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