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The official gpt4free repository | various collection of powerful language models

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Quick Overview

gpt4free is an open-source project that provides free access to various AI models, including GPT-4, through reverse-engineered APIs. It aims to make advanced language models accessible to developers and researchers without the need for paid subscriptions or API keys.

Pros

  • Free access to powerful AI models
  • Multiple providers and models available
  • Active community and frequent updates
  • Useful for testing and prototyping AI applications

Cons

  • Potential legal and ethical concerns regarding API usage
  • Reliability issues due to dependence on third-party services
  • May not be suitable for production environments
  • Limited support and documentation compared to official APIs

Code Examples

  1. Using the Forefront provider:
import g4f

response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    provider=g4f.Provider.Forefront,
    messages=[{"role": "user", "content": "Hello, how are you?"}],
    stream=True,
)

for message in response:
    print(message, flush=True, end='')
  1. Using the You provider:
import g4f

response = g4f.ChatCompletion.create(
    model=g4f.models.gpt_35_turbo,
    messages=[{"role": "user", "content": "Write a poem about AI"}],
    provider=g4f.Provider.You,
)

print(response)
  1. Using the Bing provider:
import g4f

response = g4f.ChatCompletion.create(
    model="gpt-4",
    provider=g4f.Provider.Bing,
    messages=[{"role": "user", "content": "Explain quantum computing"}],
    cookies=g4f.get_cookies(".bing.com"),
)

print(response)

Getting Started

To get started with gpt4free, follow these steps:

  1. Install the library:
pip install -U g4f
  1. Import the library and use a provider:
import g4f

response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    provider=g4f.Provider.OpenaiChat,
    messages=[{"role": "user", "content": "Hello, world!"}],
)

print(response)

Note: Make sure to check the project's documentation for the latest updates and provider-specific instructions.

Competitor Comparisons

acheong08 logo

ChatGPT

28,009

Reverse engineered ChatGPT API

Pros of ChatGPT

  • More established project with a larger community and longer development history
  • Offers a wider range of features, including support for multiple ChatGPT models
  • Better documentation and more comprehensive setup instructions

Cons of ChatGPT

  • Requires authentication and API keys, which may be less accessible for some users
  • More complex setup process compared to gpt4free
  • May have higher usage costs due to reliance on official OpenAI APIs

Code Comparison

ChatGPT:

from revChatGPT.V3 import Chatbot

chatbot = Chatbot(api_key="your_api_key")
response = chatbot.ask("Hello, how are you?")
print(response)

gpt4free:

import g4f

response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)
print(response)

Both repositories provide access to ChatGPT-like functionality, but gpt4free aims to offer free access without authentication, while ChatGPT focuses on providing a more robust and official integration with OpenAI's services. The choice between them depends on the user's needs, budget, and ethical considerations regarding API usage.

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agentic

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AI agent stdlib that works with any LLM and TypeScript AI SDK.

Pros of agentic

  • Focuses on building autonomous AI agents, offering a more specialized and advanced approach
  • Provides a framework for creating complex, goal-oriented AI systems
  • Emphasizes ethical considerations and responsible AI development

Cons of agentic

  • Less accessible for users seeking simple, ready-to-use GPT-like functionality
  • Requires more technical knowledge and setup compared to gpt4free
  • Smaller community and fewer contributors, potentially leading to slower development

Code Comparison

gpt4free:

from g4f import ChatCompletion

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

agentic:

from agentic import Agent, Task

agent = Agent()
task = Task("Greet the user and ask how they are")
result = agent.run(task)
print(result)

The code comparison shows that gpt4free provides a more straightforward interface for generating responses, while agentic focuses on creating autonomous agents to perform tasks. gpt4free is better suited for quick, chat-like interactions, whereas agentic is designed for more complex, goal-oriented AI applications.

