Chatgpt API By Browser Script

中文文档

This project runs on users' browsers through the Tampermonkey script and converts the web version of ChatGPT operations into an API interface. You can use this API to do some interesting things, such as playing Auto-GPT.

Features

• API no cost.
• If you have a chatgpt plus account, you can use gpt-4 api.
• Having unlimited context.
• Not easy to be banned and easier to handle errors.

Usage

Step 1 Installation and Configuration

1. Make sure your system has installed Node.js and npm.
2. Clone this repository and run npm install in the project directory to install dependencies.
3. Run npm run start to start the Node.js server.
4. Alternatively, you can use Docker docker-compose up to start the Node.js server.

Step 2 Use Tampermonkey

1. Install Tampermonkey browser extension.
2. Open Tampermonkey management panel and create a new script.
3. Copy the contents of tampermonkey-script.js file into the newly created script and save it.

Step 3 Open and Log in to ChatGPT

https://chat.openai.com/

If you see this in the upper right corner of the webpage, you have succeeded !

Step 4 Use API

You now have an API address: http://localhost:8766/v1/chat/completions

API Params

Parameter	Description	Default	Required
messages	Refer to OpenAI API documentation		Yes
model	Refer to OpenAI API documentation		No
stream	Refer to OpenAI API documentation	false	No
newChat	Whether to start a new conversation	true	No

Example of Request Parameters

{
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "Who are you?"
    }
  ],
  "model": "gpt-4"
}

Play with Auto-GPT

Modify the llm_utils.py file in Auto-GPT.

import requests
# response = openai.ChatCompletion.create(
#     model=model,
#     messages=messages,
#     temperature=temperature,
#     max_tokens=max_tokens,
# )
response = requests.post("http://localhost:8766/v1/chat/completions", json={"messages": messages, "model": model, "newChat": False, "temperature": temperature, "max_tokens": max_tokens}).json()


# return response.choices[0].message["content"]
return response["choices"][0]["message"]["content"]