"""Speech-to-text service using faster-whisper (in-process, CPU/GPU)."""
import asyncio
import logging
import tempfile
import time
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from faster_whisper import WhisperModel

logger = logging.getLogger(__name__)

_model: "WhisperModel | None" = None
_model_lock = asyncio.Lock()
_load_error: str | None = None


async def load_stt_model() -> None:
    """Load the Whisper model. Called once at startup when VOICE_ENABLED=true."""
    global _model, _load_error
    from fabledassistant.config import Config

    if not Config.VOICE_ENABLED:
        return

    async with _model_lock:
        if _model is not None:
            return
        try:
            from faster_whisper import WhisperModel

            logger.info("Loading Whisper STT model '%s'...", Config.STT_MODEL)
            loop = asyncio.get_running_loop()
            _model = await loop.run_in_executor(
                None,
                lambda: WhisperModel(Config.STT_MODEL, device="cpu", compute_type="int8"),
            )
            logger.info("Whisper STT model '%s' loaded", Config.STT_MODEL)
        except Exception:
            _load_error = f"Failed to load Whisper model '{Config.STT_MODEL}'"
            logger.exception(_load_error)


def stt_available() -> bool:
    return _model is not None


async def transcribe(audio_bytes: bytes, mime_type: str = "audio/webm") -> str:
    """Transcribe audio bytes to text. Runs the model in a thread executor."""
    if _model is None:
        raise RuntimeError("STT model not loaded")

    suffix = ".webm"
    if "ogg" in mime_type:
        suffix = ".ogg"
    elif "wav" in mime_type:
        suffix = ".wav"
    elif "mp4" in mime_type or "m4a" in mime_type:
        suffix = ".mp4"

    def _run() -> str:
        with tempfile.NamedTemporaryFile(suffix=suffix, delete=True) as f:
            f.write(audio_bytes)
            f.flush()
            t0 = time.monotonic()
            segments, _ = _model.transcribe(f.name, beam_size=5)  # type: ignore[union-attr]
            text = " ".join(seg.text.strip() for seg in segments).strip()
            logger.debug("STT transcription took %.2fs", time.monotonic() - t0)
            return text

    loop = asyncio.get_running_loop()
    return await loop.run_in_executor(None, _run)