gpt4free

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

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='')

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)

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:

Install the library:

pip install -U g4f

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

ChatGPT

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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.

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.

AutoGPT

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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.

DeepSpeed

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

Pros of DeepSpeed

Focuses on optimizing deep learning training and inference
Offers advanced techniques like ZeRO (Zero Redundancy Optimizer)
Supports various AI frameworks and models

Cons of DeepSpeed

More complex setup and configuration
Primarily targets large-scale AI training scenarios
Steeper learning curve for beginners

Code Comparison

DeepSpeed:

import deepspeed
model_engine, optimizer, _, _ = deepspeed.initialize(args=args,
                                                     model=model,
                                                     model_parameters=params)

gpt4free:

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

Summary

DeepSpeed is a powerful library for optimizing deep learning workflows, particularly suited for large-scale AI training. It offers advanced techniques like ZeRO and supports various AI frameworks. However, it has a steeper learning curve and is more complex to set up compared to gpt4free.

gpt4free, on the other hand, provides a simpler interface for accessing GPT-like models, making it more accessible for quick prototyping and smaller projects. It lacks the advanced optimization features of DeepSpeed but offers easier integration for basic AI text generation tasks.

openai-python

24,080

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

transformers

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🤗 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

Written by @xtekky

[!IMPORTANT] 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] ^{Latest version:}

^Stats:

pip install -U g4f[all]

docker pull hlohaus789/g4f

ð What's New

1000032415

Explore the latest features and updates
Find comprehensive details on our Releases Page.
Stay updated with our Telegram Channel ð¨
Join us at telegram.me/g4f_channel.
Subscribe to our Discord News Channel ð¬ðï¸
Stay informed about updates via our News Channel: discord.gg/5E39JUWUFa.
Get support in our Discord Community ð¤ð»
Reach out for help in our Support Group: discord.gg/qXA4Wf4Fsm.

ð» 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. ð

ð GPT4Free on HuggingFace

Is a proof-of-concept API package for multi-provider AI requests. It showcases features such as:

Load balancing and request flow control.
Seamless integration with multiple AI providers.
Comprehensive text and image generation support.

Explore the Visit GPT4Free on HuggingFace Space for a hosted version or Duplicate GPT4Free Space it for personal use.

ð Table of Contents

ð What's New
ð Table of Contents
â¡ Getting Started
- ð Installation
ð¡ Usage
ð Providers and Models
ð Powered by gpt4free
ð¤ Contribute
- How do i create a new Provider?
- How can AI help me with writing code?
ð Contributors
Â©ï¸ Copyright
â Star History
ð License

â¡ï¸ Getting Started

ð Installation

ð³ Using Docker

Install Docker: Download and install Docker.
Set Up Directories: Before running the container, make sure the necessary data directories exist or can be created. For example, you can create and set ownership on these directories by running:

   mkdir -p ${PWD}/har_and_cookies ${PWD}/generated_images
   sudo chown -R 1200:1201 ${PWD}/har_and_cookies ${PWD}/generated_images

Run the Docker Container: Use the following commands to pull the latest image and start the container (Only x64):

   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_images:/app/generated_images \
     hlohaus789/g4f:latest

Running the Slim Docker Image: And use the following commands to run the Slim Docker image. This command also updates the g4f package at startup and installs any additional dependencies: (x64 and arm64)

  mkdir -p ${PWD}/har_and_cookies ${PWD}/generated_images
  chown -R 1000:1000 ${PWD}/har_and_cookies ${PWD}/generated_images
	docker run \
	  -p 1337:1337 \
	  -v ${PWD}/har_and_cookies:/app/har_and_cookies \
	  -v ${PWD}/generated_images:/app/generated_images \
	  hlohaus789/g4f:latest-slim \
	  rm -r -f /app/g4f/ \
	  && pip install -U g4f[slim] \
	  && python -m g4f --debug

Access the Client Interface:
- To use the included client, navigate to: http://localhost:8080/chat/
- Or set the API base for your client to: http://localhost:8080/v1
(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.

ðª Windows Guide (.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:

Download the Application: Visit our releases page and download the most recent version of the application, named g4f.exe.zip.
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.
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.
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.

ð Python Installation

Prerequisites:

Install Python 3.10+ from python.org.
Install Google Chrome for certain providers.

Install with PyPI:

pip install -U g4f[all]

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

Install from Source:

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

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

ð¡ Usage

ð Text Generation

from g4f.client import Client

client = Client()
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello"}],
    web_search=False
)
print(response.choices[0].message.content)

Hello! How can I assist you today?

