feat(b3): ml-worker becomes optional — embed-only role, decoupled GPU coordination, cpu-embed switch

The ml-worker's ONLY processing role is now the CPU whole-image embed fallback
(tag_and_embed renamed embed_image — Camie tagging was retired #1189 and the
name kept implying otherwise; videos were already handled agent-style: frame
sampling + mean-pool). Detection/cropping/CCIP stay GPU-agent-only, and their
completion is judged per-pipeline: ccip by gpu_job rows, siglip by concept
regions at the current model version — never by image_record.siglip_embedding.
A CPU embed therefore can NEVER close crop work for the agent (regression test
pins this; only the whole-image 'embed' job, the same artifact, is satisfied).

Making removal actually safe (operator will drop the container):
- GPU-queue coordination (enqueue_gpu_backfill, recover_orphaned_gpu_jobs,
  reprocess_gpu_jobs) moved verbatim to tasks/gpu_queue.py on the maintenance
  quick lane — it lived on the 'ml' queue only by module colocation, which made
  the ml-worker a hard dependency of the whole agent pipeline.
- New ml_settings.cpu_embed_enabled (migration 0074, default ON so agent-less
  installs keep working): OFF stops the four import hooks queueing embed work
  nothing will consume and no-ops the manual backfill; switch lives on the
  renamed 'CPU embedding backfill' card.
- NB heads training / auto-apply still run on the ml image (sklearn) — a stack
  that removes the container gives those up too.

Deploy note: in-flight messages under the old task names are dropped by the
new workers; the 60s orphan sweep + hourly backfill re-fire under the new
names immediately.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM

backend/app/tasks/external.py

@@ -216,11 +216,13 @@ def fetch_external_link(self, link_id: int, _serialize_waits: int = 0) -> dict:
         # Thumbnails + ML for any newly-attached images (mirrors the download
         # path). Lazy import to dodge a task-module import cycle.
         if image_ids:
-            from .ml import tag_and_embed
+            from .ml import cpu_embed_enabled, embed_image
             from .thumbnail import generate_thumbnail
+            do_embed = cpu_embed_enabled()
             for img_id in image_ids:
                 generate_thumbnail.delay(img_id)
-                tag_and_embed.delay(img_id)
+                if do_embed:
+                    embed_image.delay(img_id)
         return {"link_id": link_id, "files": len(result.files), "images": len(image_ids)}
     except Exception as exc:  # never leave a link stuck in 'downloading'
         log.exception("external fetch task failed for link %s", link_id)