Update (2023-02-02)

Trying to use text-chat-davinci-002-20230126 with the OpenAI API now returns a 404 error. Someone has already found the new model name, but they are unwilling to share at this time. I will update this repository once I find the new model. If you have any leads, please open an issue or a pull request.

In the meantime, I've added support for models like text-davinci-003, which you can use as a drop-in replacement. Keep in mind that text-davinci-003 is not as good as text-chat-davinci-002 (which is trained via RHLF and fine-tuned to be a conversational AI), though results are still very good. Please note that using text-davinci-003 will cost you credits ($).

Discord user @pig#8932 has found a working text-chat-davinci-002 model, text-chat-davinci-002-20221122. I've updated the library to use this model.

ChatGPT API

A ChatGPT implementation using the official ChatGPT model via OpenAI's API.

This is an implementation of ChatGPT using the official ChatGPT raw model, text-chat-davinci-002. This model name text-chat-davinci-002-20230126 was briefly leaked while I was inspecting the network requests made by the official ChatGPT website, and I discovered that it works with the OpenAI API. Usage of this model currently does not cost any credits.

As far as I'm aware, I was the first one who discovered this, and usage of the model has since been implemented in libraries like acheong08/ChatGPT.

The previous version of this library that used transitive-bullshit/chatgpt-api is still available on the archive/old-version branch.

By itself, the model does not have any conversational support, so this library uses a cache to store conversations and pass them to the model as context. This allows you to have persistent conversations with ChatGPT in a nearly identical way to the official website.

Table of Contents

• Features
• Getting Started
  • Prerequisites
  • Usage
    • Module
    • API Server
    • CLI
• Caveats
• Contributing
• License

Features

• Uses the official ChatGPT raw model, text-chat-davinci-002-20221122.
• Includes an API server (with Docker support) you can run to use ChatGPT in non-Node.js applications.
• Includes a ChatGPTClient class that you can use in your own Node.js applications.
• Includes a CLI interface where you can chat with ChatGPT.
• Replicates chat threads from the official ChatGPT website (with conversation IDs and message IDs), with persistent conversations using Keyv.
  • Conversations are stored in memory by default, but you can optionally install a storage adapter to persist conversations to a database.
  • The keyv-file adapter is also included in this package, and can be used to store conversations in a JSON file if you're using the API server or CLI (see settings.example.js).
• Supports configurable prompt prefixes, and custom names for the user and ChatGPT.
  • In essence, this allows you to turn ChatGPT into a different character.
  • This is currently only configurable on a global level, but I plan to add support for per-conversation customization.

Getting Started

Prerequisites

• Node.js
• npm
• Docker (optional, for API server)
• OpenAI API key

Usage

Module

npm i @waylaidwanderer/chatgpt-api

import ChatGPTClient from '@waylaidwanderer/chatgpt-api';

const clientOptions = {
  // (Optional) Parameters as described in https://platform.openai.com/docs/api-reference/completions
  modelOptions: {
    // The model is set to text-chat-davinci-002-20221122 by default, but you can override
    // it and any other parameters here
    model: 'text-chat-davinci-002-20221122',
  },
  // (Optional) Set custom instructions instead of "You are ChatGPT...".
  // promptPrefix: 'You are Bob, a cowboy in Western times...',
  // (Optional) Set a custom name for the user
  // userLabel: 'User',
  // (Optional) Set a custom name for ChatGPT
  // chatGptLabel: 'ChatGPT',
  // (Optional) Set to true to enable `console.debug()` logging
  debug: false,
};

const cacheOptions = {
  // Options for the Keyv cache, see https://www.npmjs.com/package/keyv
  // This is used for storing conversations, and supports additional drivers (conversations are stored in memory by default)
  // For example, to use a JSON file (`npm i keyv-file`) as a database:
  // store: new KeyvFile({ filename: 'cache.json' }),
};

const chatGptClient = new ChatGPTClient('OPENAI_API_KEY', clientOptions, cacheOptions);

const response = await chatGptClient.sendMessage('Hello!');
console.log(response); // { response: 'Hi! How can I help you today?', conversationId: '...', messageId: '...' }

const response2 = await chatGptClient.sendMessage('Write a poem about cats.', { conversationId: response.conversationId, parentMessageId: response.messageId });
console.log(response2.response); // Cats are the best pets in the world.

const response3 = await chatGptClient.sendMessage('Now write it in French.', {
  conversationId: response2.conversationId,
  parentMessageId: response2.messageId,
  // If you want streamed responses, you can set the `onProgress` callback to receive the response as it's generated.
  // You will receive one token at a time, so you will need to concatenate them yourself.
  onProgress: (token) => console.log(token),
});
console.log(response3.response); // Les chats sont les meilleurs animaux de compagnie du monde.