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AutoGPT

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AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

Pros of AutoGPT

  • Autonomous task completion with minimal human intervention
  • Versatile application across various domains (e.g., coding, research, analysis)
  • Active development and community support

Cons of AutoGPT

  • Requires API key and potentially higher costs for extended use
  • More complex setup and configuration process
  • May produce inconsistent or unexpected results due to its autonomous nature

Code Comparison

AutoGPT:

def start_interaction_loop(self):
    # Interaction loop
    while True:
        # Get user input
        user_input = input("Human: ")
        if user_input.lower() == "exit":
            break

gpt4free:

def create_chat(self, model="gpt-3.5-turbo", messages=None, **kwargs):
    if messages is None:
        messages = []
    return ChatCompletion.create(
        model=model, messages=messages, **kwargs
    )

AutoGPT focuses on creating an autonomous agent that can perform tasks with minimal human intervention, while gpt4free aims to provide free access to various language models. AutoGPT offers more advanced features but requires more setup, while gpt4free is simpler to use but may have limitations in terms of available models and functionality.

microsoft logo

DeepSpeed

34,658

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Pros of DeepSpeed

  • Highly optimized for large-scale distributed training of deep learning models
  • Supports a wide range of AI models and frameworks (PyTorch, TensorFlow, etc.)
  • Backed by Microsoft, ensuring ongoing development and support

Cons of DeepSpeed

  • Steeper learning curve due to its complexity and advanced features
  • Primarily focused on model training, not inference or API access
  • Requires more computational resources for optimal performance

Code Comparison

DeepSpeed:

import deepspeed
model_engine, optimizer, _, _ = deepspeed.initialize(args=args,
                                                     model=model,
                                                     model_parameters=params)
for step, batch in enumerate(data_loader):
    loss = model_engine(batch)
    model_engine.backward(loss)
    model_engine.step()

gpt4free:

import g4f
response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)
print(response)

Summary

DeepSpeed is a powerful tool for optimizing large-scale AI model training, while gpt4free focuses on providing free access to GPT-like models. DeepSpeed offers more advanced features and better performance for training, but requires more expertise and resources. gpt4free is simpler to use and provides easy access to AI models, but may have limitations in terms of model quality and legal considerations.

openai logo

openai-python

22,464

The official Python library for the OpenAI API

Pros of openai-python

  • Official library maintained by OpenAI, ensuring reliability and up-to-date features
  • Comprehensive documentation and support from OpenAI
  • Seamless integration with OpenAI's API and services

Cons of openai-python

  • Requires an API key and associated costs for usage
  • Limited to OpenAI's models and services

Code Comparison

openai-python:

import openai

openai.api_key = "your-api-key"
response = openai.Completion.create(engine="text-davinci-002", prompt="Hello, world!")
print(response.choices[0].text)

gpt4free:

import g4f

response = g4f.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello, world!"}])
print(response)

Key Differences

  • openai-python is the official library, while gpt4free is a third-party alternative
  • gpt4free aims to provide free access to AI models, while openai-python requires an API key and associated costs
  • openai-python offers more extensive features and model options, while gpt4free focuses on providing free alternatives
  • gpt4free may have potential legal and ethical concerns due to its nature of bypassing official APIs

Use Cases

  • openai-python: Ideal for professional and commercial applications requiring reliable and official API access
  • gpt4free: Suitable for personal projects, experimentation, or scenarios where API costs are a concern, but with potential limitations and risks
huggingface logo

transformers

131,798

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Pros of transformers

  • Comprehensive library with support for numerous pre-trained models
  • Extensive documentation and community support
  • Seamless integration with PyTorch and TensorFlow

Cons of transformers

  • Steeper learning curve for beginners
  • Larger library size and potentially higher resource requirements

Code Comparison

transformers:

from transformers import pipeline

classifier = pipeline("sentiment-analysis")
result = classifier("I love this library!")[0]
print(f"Label: {result['label']}, Score: {result['score']:.4f}")

gpt4free:

import g4f

response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello, how are you?"}]
)
print(response)

Summary

transformers is a robust, well-documented library for working with various pre-trained models, offering extensive functionality and integration with popular deep learning frameworks. It's ideal for advanced users and large-scale projects.

gpt4free, on the other hand, provides a simpler interface for accessing GPT models, making it more accessible for quick implementations and experimentation. However, it may lack the comprehensive features and community support of transformers.

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README

248433934-7886223b-c1d1-4260-82aa-da5741f303bb

xtekky%2Fgpt4free | Trendshift

Written by @xtekky & maintained by @hlohaus

By using this repository or any code related to it, you agree to the legal notice. The author is not responsible for the usage of this repository nor endorses it, nor is the author responsible for any copies, forks, re-uploads made by other users, or anything else related to GPT4Free. This is the author's only account and repository. To prevent impersonation or irresponsible actions, please comply with the GNU GPL license this Repository uses.

