/ChatGPT-on-WeChat

Deploy your WeChat bot powered by OpenAI within 2 steps!

Primary LanguageTypeScript

ChatGPT on WeChat! License: ISC wakatime

Turn your WeChat into an auto-reply bot powered by ChatGPT!

Your Chat Bot in Group Chat!

Acknowledgement & Features

This project is implemented based on this amazing project and Wechaty SDK, but with a major adjustment: using the official OpenAI API Key to replace the previous pesudo-browser method, so it has the following features:

  • More stable and robust connection to ChatGPT
  • Can be deployed on cloud servers with no connection error (which the aforementioned project currently can't)

0. Table of Content

1. How to Deploy this Bot?

You can deploy in local or deploy on cloud, whatever you want.

1.1 Deploy in Local

1.1.1 Get your OpenAI API keys for ChatGPT


1.1.2 Configure Environment Variables

You can copy the template config.yaml.example into a new file config.yaml, and paste the configurations:

openaiApiKey: "<your_openai_api_key>"
openaiOrganizationID: "<your_organization_id>"
chatgptTriggerKeyword: "<your_keyword>"

Or you can export the environment variables listed in .env.sample to your system, which is a more encouraged method to keep your OpenAI API Key safe:

export OPENAI_API_KEY="sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
export OPENAI_ORGANIZATION_KEY="org-XXXXXXXXXXXXXXX"
export CHATGPT_TRIGGER_KEYWORD="Hi bot:"

Please note:

  • chatgptTriggerKeyword is the keyword which can trigger auto-reply:
    • In private chat, the message starts with it will trigger auto-reply
    • In group chat, the message starts with @Name <keyword> will trigger auto-reply (Here @Name means "@ the bot" in the group chat)
  • chatgptTriggerKeyword can be empty string, which means:
    • In private chat, every messages will trigger auto-reply
    • In group chat, only "@ the bot" will trigger auto-reply

1.1.3 Setup the Docker

  1. Setup Docker Image
docker build -t chatgpt-on-wechat .
  1. Setup Docker Container
docker run -v $(pwd)/config.yaml:/app/config.yaml chatgpt-on-wechat

1.1.4 Login your WeChat

Once you deploy the bot successfully, just follow the terminal or Logs in Docker container prompt carefully:

  1. Scan the QR Code with mobile WeChat
  2. Click "Log in" to allow desktop login (where our bot stays)
  3. Wait a few seconds and start chatting!

🤖 Enjoy your powerful chat bot! 🤖


1.2 Deploy on Cloud

Click the button below to fork this repo and deploy with Railway!

Deploy on Railway


1.2.1 Configure on Railway

Fill in the following blanks:

  1. Your forked repo name (can be any name you like)
  2. Choose make it private or not (also up to you)
  3. Environment variables (for how to get OpenAI API keys, please refer to 1.1.1 Get your OpenAI API keys for ChatGPT

Railway Config

Please note:

Make sure the environment variables are set in RailWay instead of writing directly in config.yaml. It's really NOT recommended to implicitly write out your OpenAI API Key in public repo. Anyone with your key can get access to the OpenAI API services, and it's possbile for you to lose money if you pay for that.


1.2.2 Deploy & Login on Railway

The deploy process is automatic. It may take a few minutes for the first time. As you see the Success, click the tab to see the details. (which is your secret WeChat console!)

Railway Deploy

Click Deply Logs and you will see everything is setting up, wait for a QR Code to pop up. Scan it as if you are login to your desktop WeChat, and click "Log in" on your mobile WeChat.

Railway Scan QR Code

Finally, everything is good to go! You will see the logs when people sending you messagem, and whenever the ChatGPT bot is auto-triggered to reply.

Railway Log

🤖 Enjoy your powerful chat bot! 🤖

2. Any Fancy Advanced Settings?

2.1 Config ChatGPT Models

You can change whatever ChatGPT Models you like to handle task at different capability & time-consumption trade-off. (e.g. model with better capability costs more time to respond)

Currently, we use the latest text-davinci-003 model, which is:

Most capable GPT-3 model. Can do any task the other models can do, often with higher quality, longer output and better instruction-following. Also supports inserting completions within text.

Also, for the same model, we can configure dozens of parameter. (e.g. answer randomness, maximum word limit...)

You can configure all of them in src/chatgpt.js:

const ChatGPTModelConfig = {
  // this model field is required
  model: "text-davinci-003",
  // add your ChatGPT model parameters below
  temperature: 0.9,
  max_tokens: 2000,
};

For more details, please refer to OpenAI Models Doc.


2.2 Config ChatGPT Features

You can change whatever ChatGPT features you like to handle different types of tasks. (e.g. complete text, edit text, generate image...)

Currently, we use createCompletion() to generate or manipulate text for daily usage, which:

Creates a completion for the provided prompt and parameters

You can configure in src/chatgpt.js:

const response = await this.OpenAI.createCompletion({
  ...ChatGPTModelConfig,
  prompt: inputMessage,
});

Of course you can ask how to edit text in current mode, but the outcome may fall short of expectations.

For more details, please refer to OpenAI API Doc.


2.3 Config Auto Reply in Error

When ChatGPT encounters some errors (e.g. over-crowded traffic, no authorization, ...), the chat bot will auto-reply the pre-configured message.

You can change it in src/chatgpt.js:

const chatgptErrorMessage = "🤖️:麦扣的机器人摆烂了,请稍后再试~";

2.4 Add Customized Task Handler

You can add your own task handlers to expand the ability of this chat bot!

Currently, add task handler in src/main.ts:

// e.g. if a message starts with "Hello", the bot sends "World!"
if (message.text().startsWith("Hello")) {
  await message.say("World!");
  return;
}

Of course, stuffing all handlers in main function is really a BAD habit in coding. As a result, we will fix this in future updates to do logic separation.

3. How to Contribute to this Project?

You can raise some issues, fork this repo, commit your code, submit pull request, and after code review, we can merge your patch. I'm really looking forward to develop more interesting features!