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/models/__init__.py

@@ -8,6 +8,7 @@ from .base import Base
 from .credential import Credential
 from .download_event import DownloadEvent
 from .external_link import ExternalLink
+from .gpu_job import GpuJob
 from .head_auto_apply_run import HeadAutoApplyRun
 from .head_metric import HeadMetric
 from .head_metrics_snapshot import HeadMetricsSnapshot
@@ -67,6 +68,7 @@ __all__ = [
     "image_tag",
     "DownloadEvent",
     "ExternalLink",
+    "GpuJob",
     "ImportBatch",
     "ImportTask",
     "ImportSettings",