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from __future__ import annotations
import time
import hashlib
from ..typing import AsyncResult, Messages
from ..requests import StreamSession
from .base_provider import AsyncGeneratorProvider
class ChatForAi(AsyncGeneratorProvider):
url = "https://chatforai.store"
working = False
supports_gpt_35_turbo = True
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
timeout: int = 120,
**kwargs
) -> AsyncResult:
headers = {
"Content-Type": "text/plain;charset=UTF-8",
"Origin": cls.url,
"Referer": f"{cls.url}/?r=b",
}
async with StreamSession(impersonate="chrome107", headers=headers, proxies={"https": proxy}, timeout=timeout) as session:
prompt = messages[-1]["content"]
timestamp = int(time.time() * 1e3)
conversation_id = f"id_{timestamp-123}"
data = {
"conversationId": conversation_id,
"conversationType": "chat_continuous",
"botId": "chat_continuous",
"globalSettings":{
"baseUrl": "https://api.openai.com",
"model": model if model else "gpt-3.5-turbo",
"messageHistorySize": 5,
"temperature": 0.7,
"top_p": 1,
**kwargs
},
"botSettings": {},
"prompt": prompt,
"messages": messages,
"timestamp": timestamp,
"sign": generate_signature(timestamp, prompt, conversation_id)
}
async with session.post(f"{cls.url}/api/handle/provider-openai", json=data) as response:
response.raise_for_status()
async for chunk in response.iter_content():
if b"https://chatforai.store" in chunk:
raise RuntimeError(f"Response: {chunk.decode()}")
yield chunk.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})"
def generate_signature(timestamp: int, message: str, id: str):
buffer = f"{timestamp}:{id}:{message}:7YN8z6d6"
return hashlib.sha256(buffer.encode()).hexdigest()
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