GPT4Free Python Library: A Beginner’s Guide

gpt4free is an open-source Python library that lets you access a variety of powerful language models through multiple providers — all without needing official API keys in many cases. Designed as a proof-of-concept, this library demonstrates how to build an API package that handles multi-provider requests, timeouts, load balancing, and flow control.

With support for models like GPT-3.5, GPT-4, and others, gpt4free enables developers to explore AI-powered text generation from different sources using a unified interface.

This tutorial will walk you through how to install, configure, and use gpt4free for various AI tasks.

⚠️ Legal Notice

Before using gpt4free, please read the legal disclaimer:

• This project is provided for educational and proof-of-concept purposes only.
• The original author does not endorse or take responsibility for how this repository is used.
• Bypassing official APIs may violate the terms of service of the model providers.
• You must ensure you have proper authorization before using gpt4free in any production environment.

💡 Pro Tip: Use Apidog for Smarter API Testing

Looking for a powerful alternative to Postman? Apidog is an all-in-one API development platform that supports API design, debugging, automation, and documentation. When working with gpt4free, Apidog helps you:

• Send requests to interference API endpoints
• Experiment with different parameters and settings
• Visualize and inspect API responses
• Save and reuse API request collections

Apidog even supports MCP server integration, making it ideal for testing local APIs in AI agent mode.

🔧 How to Install gpt4free

📋 Prerequisites

• Python 3.10 or higher
• Google Chrome (required for some providers using browser automation)

📦 Installation Methods

Method 1: Install via PyPI

For full-featured installation:

pip install gpt4free

For partial installs (customized providers):

pip install gpt4free[provider_name]

Method 2: Clone from GitHub

git clone https://github.com/xtekky/gpt4free.git
cd gpt4free
pip install -r requirements.txt

Method 3: Using Docker

To run in a Docker container:

docker build -t gpt4free .
docker run -p 8080:8080 gpt4free

For slim version (x64 and arm64 compatible):

docker build -t gpt4free-slim -f Dockerfile.slim .

🧠 Using gpt4free in Python

✍️ Basic Text Generation

Simple Example

from g4f import ChatCompletion

response = ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello, AI!"}]
)
print(response)

Streaming Response

for chunk in ChatCompletion.create(..., stream=True):
    print(chunk, end="")

Using a Specific Provider

ChatCompletion.create(
    provider=g4f.Provider.Bing,
    model="gpt-4",
    messages=[...]
)

Using the Client API

ChatCompletion.create(
    provider=g4f.Provider.Bing,
    model="gpt-4",
    messages=[...]
)

⚙️ Advanced Usage

✅ Client API

A modern and more flexible method:

client = g4f.Client(provider=g4f.Provider.Bing)
response = client.chat.completions.create(...)

🖼️ Image Generation

image = g4f.ImageCompletion.create(prompt="A sunset on Mars")

🔐 Provider Authentication

Some providers require cookies or tokens:

g4f.Provider.Bing.cookies = {...}

🧭 Browser Automation

Used for providers needing browser interaction:

python start_browser.py

⚡ Async Support

Boost performance with asynchronous calls:

await ChatCompletion.create_async(...)

🌐 Proxy & Timeout

Set global proxy via environment variable:

export http_proxy=http://localhost:7890

🌍 Web Interface

gpt4free includes a simple web UI:

python3 -m g4f.ui

Access it at: http://localhost:8080/chat

🔌 Using the Interference API

Run gpt4free’s OpenAI-compatible API:

python3 -m g4f.api

Then connect using the OpenAI client:

openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    api_base="http://localhost:1337",
    ...
)

📚 Supported Models & Providers

GPT-4 Providers

• g4f.Provider.Bing
• g4f.Provider.GeekGpt
• g4f.Provider.GptChatly
• g4f.Provider.Liaobots
• g4f.Provider.Raycast

GPT-3.5 Providers

• g4f.Provider.AItianhu
• g4f.Provider.ChatBase
• g4f.Provider.ChatgptAi
• g4f.Provider.ChatForAi
• And more…

Other Model Support

• Bard (Google PaLM)
• DeepInfra
• HuggingChat
• LLaMA 2
• OpenAssistant

🏁 Conclusion

gpt4free offers a flexible way to experiment with multiple language models using a single interface — often without official API keys. It’s ideal for:

• Learning about AI capabilities
• Rapid prototyping and testing
• Comparing provider performance

However, always use it responsibly. For production use, it’s strongly recommended to stick with official APIs and proper credentials.

Stay updated via the GitHub repository for new features, providers, and best practices as this project evolves alongside the rapidly growing AI ecosystem.