from __future__ import annotations import sys import asyncio from asyncio import AbstractEventLoop from concurrent.futures import ThreadPoolExecutor from abc import abstractmethod from inspect import signature, Parameter from typing import Callable, Union from ..typing import CreateResult, AsyncResult, Messages from .types import BaseProvider from .response import FinishReason, BaseConversation, SynthesizeData from ..errors import NestAsyncioError, ModelNotSupportedError from .. import debug if sys.version_info < (3, 10): NoneType = type(None) else: from types import NoneType try: import nest_asyncio has_nest_asyncio = True except ImportError: has_nest_asyncio = False try: import uvloop has_uvloop = True except ImportError: has_uvloop = False # Set Windows event loop policy for better compatibility with asyncio and curl_cffi if sys.platform == 'win32': try: from curl_cffi import aio if not hasattr(aio, "_get_selector"): if isinstance(asyncio.get_event_loop_policy(), asyncio.WindowsProactorEventLoopPolicy): asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) except ImportError: pass def get_running_loop(check_nested: bool) -> Union[AbstractEventLoop, None]: try: loop = asyncio.get_running_loop() # Do not patch uvloop loop because its incompatible. if has_uvloop: if isinstance(loop, uvloop.Loop): return loop if not hasattr(loop.__class__, "_nest_patched"): if has_nest_asyncio: nest_asyncio.apply(loop) elif check_nested: raise NestAsyncioError('Install "nest_asyncio" package | pip install -U nest_asyncio') return loop except RuntimeError: pass # Fix for RuntimeError: async generator ignored GeneratorExit async def await_callback(callback: Callable): return await callback() class AbstractProvider(BaseProvider): """ Abstract class for providing asynchronous functionality to derived classes. """ @classmethod async def create_async( cls, model: str, messages: Messages, *, loop: AbstractEventLoop = None, executor: ThreadPoolExecutor = None, **kwargs ) -> str: """ Asynchronously creates a result based on the given model and messages. Args: cls (type): The class on which this method is called. model (str): The model to use for creation. messages (Messages): The messages to process. loop (AbstractEventLoop, optional): The event loop to use. Defaults to None. executor (ThreadPoolExecutor, optional): The executor for running async tasks. Defaults to None. **kwargs: Additional keyword arguments. Returns: str: The created result as a string. """ loop = loop or asyncio.get_running_loop() def create_func() -> str: return "".join(cls.create_completion(model, messages, False, **kwargs)) return await asyncio.wait_for( loop.run_in_executor(executor, create_func), timeout=kwargs.get("timeout") ) @classmethod def get_parameters(cls) -> dict[str, Parameter]: return signature( cls.create_async_generator if issubclass(cls, AsyncGeneratorProvider) else cls.create_async if issubclass(cls, AsyncProvider) else cls.create_completion ).parameters @classmethod @property def params(cls) -> str: """ Returns the parameters supported by the provider. Args: cls (type): The class on which this property is called. Returns: str: A string listing the supported parameters. """ def get_type_name(annotation: type) -> str: return annotation.__name__ if hasattr(annotation, "__name__") else str(annotation) args = "" for name, param in cls.get_parameters().items(): if name in ("self", "kwargs") or (name == "stream" and not cls.supports_stream): continue args += f"\n {name}" args += f": {get_type_name(param.annotation)}" if param.annotation is not Parameter.empty else "" default_value = f'"{param.default}"' if isinstance(param.default, str) else param.default args += f" = {default_value}" if param.default is not Parameter.empty else "" args += "," return f"g4f.Provider.{cls.__name__} supports: ({args}\n)" class AsyncProvider(AbstractProvider): """ Provides asynchronous functionality for creating completions. """ @classmethod def create_completion( cls, model: str, messages: Messages, stream: bool = False, **kwargs ) -> CreateResult: """ Creates a completion result synchronously. Args: cls (type): The class on which this method is called. model (str): The model to use for creation. messages (Messages): The messages to process. stream (bool): Indicates whether to stream the results. Defaults to False. loop (AbstractEventLoop, optional): The event loop to use. Defaults to None. **kwargs: Additional keyword arguments. Returns: CreateResult: The result of the completion creation. """ get_running_loop(check_nested=False) yield asyncio.run(cls.create_async(model, messages, **kwargs)) @staticmethod @abstractmethod async def create_async( model: str, messages: Messages, **kwargs ) -> str: """ Abstract method for creating asynchronous results. Args: model (str): The model to use for creation. messages (Messages): The messages to process. **kwargs: Additional keyword arguments. Raises: NotImplementedError: If this method is not overridden in derived classes. Returns: str: The created result as a string. """ raise NotImplementedError() class AsyncGeneratorProvider(AsyncProvider): """ Provides asynchronous generator functionality for streaming results. """ supports_stream = True @classmethod def create_completion( cls, model: str, messages: Messages, stream: bool = True, **kwargs ) -> CreateResult: """ Creates a streaming completion result synchronously. Args: cls (type): The class on which this method is called. model (str): The model to use for creation. messages (Messages): The messages to process. stream (bool): Indicates whether to stream the results. Defaults to True. loop (AbstractEventLoop, optional): The event loop to use. Defaults to None. **kwargs: Additional keyword arguments. Returns: CreateResult: The result of the streaming completion creation. """ loop = get_running_loop(check_nested=False) new_loop = False if loop is None: loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) new_loop = True generator = cls.create_async_generator(model, messages, stream=stream, **kwargs) gen = generator.__aiter__() try: while True: yield loop.run_until_complete(await_callback(gen.__anext__)) except StopAsyncIteration: pass finally: if new_loop: loop.close() asyncio.set_event_loop(None) @classmethod async def create_async( cls, model: str, messages: Messages, **kwargs ) -> str: """ Asynchronously creates a result from a generator. Args: cls (type): The class on which this method is called. model (str): The model to use for creation. messages (Messages): The messages to process. **kwargs: Additional keyword arguments. Returns: str: The created result as a string. """ return "".join([ str(chunk) async for chunk in cls.create_async_generator(model, messages, stream=False, **kwargs) if not isinstance(chunk, (Exception, FinishReason, BaseConversation, SynthesizeData)) ]) @staticmethod @abstractmethod async def create_async_generator( model: str, messages: Messages, stream: bool = True, **kwargs ) -> AsyncResult: """ Abstract method for creating an asynchronous generator. Args: model (str): The model to use for creation. messages (Messages): The messages to process. stream (bool): Indicates whether to stream the results. Defaults to True. **kwargs: Additional keyword arguments. Raises: NotImplementedError: If this method is not overridden in derived classes. Returns: AsyncResult: An asynchronous generator yielding results. """ raise NotImplementedError() class ProviderModelMixin: default_model: str = None models: list[str] = [] model_aliases: dict[str, str] = {} image_models: list = None @classmethod def get_models(cls) -> list[str]: if not cls.models and cls.default_model is not None: return [cls.default_model] return cls.models @classmethod def get_model(cls, model: str) -> str: if not model and cls.default_model is not None: model = cls.default_model elif model in cls.model_aliases: model = cls.model_aliases[model] elif model not in cls.get_models() and cls.models: raise ModelNotSupportedError(f"Model is not supported: {model} in: {cls.__name__}") debug.last_model = model return model