[!Warning] > "gpt4free" serves as a PoC (proof of concept), demonstrating the development of an API package with multi-provider requests, with features like timeouts, load balance and flow control.

[!Note] > Lastet version: PyPI version Docker version
Stats: Downloads Downloads

pip install -U g4f

docker pull hlohaus789/g4f

🆕 What's New

🔻 Site Takedown

Is your site on this repository and you want to take it down? Send an email to takedown@g4f.ai with proof it is yours and it will be removed as fast as possible. To prevent reproduction please secure your API. 😉

🚀 Feedback and Todo

You can always leave some feedback here: https://forms.gle/FeWV9RLEedfdkmFN6

As per the survey, here is a list of improvements to come

  • Update the repository to include the new openai library syntax (ex: Openai() class) | completed, use g4f.client.Client
  • Golang implementation
  • 🚧 Improve Documentation (in /docs & Guides, Howtos, & Do video tutorials)
  • Improve the provider status list & updates
  • Tutorials on how to reverse sites to write your own wrapper (PoC only ofc)
  • Improve the Bing wrapper. (Wait and Retry or reuse conversation)
  • 🚧 Write a standard provider performance test to improve the stability
  • Potential support and development of local models
  • 🚧 Improve compatibility and error handling

📚 Table of Contents

🛠️ Getting Started

Docker Container Guide

Getting Started Quickly:

  1. Install Docker: Begin by downloading and installing Docker.

  2. Set Up the Container: Use the following commands to pull the latest image and start the container:

docker pull hlohaus789/g4f
docker run \
  -p 8080:8080 -p 1337:1337 -p 7900:7900 \
  --shm-size="2g" \
  -v ${PWD}/har_and_cookies:/app/har_and_cookies \
  -v ${PWD}/generated_images:/app/generated_images \
  hlohaus789/g4f:latest

  1. Access the Client:

  2. (Optional) Provider Login: If required, you can access the container's desktop here: http://localhost:7900/?autoconnect=1&resize=scale&password=secret for provider login purposes.

Installation Guide for Windows (.exe)

To ensure the seamless operation of our application, please follow the instructions below. These steps are designed to guide you through the installation process on Windows operating systems.

Installation Steps

  1. Download the Application: Visit our releases page and download the most recent version of the application, named g4f.exe.zip.
  2. File Placement: After downloading, locate the .zip file in your Downloads folder. Unpack it to a directory of your choice on your system, then execute the g4f.exe file to run the app.
  3. Open GUI: The app starts a web server with the GUI. Open your favorite browser and navigate to http://localhost:8080/chat/ to access the application interface.
  4. Firewall Configuration (Hotfix): Upon installation, it may be necessary to adjust your Windows Firewall settings to allow the application to operate correctly. To do this, access your Windows Firewall settings and allow the application.

By following these steps, you should be able to successfully install and run the application on your Windows system. If you encounter any issues during the installation process, please refer to our Issue Tracker or try to get contact over Discord for assistance.

Run the Webview UI on other Platfroms:

Use your smartphone:

Run the Web UI on Your Smartphone:

Use python

Prerequisites:
  1. Download and install Python (Version 3.10+ is recommended).
  2. Install Google Chrome for providers with webdriver
Install using PyPI package:
pip install -U g4f[all]

How do I install only parts or do disable parts? Use partial requirements: /docs/requirements

Install from source:

How do I load the project using git and installing the project requirements? Read this tutorial and follow it step by step: /docs/git

Install using Docker:

How do I build and run composer image from source? Use docker-compose: /docs/docker

💡 Usage

Text Generation

from g4f.client import Client

client = Client()
response = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello"}],
    ...
)
print(response.choices[0].message.content)

Hello! How can I assist you today?

Image Generation

from g4f.client import Client

client = Client()
response = client.images.generate(
  model="gemini",
  prompt="a white siamese cat",
  ...
)
image_url = response.data[0].url

Image with cat

Full Documentation for Python API

Web UI

To start the web interface, type the following codes in python:

from g4f.gui import run_gui
run_gui()

or execute the following command:

python -m g4f.cli gui -port 8080 -debug

Interference API

You can use the Interference API to serve other OpenAI integrations with G4F.

