feat(tagging): SigLIP concept crops + max-over-bag scoring (#114)

Lift recall on small/local concepts (glasses, cum, stomach-bulge, xray,
lactation) that the whole-image SigLIP vector washes out: the GPU agent now
embeds figure crops with SigLIP too, stored as kind='concept' regions, and the
suggestion rail scores each image as a BAG (whole-image + every concept crop),
taking each head's MAX over the bag. The whole-image vector is always in the
bag, so this can never score lower than before.

Model-agnostic by construction: the server ANNOUNCES the embedding model
(HF name + version) in the lease, so the agent loads whatever the heads were
trained in and stays in lock-step — a model swap is a server setting + a
re-embed migration, never an agent change.

- agent: model-agnostic CropEmbedder (torch/transformers get_image_features,
  fp16 on CUDA, inference-locked); worker branches on job.task — 'ccip' emits
  figure(CCIP)+concept(SigLIP) in one pass, 'siglip' emits concept-only so the
  back-catalogue backfill never churns figure/CCIP regions; torch cu124 +
  transformers in the image.
- server: lease announces embed_model_name/embed_version; score_image is
  max-over-bag (version-filtered region embeddings); enqueue_gpu_backfill
  'siglip' gates on a missing concept region (drains the back-catalogue,
  retries failures, no double-enqueue); daily siglip-backfill beat; UI button;
  /api/ccip/overview reports images_with_concept_siglip.
- v1 scope: suggestion rail only — auto-apply stays whole-image (conservative;
  heads' thresholds were calibrated on whole-image). Bulk-apply bag = follow-up.

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

agent/fc_agent/config.py

@@ -13,6 +13,9 @@ class Config:
     ccip_model: str      # imgutils CCIP model name ("" → imgutils default)
     detector_level: str  # imgutils person-detector level: n|s|m|x
     poll_idle_seconds: float   # wait between empty leases
+    embed_dtype: str     # torch dtype for the crop embedder: float16|float32
+    embed_model_override: str  # force a SigLIP-family model ("" → use the one
+    #                            the server announces in the lease)
 
     @classmethod
     def from_env(cls) -> "Config":
@@ -25,4 +28,6 @@ class Config:
             ccip_model=os.environ.get("CCIP_MODEL", ""),
             detector_level=os.environ.get("DETECTOR_LEVEL", "m"),
             poll_idle_seconds=float(os.environ.get("POLL_IDLE_SECONDS", "10")),
+            embed_dtype=os.environ.get("SIGLIP_DTYPE", "float16"),
+            embed_model_override=os.environ.get("EMBED_MODEL_NAME", ""),
         )