GPT4Free (g4f)
Created by @xtekky,
maintained by @hlohaus
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Live demo & docs: https://g4f.dev | Documentation: https://g4f.dev/docs
GPT4Free (g4f) is a community-driven project that aggregates multiple accessible providers and interfaces to make working with modern LLMs and media-generation models easier and more flexible. GPT4Free aims to offer multi-provider support, local GUI, OpenAI-compatible REST APIs, and convenient Python and JavaScript clients — all under a community-first license.
This README is a consolidated, improved, and complete guide to installing, running, and contributing to GPT4Free.
Table of contents
What’s included
- Python client library and async client.
- Optional local web GUI.
- FastAPI-based OpenAI-compatible API (Interference API).
- Official browser JS client (g4f.dev distribution).
- Docker images (full and slim).
- Multi-provider adapters (LLMs, media providers, local inference backends).
- Tooling for image/audio/video generation and media persistence.
Quick links
Requirements & compatibility
- Python 3.10+ recommended.
- Google Chrome/Chromium for providers using browser automation.
- Docker for containerized deployment.
- Works on x86_64 and arm64 (slim image supports both).
- Some provider adapters may require platform-specific tooling (Chrome/Chromium, etc.). Check provider docs for details.
Installation
Docker (recommended)
- Install Docker: https://docs.docker.com/get-docker/
- Create persistent directories:
- Pull image:
docker pull hlohaus789/g4f
- Run container:
docker run -p 8080:8080 -p 7900:7900 \
--shm-size="2g" \
-v ${PWD}/har_and_cookies:/app/har_and_cookies \
-v ${PWD}/generated_media:/app/generated_media \
hlohaus789/g4f:latest
Notes:
- Port 8080 serves GUI/API; 7900 can expose a VNC-like desktop for provider logins (optional).
- Increase --shm-size for heavier browser automation tasks.
Slim Docker image (x64 & arm64)
mkdir -p ${PWD}/har_and_cookies ${PWD}/generated_media
chown -R 1000:1000 ${PWD}/har_and_cookies ${PWD}/generated_media
docker run \
-p 1337:8080 -p 8080:8080 \
-v ${PWD}/har_and_cookies:/app/har_and_cookies \
-v ${PWD}/generated_media:/app/generated_media \
hlohaus789/g4f:latest-slim
Notes:
- The slim image can update the g4f package on startup and installs additional dependencies as needed.
- In this example, the Interference API is mapped to 1337.
Windows Guide (.exe)
👉 Check out the Windows launcher for GPT4Free:
🔗 https://github.com/gpt4free/g4f.exe 🚀
- Download the release artifact
g4f.exe.zip from:
https://github.com/xtekky/gpt4free/releases/latest
- Unzip and run
g4f.exe.
- Open GUI at: http://localhost:8080/chat/
- If Windows Firewall blocks access, allow the application.
Python Installation (pip / from source / partial installs)
Prerequisites:
Install from PyPI (recommended):
pip install -U g4f[all]
Partial installs
- To install only specific functionality, use optional extras groups. See docs/requirements.md in the project docs.
Install from source:
git clone https://github.com/xtekky/gpt4free.git
cd gpt4free
pip install -r requirements.txt
pip install -e .
Notes:
- Some features require Chrome/Chromium or other tools; follow provider-specific docs.
Running the app
GUI (web client)
from g4f.gui import run_gui
run_gui()
python -m g4f.cli gui --port 8080 --debug
FastAPI / Interference API
python -m g4f --port 8080 --debug
- If using slim docker mapping, Interference API may be available at
http://localhost:1337/v1
- Swagger UI:
http://localhost:1337/docs
CLI
python -m g4f.cli gui --port 8080 --debug
MCP Server
GPT4Free now includes a Model Context Protocol (MCP) server that allows AI assistants like Claude to access web search, scraping, and image generation capabilities.
Starting the MCP server (stdio mode):
# Using g4f command
g4f mcp
# Or using Python module
python -m g4f.mcp
Starting the MCP server (HTTP mode):
# Start HTTP server on port 8765
g4f mcp --http --port 8765
# Custom host and port
g4f mcp --http --host 127.0.0.1 --port 3000
HTTP mode provides:
POST http://localhost:8765/mcp - JSON-RPC endpointGET http://localhost:8765/health - Health check
Configuring with Claude Desktop:
Add to your claude_desktop_config.json:
{
"mcpServers": {
"gpt4free": {
"command": "python",
"args": ["-m", "g4f.mcp"]
}
}
}
Available MCP Tools:
web_search - Search the web using DuckDuckGoweb_scrape - Extract text content from web pages image_generation - Generate images from text prompts
For detailed MCP documentation, see g4f/mcp/README.md
Optional provider login (desktop within container)
Using the Python client
Install:
pip install -U g4f[all]
Synchronous text example:
from g4f.client import Client
client = Client()
response = client.chat.completions.create(
model="auto",
messages=[{"role": "user", "content": "Hello, how are you?"}],
web_search=False
)
print(response.choices[0].message.content)
Expected:
Hello! How can I assist you today?
Image generation example:
from g4f.client import Client
client = Client()
response = client.images.generate(
model="flux",
prompt="a white siamese cat",
response_format="url"
)
print(f"Generated image URL: {response.data[0].url}")
Async client example:
from g4f.client import AsyncClient
import asyncio
async def main():
client = AsyncClient()
response = await client.chat.completions.create(
model="auto",
messages=[{"role": "user", "content": "Explain quantum computing briefly"}],
)
print(response.choices[0].message.content)
asyncio.run(main())
Notes:
Using GPT4Free.js (browser JS client)
Use the official JS client in the browser—no backend required.
