import asyncio
import tempfile
from pathlib import Path

import aiohttp
from speechkit import configure_credentials, creds, model_repository
from speechkit.stt import AudioProcessingType

from config import YSK_API_KEY, create_aiohttp_session, get_aiohttp_request_kwargs

if YSK_API_KEY:
    configure_credentials(
        yandex_credentials=creds.YandexCredentials(api_key=YSK_API_KEY)
    )


def _transcribe_file_sync(file_path: str) -> str | None:
    model = model_repository.recognition_model()
    model.model = "general"
    model.language = "ru-RU"
    model.audio_processing_type = AudioProcessingType.Full

    result = model.transcribe_file(file_path)
    for res in result:
        normalized_text = getattr(res, "normalized_text", None)
        if normalized_text:
            return normalized_text
    return None


async def get_text_from_speech(file_url: str) -> str | None:
    temp_path = None
    timeout = aiohttp.ClientTimeout(total=300, sock_connect=30, sock_read=300)

    try:
        async with create_aiohttp_session(timeout=timeout) as session:
            async with session.get(file_url, **get_aiohttp_request_kwargs()) as response:
                response.raise_for_status()
                content = await response.read()

        with tempfile.NamedTemporaryFile(delete=False, suffix=".ogg") as temp_file:
            temp_file.write(content)
            temp_path = temp_file.name

        return await asyncio.to_thread(_transcribe_file_sync, temp_path)
    finally:
        if temp_path:
            try:
                Path(temp_path).unlink(missing_ok=True)
            except Exception:
                pass


def synthesize(text: str) -> str:
    model = model_repository.synthesis_model()
    model.voice = "lera"
    result = model.synthesize(text, raw_format=False)

    with tempfile.NamedTemporaryFile(delete=False, suffix=".ogg") as temp_file:
        output_path = temp_file.name

    result.export(output_path, "ogg")
    return output_path