See docs: /docs/interference

Access with: http://localhost:1337/v1

Configuration

Cookies

Cookies are essential for using Meta AI and Microsoft Designer to create images. Additionally, cookies are required for the Google Gemini and WhiteRabbitNeo Provider. From Bing, ensure you have the "_U" cookie, and from Google, all cookies starting with "__Secure-1PSID" are needed.

You can pass these cookies directly to the create function or set them using the set_cookies method before running G4F:

from g4f.cookies import set_cookies

set_cookies(".bing.com", {
  "_U": "cookie value"
})

set_cookies(".google.com", {
  "__Secure-1PSID": "cookie value"
})

Using .har and Cookie Files

You can place .har and cookie files in the default ./har_and_cookies directory. To export a cookie file, use the EditThisCookie Extension available on the Chrome Web Store.

Creating .har Files to Capture Cookies

To capture cookies, you can also create .har files. For more details, refer to the next section.

Changing the Cookies Directory and Loading Cookie Files in Python

You can change the cookies directory and load cookie files in your Python environment. To set the cookies directory relative to your Python file, use the following code:

import os.path
from g4f.cookies import set_cookies_dir, read_cookie_files

import g4f.debug
g4f.debug.logging = True

cookies_dir = os.path.join(os.path.dirname(__file__), "har_and_cookies")
set_cookies_dir(cookies_dir)
read_cookie_files(cookies_dir)

Debug Mode

If you enable debug mode, you will see logs similar to the following:

Read .har file: ./har_and_cookies/you.com.har
Cookies added: 10 from .you.com
Read cookie file: ./har_and_cookies/google.json
Cookies added: 16 from .google.com

.HAR File for OpenaiChat Provider

Generating a .HAR File

To utilize the OpenaiChat provider, a .har file is required from https://chatgpt.com/. Follow the steps below to create a valid .har file:

  1. Navigate to https://chatgpt.com/ using your preferred web browser and log in with your credentials.
  2. Access the Developer Tools in your browser. This can typically be done by right-clicking the page and selecting "Inspect," or by pressing F12 or Ctrl+Shift+I (Cmd+Option+I on a Mac).
  3. With the Developer Tools open, switch to the "Network" tab.
  4. Reload the website to capture the loading process within the Network tab.
  5. Initiate an action in the chat which can be captured in the .har file.
  6. Right-click any of the network activities listed and select "Save all as HAR with content" to export the .har file.
Storing the .HAR File
  • Place the exported .har file in the ./har_and_cookies directory if you are using Docker. Alternatively, you can store it in any preferred location within your current working directory.

Note: Ensure that your .har file is stored securely, as it may contain sensitive information.

Using Proxy

If you want to hide or change your IP address for the providers, you can set a proxy globally via an environment variable:

  • On macOS and Linux:
export G4F_PROXY="http://host:port"
  • On Windows:
set G4F_PROXY=http://host:port

🚀 Providers and Models

GPT-4

WebsiteProviderGPT-3.5GPT-4StreamStatusAuth
bing.comg4f.Provider.Bing❌✔️✔️Active❌
chatgpt.aig4f.Provider.ChatgptAi❌✔️✔️Unknown❌
liaobots.siteg4f.Provider.Liaobots✔️✔️✔️Unknown❌
chatgpt.comg4f.Provider.OpenaiChat✔️✔️✔️Active❌+✔️
raycast.comg4f.Provider.Raycast✔️✔️✔️Unknown✔️
beta.theb.aig4f.Provider.Theb✔️✔️✔️Unknown❌
you.comg4f.Provider.You✔️✔️✔️Active❌

Best OpenSource Models

While we wait for gpt-5, here is a list of new models that are at least better than gpt-3.5-turbo. Some are better than gpt-4. Expect this list to grow.

