mirror of
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62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
import uuid, requests
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from ..typing import Any, CreateResult
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from .base_provider import BaseProvider
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class V50(BaseProvider):
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url = 'https://p5.v50.ltd'
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supports_gpt_35_turbo = True
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supports_stream = False
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needs_auth = False
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working = True
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@staticmethod
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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,
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**kwargs: Any,
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) -> CreateResult:
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conversation = ''
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for message in messages:
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conversation += '%s: %s\n' % (message['role'], message['content'])
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conversation += 'assistant: '
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payload = {
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"prompt": conversation,
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"options": {},
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"systemMessage": ".",
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"temperature": kwargs.get("temperature", 0.4),
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"top_p": kwargs.get("top_p", 0.4),
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"model": model,
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"user": str(uuid.uuid4())
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}
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headers = {
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'authority': 'p5.v50.ltd',
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'accept': 'application/json, text/plain, */*',
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'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
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'content-type': 'application/json',
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'origin': 'https://p5.v50.ltd',
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'referer': 'https://p5.v50.ltd/',
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'sec-ch-ua-platform': '"Windows"',
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'sec-fetch-dest': 'empty',
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'sec-fetch-mode': 'cors',
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'sec-fetch-site': 'same-origin',
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'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36'
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}
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response = requests.post("https://p5.v50.ltd/api/chat-process",
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json=payload, headers=headers, proxies=kwargs['proxy'] if 'proxy' in kwargs else {})
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yield response.text
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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})" |