2023-09-26 01:52:29 +03:00
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from __future__ import annotations
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import random, json
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2023-10-23 00:53:18 +03:00
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from .. import debug
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2023-10-21 02:52:19 +03:00
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from ..typing import AsyncResult, Messages
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from ..requests import StreamSession
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2023-10-05 06:13:37 +03:00
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from .base_provider import AsyncGeneratorProvider, format_prompt, get_cookies
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2023-09-26 01:52:29 +03:00
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domains = {
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2023-10-05 06:13:37 +03:00
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"gpt-3.5-turbo": "aitianhu.space",
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"gpt-4": "aitianhu.website",
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2023-09-26 01:52:29 +03:00
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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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2023-10-21 02:52:19 +03:00
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async def create_async_generator(cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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domain: str = None,
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cookies: dict = None,
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timeout: int = 10, **kwargs) -> AsyncResult:
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2023-09-26 01:52:29 +03:00
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if not model:
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model = "gpt-3.5-turbo"
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2023-10-21 02:52:19 +03:00
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2023-09-26 01:52:29 +03:00
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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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2023-10-21 02:52:19 +03:00
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2023-10-05 06:13:37 +03:00
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if not domain:
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chars = 'abcdefghijklmnopqrstuvwxyz0123456789'
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rand = ''.join(random.choice(chars) for _ in range(6))
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domain = f"{rand}.{domains[model]}"
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2023-10-21 02:52:19 +03:00
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2023-10-23 00:53:18 +03:00
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if debug.logging:
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2023-10-21 02:52:19 +03:00
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print(f"AItianhuSpace | using domain: {domain}")
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2023-10-05 06:13:37 +03:00
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if not cookies:
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2023-10-21 02:52:19 +03:00
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cookies = get_cookies('.aitianhu.space')
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2023-10-16 02:47:10 +03:00
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if not cookies:
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2023-10-21 02:52:19 +03:00
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raise RuntimeError(f"g4f.provider.{cls.__name__} requires cookies [refresh https://{domain} on chrome]")
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2023-09-26 01:52:29 +03:00
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2023-10-05 06:13:37 +03:00
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url = f'https://{domain}'
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async with StreamSession(proxies={"https": proxy},
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cookies=cookies, timeout=timeout, impersonate="chrome110", verify=False) as session:
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2023-09-26 01:52:29 +03:00
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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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2023-10-01 07:38:11 +03:00
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headers = {
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"Authority": url,
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"Accept": "application/json, text/plain, */*",
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"Origin": url,
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"Referer": f"{url}/"
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}
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async with session.post(f"{url}/api/chat-process", json=data, headers=headers) as response:
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response.raise_for_status()
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2023-10-02 03:04:22 +03:00
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async for line in response.iter_lines():
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2023-10-04 08:20:51 +03:00
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if line == b"<script>":
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raise RuntimeError("Solve challenge and pass cookies and a fixed domain")
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2023-10-01 07:38:11 +03:00
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if b"platform's risk control" in line:
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raise RuntimeError("Platform's Risk Control")
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line = json.loads(line)
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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(f"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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