gpt4free/g4f/Provider/GeminiProChat.py

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from __future__ import annotations
import time
from hashlib import sha256
from aiohttp import ClientSession, BaseConnector
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider
from ..errors import RateLimitError
from ..requests import raise_for_status
from ..requests.aiohttp import get_connector
class GeminiProChat(AsyncGeneratorProvider):
url = "https://gemini-chatbot-sigma.vercel.app"
working = True
supports_message_history = True
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
connector: BaseConnector = 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(connector=get_connector(connector, proxy), 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:
if response.status == 500:
if "Quota exceeded" in await response.text():
raise RateLimitError(f"Response {response.status}: Rate limit reached")
await raise_for_status(response)
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()