WebsiteProviderparametersbetter than
claude-3-opusg4f.Provider.You?Bgpt-4-0125-preview
command-r+g4f.Provider.HuggingChat104Bgpt-4-0314
llama-3-70bg4f.Provider.Llama or DeepInfra70Bgpt-4-0314
claude-3-sonnetg4f.Provider.You?Bgpt-4-0314
reka-coreg4f.Provider.Reka21Bgpt-4-vision
dbrx-instructg4f.Provider.DeepInfra132B / 36B activegpt-3.5-turbo
mixtral-8x22bg4f.Provider.DeepInfra176B / 44b activegpt-3.5-turbo

GPT-3.5

WebsiteProviderGPT-3.5GPT-4StreamStatusAuth
chat3.aiyunos.topg4f.Provider.AItianhuSpace✔️❌✔️Unknown❌
chat10.aichatos.xyzg4f.Provider.Aichatos✔️❌✔️Active❌
chatforai.storeg4f.Provider.ChatForAi✔️❌✔️Unknown❌
chatgpt4online.orgg4f.Provider.Chatgpt4Online✔️❌✔️Unknown❌
chatgpt-free.ccg4f.Provider.ChatgptNext✔️❌✔️Unknown❌
chatgptx.deg4f.Provider.ChatgptX✔️❌✔️Unknown❌
duckduckgo.comg4f.Provider.DDG✔️❌✔️Active❌
feedough.comg4f.Provider.Feedough✔️❌✔️Active❌
flowgpt.comg4f.Provider.FlowGpt✔️❌✔️Unknown❌
freegptsnav.aifree.siteg4f.Provider.FreeGpt✔️❌✔️Active❌
gpttalk.rug4f.Provider.GptTalkRu✔️❌✔️Unknown❌
koala.shg4f.Provider.Koala✔️❌✔️Unknown❌
app.myshell.aig4f.Provider.MyShell✔️❌✔️Unknown❌
perplexity.aig4f.Provider.PerplexityAi✔️❌✔️Unknown❌
poe.comg4f.Provider.Poe✔️❌✔️Unknown✔️
talkai.infog4f.Provider.TalkAi✔️❌✔️Unknown❌
chat.vercel.aig4f.Provider.Vercel✔️❌✔️Unknown❌
aitianhu.comg4f.Provider.AItianhu✔️❌✔️Inactive❌
chatgpt.bestim.orgg4f.Provider.Bestim✔️❌✔️Inactive❌
chatbase.cog4f.Provider.ChatBase✔️❌✔️Inactive❌
chatgptdemo.infog4f.Provider.ChatgptDemo✔️❌✔️Inactive❌
chat.chatgptdemo.aig4f.Provider.ChatgptDemoAi✔️❌✔️Inactive❌
chatgptfree.aig4f.Provider.ChatgptFree✔️❌❌Inactive❌
chatgptlogin.aig4f.Provider.ChatgptLogin✔️❌✔️Inactive❌
chat.3211000.xyzg4f.Provider.Chatxyz✔️❌✔️Inactive❌
gpt6.aig4f.Provider.Gpt6✔️❌✔️Inactive❌
gptchatly.comg4f.Provider.GptChatly✔️❌❌Inactive❌
ai18.gptforlove.comg4f.Provider.GptForLove✔️❌✔️Inactive❌
gptgo.aig4f.Provider.GptGo✔️❌✔️Inactive❌
gptgod.siteg4f.Provider.GptGod✔️❌✔️Inactive❌
onlinegpt.orgg4f.Provider.OnlineGpt✔️❌✔️Inactive❌

Other

WebsiteProviderStreamStatusAuth
openchat.teamg4f.Provider.Aura✔️Unknown❌
blackbox.aig4f.Provider.Blackbox✔️Active❌
cohereforai-c4ai-command-r-plus.hf.spaceg4f.Provider.Cohere✔️Unknown❌
deepinfra.comg4f.Provider.DeepInfra✔️Active❌
free.chatgpt.org.ukg4f.Provider.FreeChatgpt✔️Unknown❌
gemini.google.comg4f.Provider.Gemini✔️Active✔️
ai.google.devg4f.Provider.GeminiPro✔️Active✔️
gemini-chatbot-sigma.vercel.appg4f.Provider.GeminiProChat✔️Unknown❌
developers.sber.rug4f.Provider.GigaChat✔️Unknown✔️
console.groq.comg4f.Provider.Groq✔️Active✔️
huggingface.cog4f.Provider.HuggingChat✔️Active❌
huggingface.cog4f.Provider.HuggingFace✔️Active❌
llama2.aig4f.Provider.Llama✔️Unknown❌
meta.aig4f.Provider.MetaAI✔️Active❌
openrouter.aig4f.Provider.OpenRouter✔️Active✔️
labs.perplexity.aig4f.Provider.PerplexityLabs✔️Active❌
pi.aig4f.Provider.Pi✔️Unknown❌
replicate.comg4f.Provider.Replicate✔️Unknown❌
theb.aig4f.Provider.ThebApi✔️Unknown✔️
whiterabbitneo.comg4f.Provider.WhiteRabbitNeo✔️Unknown✔️
bard.google.comg4f.Provider.Bard❌Inactive✔️

