import g4f
...

from g4f.client import Client

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

from g4f.gui import run_gui
run_gui()

import g4f

g4f.debug.logging = True  # Enable debug logging
g4f.debug.version_check = False  # Disable automatic version checking
print(g4f.Provider.Bing.params)  # Print supported args for Bing

# Using automatic a provider for the given model
## Streamed completion
response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)
for message in response:
    print(message, flush=True, end='')

## Normal response
response = g4f.ChatCompletion.create(
    model=g4f.models.gpt_4,
    messages=[{"role": "user", "content": "Hello"}],
)  # Alternative model setting

print(response)

import g4f

allowed_models = [
    'code-davinci-002',
    'text-ada-001',
    'text-babbage-001',
    'text-curie-001',
    'text-davinci-002',
    'text-davinci-003'
]

response = g4f.Completion.create(
    model='text-davinci-003',
    prompt='say this is a test'
)

print(response)

import g4f

# Print all available providers
print([
    provider.__name__
    for provider in g4f.Provider.__providers__
    if provider.working
])

# Execute with a specific provider
response = g4f.ChatCompletion.create(
    model="gpt-3.5-turbo",
    provider=g4f.Provider.Aichat,
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)
for message in response:
    print(message)

from g4f import set_cookies

set_cookies(".bing.com", {
  "_U": "cookie value"
})
set_cookies("chat.openai.com", {
  "access_token": "token value"
})

from g4f.gui import run_gui
run_gui()

import g4f

# Setting up the request for image creation
response = g4f.ChatCompletion.create(
    model=g4f.models.default, # Using the default model
    provider=g4f.Provider.Gemini, # Specifying the provider as Gemini
    messages=[{"role": "user", "content": "Create an image like this"}],
    image=open("images/g4f.png", "rb"), # Image input can be a data URI, bytes, PIL Image, or IO object
    image_name="g4f.png" # Optional: specifying the filename
)

# Displaying the response
print(response)

from g4f.image import ImageResponse

# Get image links from response
for chunk in g4f.ChatCompletion.create(
    model=g4f.models.default, # Using the default model
    provider=g4f.Provider.OpenaiChat, # Specifying the provider as OpenaiChat
    messages=[{"role": "user", "content": "Create images with dogs"}],
    access_token="...", # Need a access token from a plus user
    stream=True,
    ignore_stream=True
):
    if isinstance(chunk, ImageResponse):
        print(chunk.images) # Print generated image links
        print(chunk.alt) # Print used prompt for image generation

import g4f
from undetected_chromedriver import Chrome, ChromeOptions
from g4f.Provider import (
    Bard,
    Poe,
    AItianhuSpace,
    MyShell,
    PerplexityAi,
)

options = ChromeOptions()
options.add_argument("--incognito");
webdriver = Chrome(options=options, headless=True)
for idx in range(10):
    response = g4f.ChatCompletion.create(
        model=g4f.models.default,
        provider=g4f.Provider.MyShell,
        messages=[{"role": "user", "content": "Suggest me a name."}],
        webdriver=webdriver
    )
    print(f"{idx}:", response)
webdriver.quit()

import g4f
import asyncio

_providers = [
    g4f.Provider.Aichat,
    g4f.Provider.ChatBase,
    g4f.Provider.Bing,
    g4f.Provider.GptGo,
    g4f.Provider.You,
    g4f.Provider.Yqcloud,
]

async def run_provider(provider: g4f.Provider.BaseProvider):
    try:
        response = await g4f.ChatCompletion.create_async(
            model=g4f.models.default,
            messages=[{"role": "user", "content": "Hello"}],
            provider=provider,
        )
        print(f"{provider.__name__}:", response)
    except Exception as e:
        print(f"{provider.__name__}:", e)
        
async def run_all():
    calls = [
        run_provider(provider) for provider in _providers
    ]
    await asyncio.gather(*calls)

asyncio.run(run_all())

import g4f

response = g4f.ChatCompletion.create(
    model=g4f.models.default,
    messages=[{"role": "user", "content": "Hello"}],
    proxy="http://host:port",
    # or socks5://user:pass@host:port
    timeout=120,  # in secs
)

print(f"Result:", response)

from g4f.api import run_api

run_api()

from openai import OpenAI

client = OpenAI(
    # Set your Hugging Face token as the API key if you use embeddings
    api_key="YOUR_HUGGING_FACE_TOKEN",

    # Set the API base URL if needed, e.g., for a local development environment
    base_url="http://localhost:1337/v1"
)


def main():
    chat_completion = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": "write a poem about a tree"}],
        stream=True,
    )

    if isinstance(chat_completion, dict):
        # Not streaming
        print(chat_completion.choices[0].message.content)
    else:
        # Streaming
        for token in chat_completion:
            content = token.choices[0].delta.content
            if content is not None:
                print(content, end="", flush=True)


if __name__ == "__main__":
    main()

import requests
url = "http://localhost:1337/v1/chat/completions"
body = {
    "model": "gpt-3.5-turbo-16k",
    "stream": False,
    "messages": [
        {"role": "assistant", "content": "What can you do?"}
    ]
}
json_response = requests.post(url, json=body).json().get('choices', [])

for choice in json_response:
    print(choice.get('message', {}).get('content', ''))

from __future__ import annotations

from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider

class HogeService(AsyncGeneratorProvider):
    url                   = "https://chat-gpt.com"
    working               = True
    supports_gpt_35_turbo = True

    @classmethod
    async def create_async_generator(
        cls,
        model: str,
        messages: Messages,
        proxy: str = None,
        **kwargs
    ) -> AsyncResult:
        yield ""

from .HogeService import HogeService

__all__ = [
  HogeService,
]

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='')