gpt4free/g4f/__init__.py

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from __future__ import annotations
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import os
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import logging
from typing import Union, Optional, Coroutine
from . import debug, version
from .models import Model
from .client import Client, AsyncClient
from .typing import Messages, CreateResult, AsyncResult, ImageType
from .errors import StreamNotSupportedError
from .cookies import get_cookies, set_cookies
from .providers.types import ProviderType
from .client.service import get_model_and_provider, get_last_provider
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#Configure "g4f" logger
logger = logging.getLogger(__name__)
log_handler = logging.StreamHandler()
log_handler.setFormatter(logging.Formatter(logging.BASIC_FORMAT))
logger.addHandler(log_handler)
logger.setLevel(logging.ERROR)
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class ChatCompletion:
@staticmethod
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def create(model : Union[Model, str],
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messages : Messages,
provider : Union[ProviderType, str, None] = None,
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stream : bool = False,
image : ImageType = None,
image_name: Optional[str] = None,
ignore_working: bool = False,
ignore_stream: bool = False,
**kwargs) -> Union[CreateResult, str]:
model, provider = get_model_and_provider(
model, provider, stream,
ignore_working,
ignore_stream
)
if image is not None:
kwargs["images"] = [(image, image_name)]
if "proxy" not in kwargs:
proxy = os.environ.get("G4F_PROXY")
if proxy:
kwargs["proxy"] = proxy
if ignore_stream:
kwargs["ignore_stream"] = True
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result = provider.create_completion(model, messages, stream=stream, **kwargs)
return result if stream else ''.join([str(chunk) for chunk in result if chunk])
@staticmethod
def create_async(model : Union[Model, str],
messages : Messages,
provider : Union[ProviderType, str, None] = None,
stream : bool = False,
image : ImageType = None,
image_name: Optional[str] = None,
ignore_stream: bool = False,
ignore_working: bool = False,
**kwargs) -> Union[AsyncResult, Coroutine[str]]:
model, provider = get_model_and_provider(model, provider, False, ignore_working)
if image is not None:
kwargs["images"] = [(image, image_name)]
if "proxy" not in kwargs:
proxy = os.environ.get("G4F_PROXY")
if proxy:
kwargs["proxy"] = proxy
if ignore_stream:
kwargs["ignore_stream"] = True
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if stream:
if hasattr(provider, "create_async_generator"):
return provider.create_async_generator(model, messages, **kwargs)
raise StreamNotSupportedError(f'{provider.__name__} does not support "stream" argument in "create_async"')
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return provider.create_async(model, messages, **kwargs)