Models

ModelBase ProviderProviderWebsite
gpt-3.5-turboOpenAI8+ Providersopenai.com
gpt-4OpenAI2+ Providersopenai.com
gpt-4-turboOpenAIg4f.Provider.Bingopenai.com
Llama-2-7b-chat-hfMeta2+ Providersllama.meta.com
Llama-2-13b-chat-hfMeta2+ Providersllama.meta.com
Llama-2-70b-chat-hfMeta3+ Providersllama.meta.com
Meta-Llama-3-8b-instructMeta1+ Providersllama.meta.com
Meta-Llama-3-70b-instructMeta2+ Providersllama.meta.com
CodeLlama-34b-Instruct-hfMetag4f.Provider.HuggingChatllama.meta.com
CodeLlama-70b-Instruct-hfMeta2+ Providersllama.meta.com
Mixtral-8x7B-Instruct-v0.1Huggingface4+ Providershuggingface.co
Mistral-7B-Instruct-v0.1Huggingface3+ Providershuggingface.co
Mistral-7B-Instruct-v0.2Huggingfaceg4f.Provider.DeepInfrahuggingface.co
zephyr-orpo-141b-A35b-v0.1Huggingface2+ Providershuggingface.co
dolphin-2.6-mixtral-8x7bHuggingfaceg4f.Provider.DeepInfrahuggingface.co
geminiGoogleg4f.Provider.Geminigemini.google.com
gemini-proGoogle2+ Providersgemini.google.com
claude-v2Anthropic1+ Providersanthropic.com
claude-3-opusAnthropicg4f.Provider.Youanthropic.com
claude-3-sonnetAnthropicg4f.Provider.Youanthropic.com
lzlv_70b_fp16_hfHuggingfaceg4f.Provider.DeepInfrahuggingface.co
airoboros-70bHuggingfaceg4f.Provider.DeepInfrahuggingface.co
openchat_3.5Huggingface2+ Providershuggingface.co
piInflectiong4f.Provider.Piinflection.ai

Image and Vision Models

LabelProviderImage ModelVision ModelWebsite
Microsoft Copilot in Bingg4f.Provider.Bingdall-e-3gpt-4-visionbing.com
DeepInfrag4f.Provider.DeepInfrastability-ai/sdxlllava-1.5-7b-hfdeepinfra.com
Geminig4f.Provider.Gemini✔️✔️gemini.google.com
Gemini APIg4f.Provider.GeminiPro❌gemini-1.5-proai.google.dev
Meta AIg4f.Provider.MetaAI✔️❌meta.ai
OpenAI ChatGPTg4f.Provider.OpenaiChatdall-e-3gpt-4-visionchatgpt.com
Rekag4f.Provider.Reka❌✔️chat.reka.ai
Replicateg4f.Provider.Replicatestability-ai/sdxlllava-v1.6-34breplicate.com
You.comg4f.Provider.Youdall-e-3✔️you.com

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🤝 Contribute

We welcome contributions from the community. Whether you're adding new providers or features, or simply fixing typos and making small improvements, your input is valued. Creating a pull request is all it takes – our co-pilot will handle the code review process. Once all changes have been addressed, we'll merge the pull request into the main branch and release the updates at a later time.

Guide: How do i create a new Provider?
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🙌 Contributors

A list of all contributors is available here

Having input implies that the AI's code generation utilized it as one of many sources.

©️ Copyright

This program is licensed under the GNU GPL v3

xtekky/gpt4free: Copyright (C) 2023 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.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.

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This project is licensed under GNU_GPL_v3.0.

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