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                *   [Callbacks in custom Chains](/v0.1/docs/modules/callbacks/how_to/creating_subclasses/)
                *   [Tags](/v0.1/docs/modules/callbacks/how_to/tags/)
                *   [Listeners](/v0.1/docs/modules/callbacks/how_to/with_listeners/)
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*   [](/v0.1/)
*   [Modules](/v0.1/docs/modules/)
*   More
*   [Callbacks](/v0.1/docs/modules/callbacks/)
*   How-to
*   Listeners

Listeners
=========

LangChain callbacks offer a method `withListeners` which allow you to add event listeners to the following events:

*   `onStart` - called when the chain starts
*   `onEnd` - called when the chain ends
*   `onError` - called when an error occurs

These methods accept a callback function which will be called when the event occurs. The callback function can accept two arguments:

*   `input` - the input value, for example it would be `RunInput` if used with a Runnable.
*   `config` - an optional config object. This can contain metadata, callbacks or any other values passed in as a config object when the chain is started.

Below is an example which demonstrates how to use the `withListeners` method:

tip

See [this section for general instructions on installing integration packages](/v0.1/docs/get_started/installation/#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install @langchain/openai

    yarn add @langchain/openai

    pnpm add @langchain/openai

    import { ChatOpenAI } from "@langchain/openai";import { Run } from "@langchain/core/tracers/base";import { ChatPromptTemplate } from "@langchain/core/prompts";const prompt = ChatPromptTemplate.fromMessages([  ["ai", "You are a nice assistant."],  ["human", "{question}"],]);const model = new ChatOpenAI({});const chain = prompt.pipe(model);const trackTime = () => {  let start: { startTime: number; question: string };  let end: { endTime: number; answer: string };  const handleStart = (run: Run) => {    start = {      startTime: run.start_time,      question: run.inputs.question,    };  };  const handleEnd = (run: Run) => {    if (run.end_time && run.outputs) {      end = {        endTime: run.end_time,        answer: run.outputs.content,      };    }    console.log("start", start);    console.log("end", end);    console.log(`total time: ${end.endTime - start.startTime}ms`);  };  return { handleStart, handleEnd };};const { handleStart, handleEnd } = trackTime();await chain  .withListeners({    onStart: (run: Run) => {      handleStart(run);    },    onEnd: (run: Run) => {      handleEnd(run);    },  })  .invoke({ question: "What is the meaning of life?" });/** * start { startTime: 1701723365470, question: 'What is the meaning of life?' }end {  endTime: 1701723368767,  answer: "The meaning of life is a philosophical question that has been contemplated and debated by scholars, philosophers, and individuals for centuries. The answer to this question can vary depending on one's beliefs, perspectives, and values. Some suggest that the meaning of life is to seek happiness and fulfillment, others propose it is to serve a greater purpose or contribute to the well-being of others. Ultimately, the meaning of life can be subjective and personal, and it is up to each individual to determine their own sense of purpose and meaning."}total time: 3297ms */

#### API Reference:

*   [ChatOpenAI](https://api.js.langchain.com/classes/langchain_openai.ChatOpenAI.html) from `@langchain/openai`
*   [Run](https://api.js.langchain.com/interfaces/langchain_core_tracers_base.Run.html) from `@langchain/core/tracers/base`
*   [ChatPromptTemplate](https://api.js.langchain.com/classes/langchain_core_prompts.ChatPromptTemplate.html) from `@langchain/core/prompts`

* * *

#### Help us out by providing feedback on this documentation page:

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