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84 lines
2.9 KiB
Python
84 lines
2.9 KiB
Python
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, ProviderModelMixin
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from .helper import format_prompt
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class ChatifyAI(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://chatify-ai.vercel.app"
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api_endpoint = "https://chatify-ai.vercel.app/api/chat"
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working = True
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supports_stream = False
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supports_system_message = True
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supports_message_history = True
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default_model = 'llama-3.1'
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models = [default_model]
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model_aliases = {
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"llama-3.1-8b": "llama-3.1",
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}
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@classmethod
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def get_model(cls, model: str) -> str:
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if model in cls.models:
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return model
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elif model in cls.model_aliases:
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return cls.model_aliases.get(model, cls.default_model)
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else:
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return cls.default_model
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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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model = cls.get_model(model)
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"cache-control": "no-cache",
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"content-type": "application/json",
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"origin": cls.url,
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"pragma": "no-cache",
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"priority": "u=1, i",
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"referer": f"{cls.url}/",
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"sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Linux"',
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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 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36"
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}
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async with ClientSession(headers=headers) as session:
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data = {
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"messages": [{"role": "user", "content": format_prompt(messages)}]
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}
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async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
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response.raise_for_status()
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response_text = await response.text()
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# Фільтруємо та форматуємо відповідь
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filtered_response = cls.filter_response(response_text)
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yield filtered_response
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@staticmethod
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def filter_response(response_text: str) -> str:
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# Розділяємо рядок на частини
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parts = response_text.split('"')
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# Вибираємо лише текстові частини (кожна друга частина)
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text_parts = parts[1::2]
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# Об'єднуємо текстові частини
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clean_text = ''.join(text_parts)
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return clean_text
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