ð¨ Image Generation

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}")

ð Web Interface

Run the GUI using Python:

from g4f.gui import run_gui

run_gui()

Run via CLI (To start the Flask Server):

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

Or, start the FastAPI Server:

python -m g4f --port 8080 --debug

Learn More About the GUI: For detailed instructions on how to set up, configure, and use the GPT4Free GUI, refer to the GUI Documentation . This guide includes step-by-step details on provider selection, managing conversations, using advanced features like speech recognition, and more.

ð¤ Interference API

The Interference API enables seamless integration with OpenAI's services through G4F, allowing you to deploy efficient AI solutions.

Documentation: Interference API Docs
Endpoint: http://localhost:1337/v1
Swagger UI: Explore the OpenAPI documentation via Swagger UI at http://localhost:1337/docs
Provider Selection: How to Specify a Provider?

This API is designed for straightforward implementation and enhanced compatibility with other OpenAI integrations.

ð± Run on Smartphone

Run the Web UI on your smartphone for easy access on the go. Check out the dedicated guide to learn how to set up and use the GUI on your mobile device: Run on Smartphone Guide

ð Full Documentation for Python API

Client API from G4F: /docs/client
AsyncClient API from G4F: /docs/async_client
Requests API from G4F: /docs/requests
File API from G4F: /docs/file
PydanticAI and LangChain Integration for G4F: /docs/pydantic_ai
Legacy API with python modules: /docs/legacy

ð Powered by gpt4free

ð Projects	â Stars	ð Forks	ð Issues	ð¬ Pull requests
gpt4free
gpt4free-ts
Free AI API's & Potential Providers List
ChatGPT-Clone
Ai agent
ChatGpt Discord Bot
chatGPT-discord-bot
Nyx-Bot (Discord)
LangChain gpt4free
ChatGpt Telegram Bot
ChatGpt Line Bot
Action Translate Readme
Langchain Document GPT
python-tgpt
GPT4js
VividNode (pyqt-openai)

ð¤ 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 â 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?

Read: Create Provider Guide

Guide: How can AI help me with writing code?

Read: AI Assistance Guide

Contributors

A list of all contributors is available here

ading2210 xqdoo00o nathanrchn dsdanielpark missuo

The Vercel.py file contains code from vercel-llm-api by @ading2210
The har_file.py has input from xqdoo00o/ChatGPT-to-API
The PerplexityLabs.py has input from nathanrchn/perplexityai
The Gemini.py has input from dsdanielpark/Gemini-API
The MetaAI.py file contains code from meta-ai-api by @Strvm
The proofofwork.py has input from missuo/FreeGPT35
The Gemini.py has input from HanaokaYuzu/Gemini-API

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

Â©ï¸ 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/>.

â Star History

ð License

This project is licensed under GNU_GPL_v3.0.

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Quick Overview

Pros

Cons

Code Examples

Getting Started

Competitor Comparisons

Pros of ChatGPT

Cons of ChatGPT

Code Comparison

Pros of agentic

Cons of agentic

Code Comparison

Pros of AutoGPT

Cons of AutoGPT

Code Comparison

Pros of DeepSpeed

Cons of DeepSpeed

Code Comparison

Summary

Pros of openai-python

Cons of openai-python

Code Comparison

Key Differences

Use Cases

Pros of transformers

Cons of transformers

Code Comparison

Summary

Convert designs to code with AI

README

ð What's New

ð» Site Takedown

ð GPT4Free on HuggingFace

ð Table of Contents

â¡ï¸ Getting Started

ð Installation

ð³ Using Docker

ðª Windows Guide (.exe)

ð Python Installation

Prerequisites:

Install with PyPI:

Install from Source:

ð¡ Usage

ð Text Generation

ð¨ Image Generation

ð Web Interface

ð¤ Interference API

ð± Run on Smartphone

ð Full Documentation for Python API

ð Powered by gpt4free

ð¤ Contribute

Guide: How do i create a new Provider?

Guide: How can AI help me with writing code?

Contributors

Â©ï¸ Copyright

â­ Star History

ð License

Top Related Projects

Convert designs to code with AI

ð What's New

ð» Site Takedown

ð GPT4Free on HuggingFace

ð Table of Contents

â¡ï¸ Getting Started

ð Installation

ð³ Using Docker

ðª Windows Guide (.exe)

ð Python Installation

ð¡ Usage

ð Text Generation

ð¨ Image Generation

ð Web Interface

ð¤ Interference API

ð± Run on Smartphone

ð Full Documentation for Python API

ð Powered by gpt4free

ð¤ Contribute

Â©ï¸ Copyright

â Star History

ð License