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from __future__ import annotations |
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from aiohttp import ClientSession |
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from ...typing import AsyncResult, Messages |
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from ..base_provider import AsyncGeneratorProvider |
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class AiAsk(AsyncGeneratorProvider): |
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url = "https://e.aiask.me" |
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supports_message_history = True |
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supports_gpt_35_turbo = True |
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working = False |
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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: Messages, |
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proxy: str = None, |
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**kwargs |
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) -> AsyncResult: |
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headers = { |
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"accept": "application/json, text/plain, */*", |
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"origin": cls.url, |
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"referer": f"{cls.url}/chat", |
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} |
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async with ClientSession(headers=headers) as session: |
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data = { |
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"continuous": True, |
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"id": "fRMSQtuHl91A4De9cCvKD", |
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"list": messages, |
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"models": "0", |
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"prompt": "", |
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"temperature": kwargs.get("temperature", 0.5), |
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"title": "", |
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} |
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buffer = "" |
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rate_limit = "您的免费额度不够使用这个模型啦,请点击右上角登录继续使用!" |
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async with session.post(f"{cls.url}/v1/chat/gpt/", json=data, proxy=proxy) as response: |
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response.raise_for_status() |
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async for chunk in response.content.iter_any(): |
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buffer += chunk.decode() |
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if not rate_limit.startswith(buffer): |
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yield buffer |
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buffer = "" |
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elif buffer == rate_limit: |
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raise RuntimeError("Rate limit reached") |