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https://github.com/xtekky/gpt4free.git
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~ | Merge pull request #941 from hlohaus/myshell
AItianhuSpace Provider with GPT 4 added
This commit is contained in:
commit
fd5d28cf7b
73
g4f/Provider/AItianhuSpace.py
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73
g4f/Provider/AItianhuSpace.py
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@ -0,0 +1,73 @@
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from __future__ import annotations
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import random, json
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from g4f.requests import AsyncSession, StreamRequest
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from .base_provider import AsyncGeneratorProvider, format_prompt
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domains = {
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"gpt-3.5-turbo": ".aitianhu.space",
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"gpt-4": ".aitianhu.website",
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}
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class AItianhuSpace(AsyncGeneratorProvider):
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url = "https://chat3.aiyunos.top/"
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working = True
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supports_gpt_35_turbo = True
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: list[dict[str, str]],
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stream: bool = True,
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**kwargs
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) -> str:
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if not model:
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model = "gpt-3.5-turbo"
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elif not model in domains:
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raise ValueError(f"Model are not supported: {model}")
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chars = 'abcdefghijklmnopqrstuvwxyz0123456789'
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rand = ''.join(random.choice(chars) for _ in range(6))
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domain = domains[model]
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url = f'https://{rand}{domain}/api/chat-process'
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headers = {
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"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36",
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}
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async with AsyncSession(headers=headers, impersonate="chrome107", verify=False) as session:
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data = {
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"prompt": format_prompt(messages),
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"options": {},
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"systemMessage": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully.",
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"temperature": 0.8,
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"top_p": 1,
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**kwargs
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}
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async with StreamRequest(session, "POST", url, json=data) as response:
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response.raise_for_status()
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async for line in response.content:
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line = json.loads(line.rstrip())
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if "detail" in line:
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content = line["detail"]["choices"][0]["delta"].get("content")
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if content:
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yield content
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elif "message" in line and "AI-4接口非常昂贵" in line["message"]:
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raise RuntimeError("Rate limit for GPT 4 reached")
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else:
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raise RuntimeError("Response: {line}")
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@classmethod
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@property
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def params(cls):
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params = [
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("model", "str"),
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("messages", "list[dict[str, str]]"),
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("stream", "bool"),
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("temperature", "float"),
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("top_p", "int"),
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]
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param = ", ".join([": ".join(p) for p in params])
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return f"g4f.provider.{cls.__name__} supports: ({param})"
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@ -60,9 +60,10 @@ class Aivvm(BaseProvider):
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response = requests.post(
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"https://chat.aivvm.com/api/chat", headers=headers, json=json_data, stream=True)
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response.raise_for_status()
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for line in response.iter_content(chunk_size=1048):
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yield line.decode('utf-8')
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for chunk in response.iter_content(chunk_size=None):
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yield chunk.decode('utf-8')
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@classmethod
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@property
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@ -18,7 +18,13 @@ class Vercel(BaseProvider):
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def create_completion(
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model: str,
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messages: list[dict[str, str]],
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stream: bool, **kwargs ) -> CreateResult:
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stream: bool,
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**kwargs
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) -> CreateResult:
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if not model:
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model = "gpt-3.5-turbo"
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elif model not in model_info:
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raise ValueError(f"Model are not supported: {model}")
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headers = {
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'authority' : 'sdk.vercel.ai',
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@ -26,7 +32,7 @@ class Vercel(BaseProvider):
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'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
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'cache-control' : 'no-cache',
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'content-type' : 'application/json',
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'custom-encoding' : AntiBotToken(),
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'custom-encoding' : get_anti_bot_token(),
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'origin' : 'https://sdk.vercel.ai',
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'pragma' : 'no-cache',
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'referer' : 'https://sdk.vercel.ai/',
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@ -48,22 +54,20 @@ class Vercel(BaseProvider):
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'playgroundId': str(uuid.uuid4()),
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'chatIndex' : 0} | model_info[model]['default_params']
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server_error = True
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retries = 0
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max_retries = kwargs.get('max_retries', 20)
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while server_error and not retries > max_retries:
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for i in range(max_retries):
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response = requests.post('https://sdk.vercel.ai/api/generate',
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headers=headers, json=json_data, stream=True)
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try:
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response.raise_for_status()
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except:
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continue
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for token in response.iter_content(chunk_size=8):
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yield token.decode()
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break
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for token in response.iter_content(chunk_size=2046):
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if token != b'Internal Server Error':
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server_error = False
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yield (token.decode())
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retries += 1
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def AntiBotToken() -> str:
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def get_anti_bot_token() -> str:
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headers = {
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'authority' : 'sdk.vercel.ai',
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'accept' : '*/*',
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@ -4,6 +4,7 @@ from .Aichat import Aichat
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from .Ails import Ails
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from .AiService import AiService
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from .AItianhu import AItianhu
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from .AItianhuSpace import AItianhuSpace
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from .Aivvm import Aivvm
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from .Bard import Bard
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from .Bing import Bing
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@ -52,6 +53,7 @@ __all__ = [
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'Ails',
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'AiService',
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'AItianhu',
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'AItianhuSpace',
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'Aivvm',
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'Bard',
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'Bing',