Example:
<script type="module">
import Client from 'https://g4f.dev/dist/js/client.js';
const client = new Client();
const result = await client.chat.completions.create({
model: 'auto', // Or "glm-5.3", "kimi-k3", etc.
messages: [{ role: 'user', content: 'Explain quantum computing' }]
});
console.log(result.choices[0].message.content);
</script>
Notes:
- The JS client is distributed via the g4f.dev CDN for easy usage. Review CORS considerations and usage limits.
Providers & models (overview)
- GPT4Free integrates many providers including (but not limited to) OpenAI-compatible endpoints, PerplexityLabs, Gemini, MetaAI, Pollinations (media), and local inference backends.
- Model availability and behavior depend on provider capabilities. See the providers doc for current, supported provider/model lists: https://g4f.dev/docs/providers-and-models
Provider requirements may include:
- API keys or tokens (for authenticated providers)
- Browser cookies / HAR files for providers scraped via browser automation
- Chrome/Chromium or headless browser tooling
- Local model binaries and runtime (for local inference)
- GPT4Free supports local inference backends. See docs/local.md for supported runtimes and hardware guidance.
- Media generation (image, audio, video) is supported through providers (e.g., Pollinations). See docs/media.md for formats, options, and sample usage.
Configuration & customization
- Configure via environment variables, CLI flags, or config files. See docs/config.md.
- To reduce install size, use partial requirement groups. See docs/requirements.md.
- Provider selection: learn how to set defaults and override per-request at docs/selecting_a_provider.md.
- Persistence: HAR files, cookies, and generated media persist in mapped directories (e.g., har_and_cookies, generated_media).
Running on smartphone
- The web GUI is responsive and can be accessed from a phone by visiting your host IP:8080 or via a tunnel. See docs/guides/phone.md.
Interference API (OpenAI‑compatible)
- The Interference API enables OpenAI-like workflows routed through GPT4Free provider selection.
- Docs: docs/interference-api.md
- Default endpoint (example slim docker):
http://localhost:1337/v1
- Swagger UI:
http://localhost:1337/docs
Examples & common patterns
- Streaming completions, stopping criteria, system messages, and tool-calling patterns are documented in:
- Integrations (LangChain, PydanticAI): docs/pydantic_ai.md
- Legacy examples: docs/legacy.md
Contributing
Contributions are welcome — new providers, features, docs, and fixes are appreciated.
How to contribute:
- Fork the repository.
- Create a branch for your change.
- Run tests and linters.
- Open a Pull Request with a clear description and tests/examples if applicable.
Repository: https://github.com/xtekky/gpt4free
How to create a new provider
- Read the guide: docs/guides/create_provider.md
- Typical steps:
- Implement a provider adapter in
g4f/Provider/
- Add configuration and dependency notes
- Include tests and usage examples
- Respect third‑party code licenses and attribute appropriately
How AI can help you write code
Security, privacy & takedown policy
- Do not store or share sensitive credentials. Use per-provider recommended security practices.
- If your site appears in the project’s links and you want it removed, send proof of ownership to https://g4f.dev/community and it will be removed promptly.
- For production, secure the server with HTTPS, authentication, and firewall rules. Limit access to provider credentials and cookie/HAR storage.
Credits, contributors & attribution
Many more contributors are acknowledged in the repository.
Powered-by highlights
Changelog & releases
Manifesto / Project principles
GPT4Free is guided by community principles:
- Open access to AI tooling and models.
- Collaboration across providers and projects.
- Opposition to monopolistic, closed systems that restrict creativity.
- Community-centered development and broad access to AI technologies.
- Promote innovation, creativity, and accessibility.
https://g4f.dev/manifesto
License
This program is licensed under the GNU General Public License v3.0 (GPLv3). See the full license: https://www.gnu.org/licenses/gpl-3.0.txt
Summary:
- You may redistribute and/or modify under the terms of GPLv3.
- The program is provided WITHOUT ANY WARRANTY.
Copyright notice
xtekky/gpt4free: Copyright (C) 2025 xtekky
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
Appendix: Quick commands & examples
Install (pip):
pip install -U g4f[all]
Run GUI (Python):
python -m g4f.cli gui --port 8080 --debug
# or
python -c "from g4f.gui import run_gui; run_gui()"
Docker (full):
docker pull hlohaus789/g4f
docker run -p 8080:8080 -p 7900:7900 \
--shm-size="2g" \
-v ${PWD}/har_and_cookies:/app/har_and_cookies \
-v ${PWD}/generated_media:/app/generated_media \
hlohaus789/g4f:latest
Docker (slim):
docker run -p 1337:8080 -p 8080:8080 \
-v ${PWD}/har_and_cookies:/app/har_and_cookies \
-v ${PWD}/generated_media:/app/generated_media \
hlohaus789/g4f:latest-slim
Python usage patterns:
client.chat.completions.create(...)client.images.generate(...)- Async variants via
AsyncClient
Docs & deeper reading
Thank you for using and contributing to GPT4Free — together we make powerful AI tooling accessible, flexible, and community-driven.
GPT4Free (g4f) is a community-driven project that aggregates many free and reverse-engineered access points to commercial LLMs (GPT-4, Claude, Gemini, DeepSeek, etc.) and media-generation models, exposing them through one unified Python/JS client, web GUI, and OpenAI-compatible API.