from __future__ import annotations from aiohttp import ClientSession from ..typing import AsyncGenerator from .base_provider import AsyncGeneratorProvider class ChatBase(AsyncGeneratorProvider): url = "https://www.chatbase.co" supports_gpt_35_turbo = True supports_gpt_4 = True working = True @classmethod async def create_async_generator( cls, model: str, messages: list[dict[str, str]], **kwargs ) -> AsyncGenerator: if model == "gpt-4": chat_id = "quran---tafseer-saadi-pdf-wbgknt7zn" elif model == "gpt-3.5-turbo" or not model: chat_id = "chatbase--1--pdf-p680fxvnm" else: raise ValueError(f"Model are not supported: {model}") headers = { "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", "Accept" : "*/*", "Accept-language" : "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3", "Origin" : cls.url, "Referer" : cls.url + "/", "Sec-Fetch-Dest" : "empty", "Sec-Fetch-Mode" : "cors", "Sec-Fetch-Site" : "same-origin", } async with ClientSession( headers=headers ) as session: data = { "messages": messages, "captchaCode": "hadsa", "chatId": chat_id, "conversationId": f"kcXpqEnqUie3dnJlsRi_O-{chat_id}" } async with session.post("https://www.chatbase.co/api/fe/chat", json=data) as response: response.raise_for_status() async for stream in response.content.iter_any(): yield stream.decode() @classmethod @property def params(cls): params = [ ("model", "str"), ("messages", "list[dict[str, str]]"), ("stream", "bool"), ] param = ", ".join([": ".join(p) for p in params]) return f"g4f.provider.{cls.__name__} supports: ({param})"