bc7ac32de3
- Campaigns: new table, CRUD API, React context + provider
- Sessions: scoped to campaigns, paths under campaigns/{id}/
- File browser: scoped per campaign, removed copy/paste/autoPlay
- Sidebar: campaign selector dropdown at top
- Transcribe: GPU model cached/released via job counter
- Jobs: status text updates dynamically in real-time
- Auto-redirect: blocked when summarize job is active
68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
"""
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Minimal background job runner.
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GPU jobs use a shared counter so the Whisper model stays cached between
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back-to-back transcriptions and is only released when no more GPU work
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is queued.
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"""
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import threading
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import traceback
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from concurrent.futures import ThreadPoolExecutor
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from . import database as db
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from .errors import PipelineError
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from .logging_config import get_logger
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log = get_logger(__name__)
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_executor = ThreadPoolExecutor(max_workers=1)
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_gpu_jobs_queued = 0
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_gpu_lock = threading.Lock()
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def _unload_gpu():
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"""Release the cached Whisper model from GPU memory."""
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from .pipeline.transcribe import unload_models
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unload_models()
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def submit(job_id: str, fn, *args, requires_gpu=False, **kwargs):
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if requires_gpu:
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with _gpu_lock:
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global _gpu_jobs_queued
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_gpu_jobs_queued += 1
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def _run():
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log.info("Job %s starting", job_id)
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db.update_job(job_id, status="running", progress="Starting...")
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try:
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def progress_cb(msg):
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log.info("Job %s: %s", job_id, msg)
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db.update_job(job_id, progress=msg)
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fn(*args, progress_cb=progress_cb, **kwargs)
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db.update_job(job_id, status="done", progress="Complete")
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log.info("Job %s complete", job_id)
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except PipelineError as e:
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log.error("Job %s failed at stage '%s': %s", job_id, e.stage, e.message)
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db.update_job(
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job_id, status="error",
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error=e.message, error_stage=e.stage,
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error_detail=traceback.format_exc(),
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)
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except Exception as e:
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log.exception("Job %s failed with unexpected error", job_id)
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db.update_job(
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job_id, status="error",
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error=f"Unexpected error: {e}", error_stage="unknown",
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error_detail=traceback.format_exc(),
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)
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finally:
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if requires_gpu:
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with _gpu_lock:
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global _gpu_jobs_queued
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_gpu_jobs_queued -= 1
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if _gpu_jobs_queued <= 0:
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log.info("No more GPU jobs queued — unloading Whisper model")
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_unload_gpu()
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_executor.submit(_run)
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