gpt4free/g4f/Provider/ChatifyAI.py
2024-10-15 21:07:41 +03:00

80 lines
2.5 KiB
Python

from __future__ import annotations
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import format_prompt
class ChatifyAI(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://chatify-ai.vercel.app"
api_endpoint = "https://chatify-ai.vercel.app/api/chat"
working = True
supports_stream = False
supports_system_message = True
supports_message_history = True
default_model = 'llama-3.1'
models = [default_model]
model_aliases = {
"llama-3.1-8b": "llama-3.1",
}
@classmethod
def get_model(cls, model: str) -> str:
if model in cls.models:
return model
elif model in cls.model_aliases:
return cls.model_aliases.get(model, cls.default_model)
else:
return cls.default_model
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"cache-control": "no-cache",
"content-type": "application/json",
"origin": cls.url,
"pragma": "no-cache",
"priority": "u=1, i",
"referer": f"{cls.url}/",
"sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Linux"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36"
}
async with ClientSession(headers=headers) as session:
data = {
"messages": [{"role": "user", "content": format_prompt(messages)}]
}
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
response_text = await response.text()
filtered_response = cls.filter_response(response_text)
yield filtered_response
@staticmethod
def filter_response(response_text: str) -> str:
parts = response_text.split('"')
text_parts = parts[1::2]
clean_text = ''.join(text_parts)
return clean_text