/gpt4free-flask-api

The official gpt4free repository | various collection of powerful language models

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

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This (quite censored) New Version of gpt4free, was just released, it may contain bugs, open an issue or contribute a PR when encountering one, some features were disabled. Docker is for now not available but I would be happy if someone contributes a PR. The g4f GUI will be uploaded soon enough.

Table of Contents:

Getting Started

Prerequisites:

  1. Download and install Python (Version 3.x is recommended).

Setting up the project:

  1. Clone the GitHub repository:
git clone https://github.com/xtekky/gpt4free.git
  1. Navigate to the project directory:
cd gpt4free
  1. (Recommended) Create a virtual environment to manage Python packages for your project:
python3 -m venv venv
  1. Activate the virtual environment:
    • On Windows:
    .\venv\Scripts\activate
    
    • On macOS and Linux:
    source venv/bin/activate
    
  2. Install the required Python packages from requirements.txt:
pip install -r requirements.txt
  1. Create a test.py file in the root folder and start using the repo, further Instructions are below
import g4f

...

Usage

The g4f Package

import g4f


print(g4f.Provider.Ails.params) # supported args

# Automatic selection of provider

# streamed completion
response = g4f.ChatCompletion.create(model='gpt-3.5-turbo', messages=[
                                     {"role": "user", "content": "Hello world"}], stream=True)

for message in response:
    print(message)

# normal response
response = g4f.ChatCompletion.create(model=g4f.Model.gpt_4, messages=[
                                     {"role": "user", "content": "hi"}]) # alterative model setting

print(response)


# Set with provider
response = g4f.ChatCompletion.create(model='gpt-3.5-turbo', provider=g4f.Provider.Forefront, messages=[
                                     {"role": "user", "content": "Hello world"}], stream=True)

for message in response:
    print(message)

providers:

from g4f.Provider import (
    Ails,
    You,
    Bing,
    Yqcloud,
    Theb,
    Aichat,
    Bard,
    Vercel,
    Forefront,
    Lockchat,
    Liaobots,
    H2o,
    ChatgptLogin,
    DeepAi,
    GetGpt
)

# usage:
response = g4f.ChatCompletion.create(..., provider=ProviderName)

interference openai-proxy api (use with openai python package)

run server:

python3 -m interference.app
import openai

openai.api_key = ''
openai.api_base = 'http://127.0.0.1:1337'

chat_completion = openai.ChatCompletion.create(stream=True,
    model='gpt-3.5-turbo', messages=[{'role': 'user', 'content': 'write a poem about a tree'}])

#print(chat_completion.choices[0].message.content)

for token in chat_completion:
    
    content = token['choices'][0]['delta'].get('content')
    if content != None:
        print(content)

Models

gpt-3.5 / gpt-4

Website Provider gpt-3.5 gpt-4 Streaming Status Auth
bing.com g4f.Provider.Bing ✔️ ✔️ ✔️ Active
super.lockchat.app g4f.Provider.Lockchat ✔️ ✔️ ✔️ Active
liaobots.com g4f.Provider.Liaobots ✔️ ✔️ ✔️ Active ✔️
ai.ls g4f.Provider.Ails ✔️ ✔️ Active
you.com g4f.Provider.You ✔️ ✔️ Active
chat9.yqcloud.top g4f.Provider.Yqcloud ✔️ ✔️ Active
theb.ai g4f.Provider.Theb ✔️ ✔️ Active
play.vercel.ai g4f.Provider.Vercel ✔️ ✔️ Inactive
forefront.com g4f.Provider.Forefront ✔️ ✔️ Active
deepai.org g4f.Provider.DeepAi ✔️ ✔️ Active
chat.getgpt.world g4f.Provider.GetGpt ✔️ ✔️ Active
chatgptlogin.ac g4f.Provider.ChatgptLogin ✔️ Active
chat-gpt.org g4f.Provider.Aichat ✔️ Active

