import os
import subprocess
import time
import uuid

from app.config import settings

_model = None


def _get_model():
    global _model
    if _model is None:
        from faster_whisper import WhisperModel
        _model = WhisperModel(
            settings.whisper_model,
            device=settings.whisper_device,
            compute_type=settings.whisper_compute_type,
        )
    return _model


def extract_audio(video_path: str) -> str:
    audio_path = os.path.join(
        settings.upload_dir, f"{uuid.uuid4().hex}.wav"
    )
    subprocess.run(
        [
            "ffmpeg", "-i", video_path,
            "-vn", "-acodec", "pcm_s16le",
            "-ar", "16000", "-ac", "1",
            audio_path, "-y",
        ],
        check=True,
        capture_output=True,
    )
    return audio_path


def transcribe_audio(audio_path: str) -> dict:
    model = _get_model()
    start_time = time.time()

    segments_iter, info = model.transcribe(
        audio_path,
        beam_size=5,
        language=None,
        vad_filter=True,
    )

    segments = []
    full_text_parts = []
    for segment in segments_iter:
        segments.append({
            "start": round(segment.start, 2),
            "end": round(segment.end, 2),
            "text": segment.text.strip(),
        })
        full_text_parts.append(segment.text.strip())

    processing_time = time.time() - start_time

    return {
        "text": " ".join(full_text_parts),
        "segments": segments,
        "language": info.language,
        "processing_time": round(processing_time, 2),
    }