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- from __future__ import annotations
- import secrets
- import uuid
- import json
- from aiohttp import ClientSession
- from ...typing import AsyncResult, Messages
- from ..base_provider import AsyncGeneratorProvider
- from ..helper import format_prompt
- class Berlin(AsyncGeneratorProvider):
- url = "https://ai.berlin4h.top"
- working = False
- supports_gpt_35_turbo = True
- _token = None
- @classmethod
- async def create_async_generator(
- cls,
- model: str,
- messages: Messages,
- proxy: str = None,
- **kwargs
- ) -> AsyncResult:
- if not model:
- model = "gpt-3.5-turbo"
- headers = {
- "User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/119.0",
- "Accept": "*/*",
- "Accept-Language": "de,en-US;q=0.7,en;q=0.3",
- "Accept-Encoding": "gzip, deflate, br",
- "Referer": f"{cls.url}/",
- "Content-Type": "application/json",
- "Origin": cls.url,
- "Alt-Used": "ai.berlin4h.top",
- "Connection": "keep-alive",
- "Sec-Fetch-Dest": "empty",
- "Sec-Fetch-Mode": "cors",
- "Sec-Fetch-Site": "same-origin",
- "Pragma": "no-cache",
- "Cache-Control": "no-cache",
- "TE": "trailers",
- }
- async with ClientSession(headers=headers) as session:
- if not cls._token:
- data = {
- "account": '免费使用GPT3.5模型@163.com',
- "password": '659e945c2d004686bad1a75b708c962f'
- }
- async with session.post(f"{cls.url}/api/login", json=data, proxy=proxy) as response:
- response.raise_for_status()
- cls._token = (await response.json())["data"]["token"]
- headers = {
- "token": cls._token
- }
- prompt = format_prompt(messages)
- data = {
- "prompt": prompt,
- "parentMessageId": str(uuid.uuid4()),
- "options": {
- "model": model,
- "temperature": 0,
- "presence_penalty": 0,
- "frequency_penalty": 0,
- "max_tokens": 1888,
- **kwargs
- },
- }
- async with session.post(f"{cls.url}/api/chat/completions", json=data, proxy=proxy, headers=headers) as response:
- response.raise_for_status()
- async for chunk in response.content:
- if chunk.strip():
- try:
- yield json.loads(chunk)["content"]
- except:
- raise RuntimeError(f"Response: {chunk.decode()}")
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