from __future__ import annotations import time from hashlib import sha256 from aiohttp import ClientSession from ..typing import AsyncResult, Messages from .base_provider import AsyncGeneratorProvider class GeminiProChat(AsyncGeneratorProvider): url = "https://gemini-chatbot-sigma.vercel.app" working = True supports_gpt_35_turbo = True @classmethod async def create_async_generator( cls, model: str, messages: Messages, proxy: str = None, **kwargs ) -> AsyncResult: headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:122.0) Gecko/20100101 Firefox/122.0", "Accept": "*/*", "Accept-Language": "en-US,en;q=0.5", "Accept-Encoding": "gzip, deflate, br", "Content-Type": "text/plain;charset=UTF-8", "Referer": "https://gemini-chatbot-sigma.vercel.app/", "Origin": "https://gemini-chatbot-sigma.vercel.app", "Sec-Fetch-Dest": "empty", "Sec-Fetch-Mode": "cors", "Sec-Fetch-Site": "same-origin", "Connection": "keep-alive", "TE": "trailers", } async with ClientSession(headers=headers) as session: timestamp = int(time.time() * 1e3) data = { "messages":[{ "role": "model" if message["role"] == "assistant" else "user", "parts": [{"text": message["content"]}] } for message in messages], "time": timestamp, "pass": None, "sign": generate_signature(timestamp, messages[-1]["content"]), } async with session.post(f"{cls.url}/api/generate", json=data, proxy=proxy) as response: response.raise_for_status() async for chunk in response.content.iter_any(): yield chunk.decode() def generate_signature(time: int, text: str, secret: str = ""): message = f'{time}:{text}:{secret}'; return sha256(message.encode()).hexdigest()