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G4F - Interference API Usage Guide

Table of Contents

Introduction

The G4F Interference API is a powerful tool that allows you to serve other OpenAI integrations using G4F (Gpt4free). It acts as a proxy, translating requests intended for the OpenAI API into requests compatible with G4F providers. This guide will walk you through the process of setting up, running, and using the Interference API effectively.

Running the Interference API

You can run the Interference API in two ways: using the PyPI package or from the repository.

From PyPI Package

To run the Interference API directly from the G4F PyPI package, use the following Python code:

from g4f.api import run_api

run_api()

From Repository

If you prefer to run the Interference API from the cloned repository, you have two options:

  1. Using the command line:
g4f api
  1. Using Python:
python -m g4f.api.run

Once running, the API will be accessible at: http://localhost:1337/v1

(Advanced) Bind to custom port:

python -m g4f.cli api --bind "0.0.0.0:2400"

Using the Interference API

Basic Usage

You can interact with the Interference API using curl commands for both text and image generation:

For text generation:

curl -X POST "http://localhost:1337/v1/chat/completions" \
     -H "Content-Type: application/json" \
     -d '{
           "messages": [
             {
               "role": "user",
               "content": "Hello"
             }
           ],
           "model": "gpt-4o-mini"
         }'

For image generation:

  1. url:
curl -X POST "http://localhost:1337/v1/images/generate" \
     -H "Content-Type: application/json" \
     -d '{
           "prompt": "a white siamese cat",
           "model": "flux",
           "response_format": "url"
         }'
  1. b64_json
curl -X POST "http://localhost:1337/v1/images/generate" \
     -H "Content-Type: application/json" \
     -d '{
           "prompt": "a white siamese cat",
           "model": "flux",
           "response_format": "b64_json"
         }'

With OpenAI Library

You can use the Interference API with the OpenAI Python library by changing the base_url:

from openai import OpenAI

client = OpenAI(
    api_key="",
    base_url="http://localhost:1337/v1"
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Write a poem about a tree"}],
    stream=True,
)

if isinstance(response, dict):
    # Not streaming
    print(response.choices[0].message.content)
else:
    # Streaming
    for token in response:
        content = token.choices[0].delta.content
        if content is not None:
            print(content, end="", flush=True)

With Requests Library

You can also send requests directly to the Interference API using the requests library:

import requests

url = "http://localhost:1337/v1/chat/completions"

body = {
    "model": "gpt-4o-mini",
    "stream": False,
    "messages": [
        {"role": "assistant", "content": "What can you do?"}
    ]
}

json_response = requests.post(url, json=body).json().get('choices', [])

for choice in json_response:
    print(choice.get('message', {}).get('content', ''))

Key Points

  • The Interference API translates OpenAI API requests into G4F provider requests.
  • It can be run from either the PyPI package or the cloned repository.
  • The API supports usage with the OpenAI Python library by changing the base_url.
  • Direct requests can be sent to the API endpoints using libraries like requests.
  • Both text and image generation are supported.

Conclusion

The G4F Interference API provides a seamless way to integrate G4F with existing OpenAI-based applications and tools. By following this guide, you should now be able to set up, run, and use the Interference API effectively. Whether you're using it for text generation, image creation, or as a drop-in replacement for OpenAI in your projects, the Interference API offers flexibility and power for your AI-driven applications.

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