Other Models

Model Base Provider Provider Website
palm2 Google g4f.Provider.Bard bard.google.com
falcon-40b Huggingface g4f.Provider.H2o H2o
falcon-7b Huggingface g4f.Provider.H2o H2o
llama-13b Huggingface g4f.Provider.H2o H2o
claude-instant-v1-100k Anthropic g4f.Provider.Vercel sdk.vercel.ai
claude-instant-v1 Anthropic g4f.Provider.Vercel sdk.vercel.ai
claude-v1-100k Anthropic g4f.Provider.Vercel sdk.vercel.ai
claude-v1 Anthropic g4f.Provider.Vercel sdk.vercel.ai
alpaca-7b Replicate g4f.Provider.Vercel sdk.vercel.ai
stablelm-tuned-alpha-7b Replicate g4f.Provider.Vercel sdk.vercel.ai
bloom Huggingface g4f.Provider.Vercel sdk.vercel.ai
bloomz Huggingface g4f.Provider.Vercel sdk.vercel.ai
flan-t5-xxl Huggingface g4f.Provider.Vercel sdk.vercel.ai
flan-ul2 Huggingface g4f.Provider.Vercel sdk.vercel.ai
gpt-neox-20b Huggingface g4f.Provider.Vercel sdk.vercel.ai
oasst-sft-4-pythia-12b-epoch-3.5 Huggingface g4f.Provider.Vercel sdk.vercel.ai
santacoder Huggingface g4f.Provider.Vercel sdk.vercel.ai
command-medium-nightly Cohere g4f.Provider.Vercel sdk.vercel.ai
command-xlarge-nightly Cohere g4f.Provider.Vercel sdk.vercel.ai
code-cushman-001 OpenAI g4f.Provider.Vercel sdk.vercel.ai
code-davinci-002 OpenAI g4f.Provider.Vercel sdk.vercel.ai
text-ada-001 OpenAI g4f.Provider.Vercel sdk.vercel.ai
text-babbage-001 OpenAI g4f.Provider.Vercel sdk.vercel.ai
text-curie-001 OpenAI g4f.Provider.Vercel sdk.vercel.ai
text-davinci-002 OpenAI g4f.Provider.Vercel sdk.vercel.ai
text-davinci-003 OpenAI g4f.Provider.Vercel sdk.vercel.ai

Related gpt4free projects

🎁 Projects ⭐ Stars 📚 Forks 🛎 Issues 📬 Pull requests
gpt4free Stars Forks Issues Pull Requests
gpt4free-ts Stars Forks Issues Pull Requests
ChatGPT-Clone Stars Forks Issues Pull Requests
ChatGpt Discord Bot Stars Forks Issues Pull Requests

Contribute

to add another provider, its very simple:

  1. create a new file in g4f/Provider/Providers with the name of the Provider
  2. in the file, paste the Boilerplate you can find in g4f/Provider/Provider.py:
import os
from ..typing import sha256, Dict, get_type_hints

url = None
model = None
supports_stream = False
needs_auth = False

def _create_completion(model: str, messages: list, stream: bool, **kwargs):
    return


params = f'g4f.Providers.{os.path.basename(__file__)[:-3]} supports: ' + \
    '(%s)' % ', '.join(
        [f"{name}: {get_type_hints(_create_completion)[name].__name__}" for name in _create_completion.__code__.co_varnames[:_create_completion.__code__.co_argcount]])
  1. Here, you can adjust the settings, for example if the website does support streaming, set supports_stream to True...
  2. Write code to request the provider in _create_completion and yield the response, even if its a one-time response, do not hesitate to look at other providers for inspiration
  3. Add the Provider Name in g4f/Provider/init.py
from . import Provider
from .Providers import (
    ...,
    ProviderNameHere
)
  1. You are done !, test the provider by calling it:
import g4f

response = g4f.ChatCompletion.create(model='gpt-3.5-turbo', provider=g4f.Provider.PROVIDERNAME,
                                    messages=[{"role": "user", "content": "test"}], stream=g4f.Provider.PROVIDERNAME.supports_stream)

for message in response:
    print(message, flush=True, end='')

ChatGPT clone

Currently implementing new features and trying to scale it, please be patient it may be unstable
https://chat.g4f.ai/chat This site was developed by me and includes gpt-4/3.5, internet access and gpt-jailbreak's like DAN
Run locally here: https://github.com/xtekky/chatgpt-clone

Copyright:

This program is licensed under the GNU GPL v3

Copyright Notice:

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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