services/whisper/utils/batch_queue.py

import threading
from queue import Queue
import uuid
import time

from .job_queue import jobs, update, notify_webhook
from .transcription import transcribe_video
from .render import render_video
from .highlights import detect_highlights


batch_queue = Queue()


def create_batch_job(video_path, webhook=None):

    job_id = str(uuid.uuid4())

    jobs[job_id] = {
        "id": job_id,
        "status": "queued",
        "progress": 0,
        "clips": [],
        "video": video_path,
        "webhook": webhook,
    }

    batch_queue.put(job_id)

    return job_id


def worker():

    while True:

        job_id = batch_queue.get()
        job = jobs[job_id]

        try:

            update(job_id, status="processing", progress=5)

            # 1. TRANSCRIBE
            words = transcribe_video(job["video"])

            update(job_id, progress=30)

            # 2. DETECT HIGHLIGHTS
            highlights = detect_highlights(words)

            update(job_id, progress=50)

            outputs = []

            # 3. RENDER MULTIPLE CLIPS
            for i, segment in enumerate(highlights):

                start = segment[0]["start"]
                end = segment[-1]["end"]

                clip_path = render_video(job["video"], words)

                outputs.append(clip_path)

                update(job_id, progress=50 + int((i+1)/len(highlights)*40))

            # 4. FINALIZE
            update(job_id,
                   status="completed",
                   progress=100,
                   clips=outputs)

            notify_webhook(job_id)

        except Exception as e:

            update(job_id,
                   status="failed",
                   error=str(e))

            notify_webhook(job_id)

        batch_queue.task_done()


def start_batch_worker():

    t = threading.Thread(target=worker, daemon=True)
    t.start()