Chat API Proxy

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Chat API Proxy is a free interface service developed based on the OpenAI interface format, designed to seamlessly replace the OpenAI interface. This service utilizes the GPT4Free project, which is built on top of OpenAI GPT-4.

To-Do List ✔️
Features
Usage
Docker 🐳
- Pre-installation
- Run Docker
Integration with ChatGPT Next Web
Integration with FastGPT

To-Do List ✔️

Implement ChatCompletion API
Set token authentication through environment variables
Integrate GPT4Free
Docker support
Support customizing other free interfaces through configuration files
Support using free interfaces provided by others through shared plugins
Support building a stable service with a pool of free interfaces

Features

Seamless replacement for the OpenAI interface (ChatCompletion)
Supports the same request and response format as the OpenAI interface
Free to use, no additional charges required
Seamless integration with other popular projects, such as:
- ChatGPT Next Web
- FastGPT

Usage

1. Install Python

Make sure your environment has the following software installed:

Python 3.8+

2. Clone the Repository and Install Dependencies

git clone https://github.com/geeknonerd/chat-api-proxy.git
cd chat-api-proxy

git submodule init
git submodule update

ln -s $(pwd)/gpt4free/g4f $(pwd)

python3 -m pip install -r gpt4free/requirements.txt
python3 -m pip install -r requirements.txt

3. Run the Service

python3 -m uvicorn main:app --reload
# or
python3 main.py

You can now access your API service at http://localhost:8000/.

4. Call the API

The usage of our API interface is identical to that of OpenAI. For example, here is an example of sending a request using the Python OpenAI SDK:

import openai

openai.api_key = ""
openai.api_base = "http://localhost:8000/v1"

# create a chat completion
chat_completion = openai.ChatCompletion.create(
    model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])
# print the chat completion
print(chat_completion.choices[0].message.content)

Here is an example of sending a request using Python requests:

import requests

response = requests.post(
    "http://localhost:8000/v1/chat/completions",
    json={
        "model": "gpt-3.5-turbo",
        "messages": [{"role": "user", "content": "Hello world"}]
    })
print(response.json()['choices'][0]['message']['content'])

And here is an example of sending a request using curl:

curl http://localhost:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
  "model": "gpt-3.5-turbo",
  "messages": [
    {"role": "user", "content": "Hello world"}
  ]
}'

Docker 🐳

Pre-installation

Before getting started, make sure you have Docker installed on your machine.

Run Docker

Run the application using Docker:

docker run -d --name chatproxy -p 8000:8000 geeknonerd/chat-api-proxy

Access the application in your browser using the following URL:

http://127.0.0.1:8000

http://localhost:8000

When you are done using the application, stop the Docker container using the following command:

docker stop chatproxy

Integration with ChatGPT Next Web

Integration with FastGPT

When deploying with docker-compose, modify the environment variable as follows, replacing "xxx" with the public address of the deployed service. If HTTPS is not supported, change it to HTTP.

OPENAI_BASE_URL=https://api.openai.com/v1
=> 
OPENAI_BASE_URL=https://xxxx/v1

Contribution

We welcome contributions from everyone. If you encounter any issues or have any suggestions while using the service, feel free to let us know by submitting an issue or a pull request.

Disclaimer

This project is completely open-source and free, intended for research and educational purposes only. We are not responsible for any direct or indirect losses caused by using this service.

geeknonerd/chat-api-proxy