Como Conectar o WhatsApp ao ChatGPT (OpenAI)

Combine o whatsmeow-node com o SDK da OpenAI para criar um chatbot de WhatsApp com GPT-4.1. As mensagens chegam pelo WhatsApp, são enviadas para a OpenAI para gerar uma resposta, e a resposta volta para o usuário — com indicadores de digitação enquanto o modelo pensa.

Pré-requisitos

Uma sessão pareada do whatsmeow-node (Como Parear)
Uma chave de API da OpenAI (defina como variável de ambiente OPENAI_API_KEY)
O SDK da OpenAI: npm install openai

Passo 1: Configurar os Dois Clients

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.";

Passo 2: Tratar Mensagens Recebidas

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 });
});

Passo 3: Enviar para o 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.";
}

Passo 4: Adicionar Histórico de Conversas

Para conversas com múltiplas trocas, armazene o histórico de mensagens por usuário:

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;
}

Exemplo 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);

Erros Comuns

Loops de eco

Sempre verifique info.isFromMe primeiro. Sem isso, o bot envia uma mensagem, vê a própria mensagem, manda para o ChatGPT e responde de novo — para sempre.

Exposição da chave de API

Nunca coloque sua chave de API diretamente no código. Use variáveis de ambiente (OPENAI_API_KEY) ou um arquivo .env (adicionado ao .gitignore).

Rate limits dos dois lados

Tanto a API da OpenAI quanto o WhatsApp têm rate limits. Para a API da OpenAI, trate erros 429 com backoff exponencial. Para o WhatsApp, evite enviar muitas mensagens muito rápido — veja Rate Limiting.

Pré-requisitos​

Passo 1: Configurar os Dois Clients​

Passo 2: Tratar Mensagens Recebidas​

Passo 3: Enviar para o ChatGPT​

Passo 4: Adicionar Histórico de Conversas​

Exemplo Completo​

Erros Comuns​

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