchain-js @langchain/core@^1 @langchain/openai@^1

npm install braintrust @braintrust/langchain-js @langchain/core@^1 @langchain/openai@^1

Auto-instrumentation

To trace LangChain calls without modifying your application code, initialize Braintrust normally, then run your app with Braintrust’s import hook to patch @langchain/core at runtime. Requires @langchain/core v0.3.42 or later. The same hook traces LangGraph graphs, which run through the LangChain callback path.

Initialize Braintrust and call LangChain

import { initLogger } from "braintrust";
import { ChatOpenAI } from "@langchain/openai";

initLogger({
  projectName: "My Project",
  apiKey: process.env.BRAINTRUST_API_KEY,
});

const model = new ChatOpenAI({ model: "gpt-5-mini" });

const response = await model.invoke("What is the capital of France?");
console.log(response.content);

Run with the import hook

node --import braintrust/hook.mjs trace-langchain-auto.js

The auto-instrumentation example uses plain JavaScript so node --import can run the file directly. The Braintrust APIs work the same in TypeScript projects — compile your TypeScript to JavaScript, then run the compiled file with the import hook.

If you’re using a bundler, see Trace LLM calls for plugin and loader setup.

Manual instrumentation

To trace LangChain calls manually, attach BraintrustCallbackHandler to each call’s callbacks option yourself.

import { BraintrustCallbackHandler } from "@braintrust/langchain-js";
import { ChatOpenAI } from "@langchain/openai";
import { initLogger } from "braintrust";

initLogger({
  projectName: "My Project",
  apiKey: process.env.BRAINTRUST_API_KEY,
});

const handler = new BraintrustCallbackHandler();

async function main() {
  const model = new ChatOpenAI({ modelName: "gpt-5-mini" });

  await model.invoke("What is the capital of France?", {
    callbacks: [handler],
  });
}

main();

Run it:

npx ts-node trace-langchain.ts

What Braintrust traces

Braintrust captures:

LLM and chat model calls, chains, agents, tools, and retrievers as separate spans, with inputs and outputs preserved
Token usage on LLM spans (prompt_tokens, completion_tokens, total_tokens, prompt_cached_tokens, prompt_cache_creation_tokens)
time_to_first_token on streaming responses, captured on the first new-token callback
Model name and serialized invocation parameters in span metadata
Errors from any callback captured on the span

AI providers

SDKs

Developer tools

Setup

Auto-instrumentation

Manual instrumentation

What Braintrust traces

Tracing resources

​Setup

​Auto-instrumentation

​Manual instrumentation

​What Braintrust traces

​Tracing resources

Setup

Auto-instrumentation

Manual instrumentation

What Braintrust traces

Tracing resources