feat(gpu): video-ready regions + the HTTP GPU-job queue engine (#114 slice 3)

Answers "how are videos/all media handled by the GPU worker": a job is per ITEM,
but the agent fans a VIDEO into per-frame instances (ffmpeg in the agent, the
existing cadence), each stored with a timestamp — so a video becomes a BAG of
frame embeddings (fixes the mean-embedding muddle) instead of one washed-out
vector. Stills → frame_time NULL; animated GIF/WebP treated like short video.

- image_region.frame_time (migration 0061, not yet deployed so folded in): the
  source frame's seconds for video/animated media; NULL for stills. RegionService
  passes it through. A whole frame is just kind='frame'.
- gpu_job + GpuJobService (migration 0062): the durable work list that keeps the
  desktop agent HTTP-only — enqueue (dedupes (image,task)) / lease (FOR UPDATE
  SKIP LOCKED, re-claims expired leases so the queue self-heals) / heartbeat /
  complete / fail (re-queues until MAX_ATTEMPTS then 'error'). The server enqueues;
  the agent leases+submits over the web API; Redis/Postgres stay private.

Tests: enqueue dedupe, lease-then-skip-when-held, expired-lease reclaim, scoped
heartbeat, complete, fail-requeue-then-error. region test now covers frame_time.

NEXT: the thin HTTP API (lease/submit/heartbeat) + bearer-token auth, then the
agent container + control UI.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa

backend/app/services/ml/regions.py

@@ -46,6 +46,7 @@ class RegionService:
             rx, ry, rw, rh = r["bbox"]
             self.session.add(ImageRegion(
                 image_record_id=image_id, kind=r["kind"],
+                frame_time=r.get("frame_time"),
                 rx=rx, ry=ry, rw=rw, rh=rh,
                 score=r.get("score"),
                 detector_version=r.get("detector_version"),