Cómo Conectar WhatsApp con ChatGPT (OpenAI)

Combina whatsmeow-node con el SDK de OpenAI para crear un chatbot de WhatsApp potenciado por GPT-4.1. Los mensajes entran por WhatsApp, se envían a OpenAI para obtener una respuesta, y la respuesta vuelve al usuario — con indicadores de escritura mientras el modelo piensa.

Requisitos Previos

Una sesión vinculada de whatsmeow-node (Cómo Vincular)
Una API key de OpenAI (configurada como variable de entorno OPENAI_API_KEY)
El SDK de OpenAI: npm install openai

Paso 1: Configurar Ambos Clientes

import { createClient } from "@whatsmeow-node/whatsmeow-node";
import OpenAI from "openai";

const client = createClient({ store: "session.db" });
const openai = new OpenAI(); // reads OPENAI_API_KEY from env

const SYSTEM_PROMPT = "You are a helpful WhatsApp assistant. Keep responses concise — under 500 characters when possible, since this is a chat interface.";

Paso 2: Manejar Mensajes Entrantes

client.on("message", async ({ info, message }) => {
  if (info.isFromMe) return;

  const text =
    (message.conversation as string) ??
    (message.extendedTextMessage as { text?: string } | undefined)?.text;
  if (!text) return;

  await client.sendChatPresence(info.chat, "composing");

  const reply = await askChatGPT(info.sender, text);
  await client.sendMessage(info.chat, { conversation: reply });
});

Paso 3: Enviar a ChatGPT

async function askChatGPT(userJid: string, userMessage: string): Promise<string> {
  const response = await openai.chat.completions.create({
    model: "gpt-4.1",
    messages: [
      { role: "system", content: SYSTEM_PROMPT },
      { role: "user", content: userMessage },
    ],
  });

  return response.choices[0].message.content ?? "I couldn't generate a response.";
}

Paso 4: Agregar Historial de Conversación

Para conversaciones multi-turno, almacena el historial de mensajes por usuario:

import type { ChatCompletionMessageParam } from "openai/resources/chat/completions";

const conversations = new Map<string, ChatCompletionMessageParam[]>();
const MAX_HISTORY = 20;

async function askChatGPT(userJid: string, userMessage: string): Promise<string> {
  const history = conversations.get(userJid) ?? [];
  history.push({ role: "user", content: userMessage });

  if (history.length > MAX_HISTORY) {
    history.splice(0, history.length - MAX_HISTORY);
  }

  const response = await openai.chat.completions.create({
    model: "gpt-4.1",
    messages: [{ role: "system", content: SYSTEM_PROMPT }, ...history],
  });

  const reply = response.choices[0].message.content ?? "I couldn't generate a response.";

  history.push({ role: "assistant", content: reply });
  conversations.set(userJid, history);

  return reply;
}

Ejemplo Completo

import { createClient } from "@whatsmeow-node/whatsmeow-node";
import OpenAI from "openai";
import type { ChatCompletionMessageParam } from "openai/resources/chat/completions";

const client = createClient({ store: "session.db" });
const openai = new OpenAI();

const SYSTEM_PROMPT =
  "You are a helpful WhatsApp assistant. Keep responses concise — under 500 characters when possible, since this is a chat interface.";

const conversations = new Map<string, ChatCompletionMessageParam[]>();
const MAX_HISTORY = 20;

async function askChatGPT(userJid: string, userMessage: string): Promise<string> {
  const history = conversations.get(userJid) ?? [];
  history.push({ role: "user", content: userMessage });

  if (history.length > MAX_HISTORY) {
    history.splice(0, history.length - MAX_HISTORY);
  }

  const response = await openai.chat.completions.create({
    model: "gpt-4.1",
    messages: [{ role: "system", content: SYSTEM_PROMPT }, ...history],
  });

  const reply = response.choices[0].message.content ?? "I couldn't generate a response.";

  history.push({ role: "assistant", content: reply });
  conversations.set(userJid, history);

  return reply;
}

client.on("message", async ({ info, message }) => {
  if (info.isFromMe) return;

  const text =
    (message.conversation as string) ??
    (message.extendedTextMessage as { text?: string } | undefined)?.text;
  if (!text) return;

  console.log(`${info.pushName}: ${text}`);
  await client.sendChatPresence(info.chat, "composing");

  try {
    const reply = await askChatGPT(info.sender, text);
    await client.sendMessage(info.chat, { conversation: reply });
    console.log(`→ ${reply.slice(0, 80)}...`);
  } catch (err) {
    console.error("OpenAI API error:", err);
    await client.sendMessage(info.chat, {
      conversation: "Sorry, I'm having trouble right now. Try again in a moment.",
    });
  }
});

client.on("logged_out", ({ reason }) => {
  console.error(`Logged out: ${reason}`);
  client.close();
  process.exit(1);
});

async function main() {
  const { jid } = await client.init();
  if (!jid) {
    console.error("Not paired! See: How to Pair WhatsApp");
    process.exit(1);
  }
  await client.connect();
  await client.sendPresence("available");
  console.log("ChatGPT bot is online!");

  process.on("SIGINT", async () => {
    await client.sendPresence("unavailable");
    await client.disconnect();
    client.close();
    process.exit(0);
  });
}

main().catch(console.error);

Errores Comunes

Bucles de eco

Siempre verifica info.isFromMe primero. Sin esto, el bot envía un mensaje, ve su propio mensaje, lo envía a ChatGPT y responde de nuevo — para siempre.

Exposición de la API key

Nunca escribas tu API key directamente en el código. Usa variables de entorno (OPENAI_API_KEY) o un archivo .env (agregado a .gitignore).

Límites de tasa en ambos lados

Tanto la API de OpenAI como WhatsApp tienen límites de tasa. Para la API de OpenAI, maneja errores 429 con backoff exponencial. Para WhatsApp, evita enviar demasiados mensajes muy rápido — consulta Límites de Tasa.

Requisitos Previos​

Paso 1: Configurar Ambos Clientes​

Paso 2: Manejar Mensajes Entrantes​

Paso 3: Enviar a ChatGPT​

Paso 4: Agregar Historial de Conversación​

Ejemplo Completo​

Errores Comunes​

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