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@ -1,7 +1,9 @@
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from __future__ import annotations
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import asyncio
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from asyncio import SelectorEventLoop
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import functools
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from asyncio import SelectorEventLoop, AbstractEventLoop
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from concurrent.futures import ThreadPoolExecutor
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from abc import ABC, abstractmethod
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import browser_cookie3
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@ -27,6 +29,31 @@ class BaseProvider(ABC):
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) -> CreateResult:
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raise NotImplementedError()
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@classmethod
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async def create_async(
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cls,
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model: str,
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messages: list[dict[str, str]],
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*,
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loop: AbstractEventLoop = None,
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executor: ThreadPoolExecutor = None,
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**kwargs
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) -> str:
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if not loop:
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loop = asyncio.get_event_loop()
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partial_func = functools.partial(
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cls.create_completion,
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model,
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messages,
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False,
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**kwargs
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)
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response = await loop.run_in_executor(
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executor,
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partial_func
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)
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return "".join(response)
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@classmethod
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@property
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@ -127,7 +154,7 @@ def create_event_loop() -> SelectorEventLoop:
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except RuntimeError:
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return SelectorEventLoop()
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raise RuntimeError(
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'Use "create_async" instead of "create" function in a async loop.')
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'Use "create_async" instead of "create" function in a running event loop.')
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_cookies = {}
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@ -17,6 +17,7 @@ from .Provider import (
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Wewordle,
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Yqcloud,
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AItianhu,
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AItianhuSpace,
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Aichat,
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Myshell,
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)
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@ -38,7 +39,7 @@ default = Model(
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Wewordle, # Responds with markdown
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Yqcloud, # Answers short questions in chinese
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ChatBase, # Don't want to answer creatively
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DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, Myshell,
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DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, AItianhuSpace, Aichat, Myshell,
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])
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)
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@ -47,7 +48,7 @@ gpt_35_turbo = Model(
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name = 'gpt-3.5-turbo',
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base_provider = 'openai',
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best_provider = RetryProvider([
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DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, Myshell,
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DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, AItianhuSpace, Myshell,
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])
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)
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@ -55,7 +56,7 @@ gpt_4 = Model(
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name = 'gpt-4',
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base_provider = 'openai',
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best_provider = RetryProvider([
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Aivvm, Myshell
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Aivvm, Myshell, AItianhuSpace,
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])
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)
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78
g4f/requests.py
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78
g4f/requests.py
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from __future__ import annotations
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import json, sys
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from aiohttp import StreamReader
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from aiohttp.base_protocol import BaseProtocol
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from curl_cffi.requests import AsyncSession
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from curl_cffi.requests.cookies import Request
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from curl_cffi.requests.cookies import Response
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class StreamResponse:
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def __init__(self, inner: Response, content: StreamReader, request: Request):
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self.inner = inner
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self.content = content
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self.request = request
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self.status_code = inner.status_code
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self.reason = inner.reason
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self.ok = inner.ok
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async def text(self) -> str:
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content = await self.content.read()
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return content.decode()
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def raise_for_status(self):
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if not self.ok:
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raise RuntimeError(f"HTTP Error {self.status_code}: {self.reason}")
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async def json(self, **kwargs):
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return json.loads(await self.content.read(), **kwargs)
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class StreamRequest:
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def __init__(self, session: AsyncSession, method: str, url: str, **kwargs):
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self.session = session
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self.loop = session.loop
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self.content = StreamReader(
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BaseProtocol(session.loop),
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sys.maxsize,
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loop=session.loop
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)
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self.method = method
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self.url = url
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self.options = kwargs
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def on_content(self, data):
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if not self.enter.done():
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self.enter.set_result(None)
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self.content.feed_data(data)
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def on_done(self, task):
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self.content.feed_eof()
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async def __aenter__(self) -> StreamResponse:
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self.curl = await self.session.pop_curl()
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self.enter = self.session.loop.create_future()
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request, _, header_buffer = self.session._set_curl_options(
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self.curl,
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self.method,
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self.url,
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content_callback=self.on_content,
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**self.options
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)
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handle = self.session.acurl.add_handle(self.curl)
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self.handle = self.session.loop.create_task(handle)
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self.handle.add_done_callback(self.on_done)
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await self.enter
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return StreamResponse(
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self.session._parse_response(self.curl, request, _, header_buffer),
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self.content,
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request
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)
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async def __aexit__(self, exc_type, exc, tb):
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await self.handle
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self.curl.clean_after_perform()
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self.curl.reset()
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self.session.push_curl(self.curl)
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