API Server

Setup

You can install the package using

npm i -g @waylaidwanderer/chatgpt-api

then run it using chatgpt-api. This takes an optional --settings=<path_to_settings.js> parameter, or looks for settings.js in the current directory if not set, with the following contents:

module.exports = {
  // Your OpenAI API key
  openaiApiKey: process.env.OPENAI_API_KEY || '',
  chatGptClient: {
    // (Optional) Parameters as described in https://platform.openai.com/docs/api-reference/completions
    modelOptions: {
      // The model is set to text-chat-davinci-002-20221122 by default, but you can override
      // it and any other parameters here
      model: 'text-chat-davinci-002-20221122',
    },
    // (Optional) Set custom instructions instead of "You are ChatGPT...".
    // promptPrefix: 'You are Bob, a cowboy in Western times...',
    // (Optional) Set a custom name for the user
    // userLabel: 'User',
    // (Optional) Set a custom name for ChatGPT
    // chatGptLabel: 'ChatGPT',
    // (Optional) Set to true to enable `console.debug()` logging
    debug: false,
  },
  // Options for the Keyv cache, see https://www.npmjs.com/package/keyv
  // This is used for storing conversations, and supports additional drivers (conversations are stored in memory by default)
  cacheOptions: {},
  // Options for the API server
  apiOptions: {
    port: process.env.API_PORT || 3000,
    host: process.env.API_HOST || 'localhost',
    // (Optional) Set to true to enable `console.debug()` logging
    debug: false,
  },
  // If set, ChatGPTClient will use `keyv-file` to store conversations to this JSON file instead of in memory.
  // However, `cacheOptions.store` will override this if set
  storageFilePath: process.env.STORAGE_FILE_PATH || './cache.json',
};

Alternatively, you can install and run the package directly.

1. Clone this repository: git clone https://github.com/waylaidwanderer/node-chatgpt-api
2. Install dependencies with npm install (if not using Docker)
3. Rename settings.example.js to settings.js in the root directory and change the settings where required.
4. Start the server:
   • using npm start or npm run server (if not using Docker)
   • using docker-compose up (requires Docker)

Usage

To start a conversation with ChatGPT, send a POST request to the server's /conversation endpoint with a JSON body in the following format:

{
    "message": "Hello, how are you today?",
    "conversationId": "your-conversation-id (optional)",
    "parentMessageId": "your-parent-message-id (optional)"
}

The server will return a JSON object containing ChatGPT's response:

// HTTP/1.1 200 OK
{
    "response": "I'm doing well, thank you! How are you?",
    "conversationId": "your-conversation-id",
    "messageId": "response-message-id"
}

If the request is unsuccessful, the server will return a JSON object with an error message.

If the request object is missing a required property (e.g. message):

// HTTP/1.1 400 Bad Request
{
    "error": "The message parameter is required."
}

If there was an error sending the message to ChatGPT:

// HTTP/1.1 503 Service Unavailable
{
    "error": "There was an error communicating with ChatGPT."
}

You can set "stream": true in the request body to receive a stream of tokens as they are generated.

{
    "message": "Write a poem about cats.",
    "conversationId": "your-conversation-id (optional)",
    "parentMessageId": "your-parent-message-id (optional)",
    "stream": true
}

See demos/use-api-server-streaming.js for an example of how to receive the response as it's generated. You will receive one token at a time, so you will need to concatenate them yourself.

Successful output:

{ data: '', event: '', id: '', retry: 3000 }
{ data: 'Hello', event: '', id: '', retry: undefined }
{ data: '!', event: '', id: '', retry: undefined }
{ data: ' How', event: '', id: '', retry: undefined }
{ data: ' can', event: '', id: '', retry: undefined }
{ data: ' I', event: '', id: '', retry: undefined }
{ data: ' help', event: '', id: '', retry: undefined }
{ data: ' you', event: '', id: '', retry: undefined }
{ data: ' today', event: '', id: '', retry: undefined }
{ data: '?', event: '', id: '', retry: undefined }
{ data: '[DONE]', event: '', id: '', retry: undefined }
// Hello! How can I help you today?

Error output:

const message = {
  data: '{"code":503,"error":"There was an error communicating with ChatGPT."}',
  event: 'error',
  id: '',
  retry: undefined
};

if (message.event === 'error') {
  console.error(JSON.parse(message.data).error); // There was an error communicating with ChatGPT.
}

CLI

Setup

Follow the same setup instructions for the API server, creating settings.js.

Usage

If installed globally:

chatgpt-cli

If installed locally:

npm run cli

ChatGPT's responses are automatically copied to your clipboard, so you can paste them into other applications.

Caveats

Since text-chat-davinci-002-20221122 is ChatGPT's raw model, I had to do my best to replicate the way the official ChatGPT website uses it. After extensive testing and comparing responses, I believe that the model used by ChatGPT has some additional fine-tuning. This means my implementation or the raw model may not behave exactly the same in some ways:

• Conversations are not tied to any user IDs, so if that's important to you, you should implement your own user ID system.

• ChatGPT's model parameters (temperature, frequency penalty, etc.) are unknown, so I set some defaults that I thought would be reasonable.

• Conversations are limited to roughly the last 3000 tokens, so earlier messages may be forgotten during longer conversations.

  • This works in a similar way to ChatGPT, except I'm pretty sure they have some additional way of retrieving context from earlier messages when needed (which can probably be achieved with embeddings, but I consider that out-of-scope for now).

• It is well known that, as part of the fine-tuning, ChatGPT had the following preamble:

  "You are ChatGPT, a large language model trained by OpenAI. You answer as concisely as possible for each response (e.g. don’t be verbose). It is very important that you answer as concisely as possible, so please remember this. If you are generating a list, do not have too many items. Keep the number of items short. Knowledge cutoff: 2021-09 Current date: 2023-01-31"

  As OpenAI updates ChatGPT, this preamble may also change. The default prompt prefix in my implementation attempts to replicate a similar behavior to the current ChatGPT model.

Contributing

If you'd like to contribute to this project, please create a pull request with a detailed description of your changes.

License

This project is licensed under the MIT License.