worker.py

import whisper

def transcribe_video(video_path, model_size="tiny"):
    """
    Transcribe video into SRT file using OpenAI Whisper.
    """
    # Load model (tiny, base, or small)
    model = whisper.load_model(model_size)

    # Run transcription
    result = model.transcribe(video_path, language="English")

    # Save as .srt
    srt_path = video_path + ".srt"
    with open(srt_path, "w", encoding="utf-8") as f:
        for i, segment in enumerate(result["segments"], start=1):
            start = segment["start"]
            end = segment["end"]
            text = segment["text"].strip()

            def srt_time(seconds):
                ms = int((seconds % 1) * 1000)
                h = int(seconds // 3600)
                m = int((seconds % 3600) // 60)
                s = int(seconds % 60)
                return f"{h:02}:{m:02}:{s:02},{ms:03}"

            f.write(f"{i}\n{srt_time(start)} --> {srt_time(end)}\n{text}\n\n")

    return srt_path