LangChain.js

npm install @langchain/core @langchain/openai \
  @arizeai/openinference-instrumentation-langchain \
  @arizeai/openinference-semantic-conventions \
  @opentelemetry/api \
  @opentelemetry/exporter-trace-otlp-proto \
  @opentelemetry/instrumentation \
  @opentelemetry/resources \
  @opentelemetry/sdk-trace-base \
  @opentelemetry/sdk-trace-node \
  @opentelemetry/semantic-conventions

export ARIZE_SPACE_ID="<your-space-id>"
export ARIZE_API_KEY="<your-api-key>"
export ARIZE_PROJECT_NAME="langchain-js-tracing-example"
export OPENAI_API_KEY="<your-openai-api-key>"

// instrumentation.ts
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-proto";
import { resourceFromAttributes } from "@opentelemetry/resources";
import { SimpleSpanProcessor } from "@opentelemetry/sdk-trace-base";
import { NodeTracerProvider } from "@opentelemetry/sdk-trace-node";
import { ATTR_SERVICE_NAME } from "@opentelemetry/semantic-conventions";
import {
  SEMRESATTRS_PROJECT_NAME,
} from "@arizeai/openinference-semantic-conventions";
import {
  LangChainInstrumentation,
} from "@arizeai/openinference-instrumentation-langchain";
import * as CallbackManagerModule from "@langchain/core/callbacks/manager";

const projectName =
  process.env.ARIZE_PROJECT_NAME ?? "langchain-js-tracing-example";

export const provider = new NodeTracerProvider({
  resource: resourceFromAttributes({
    [ATTR_SERVICE_NAME]: projectName,
    [SEMRESATTRS_PROJECT_NAME]: projectName,
  }),
  spanProcessors: [
    new SimpleSpanProcessor(
      new OTLPTraceExporter({
        url: "https://otlp.arize.com/v1/traces",
        headers: {
          "arize-space-id": process.env.ARIZE_SPACE_ID ?? "",
          "arize-api-key": process.env.ARIZE_API_KEY ?? "",
        },
      }),
    ),
  ],
});

provider.register();

const instrumentation = new LangChainInstrumentation();
instrumentation.manuallyInstrument(CallbackManagerModule);

console.log("Arize AX tracing initialized for LangChain.js.");

// example.ts

// Importing instrumentation first ensures tracing is set up before any
// LangChain client is created.
import { provider } from "./instrumentation";

import { ChatOpenAI } from "@langchain/openai";
import { ChatPromptTemplate } from "@langchain/core/prompts";
import { StringOutputParser } from "@langchain/core/output_parsers";

// ChatOpenAI reads OPENAI_API_KEY from the environment.
const model = new ChatOpenAI({ model: "gpt-5" });
const prompt = ChatPromptTemplate.fromTemplate(
  "Answer the question concisely.\nQuestion: {question}\nAnswer:",
);
const chain = prompt.pipe(model).pipe(new StringOutputParser());

const result = await chain.invoke({
  question: "Why is the ocean salty? Answer in two sentences.",
});

console.log(result);

// Flush any pending spans before the process exits.
await provider.forceFlush();