feat(agent): autoscale the worker count (throughput hill-climb), Auto default-on

The new per-job workload (3 detectors + several SigLIP embeds) is far more
GPU-bound than the old I/O-bound CCIP pass, so the right worker count shifted and
is hard to guess. Add an Auto mode (default ON) that finds it:

- _control_loop samples jobs/sec + GPU util/VRAM every ~6s and hill-climbs the
  target: grow while throughput keeps improving and VRAM stays under budget,
  revert a step that doesn't help, back off under memory pressure (VRAM >= 90%),
  then settle and periodically re-probe (the GPU/IO balance shifts over a run).
- A manual concurrency set is an override → leaves Auto; an "Auto" toggle in the
  control UI re-enables it. status() reports `auto`; the dial reflects the
  auto-chosen count (read-only) while Auto is on.
- AUTO_SCALE env (default on) + compose doc. Agent py-compiled (outside CI).

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

agent/fc_agent/config.py

@@ -18,6 +18,7 @@ class Config:
     #                            the server announces in the lease)
     auto_start: bool     # start the worker pool on boot (so a container restart
     #                      resumes processing without anyone clicking Start)
+    auto_scale: bool     # autoscale the worker count (throughput hill-climb)
     # Crop PROPOSERS (extra YOLO detectors that say where to crop). Each weight
     # spec is an ultralytics name | http(s) URL | "hf_repo::file" ("" = off).
     person_weights: str  # general COCO person detector (Western/realistic figs)
@@ -43,6 +44,7 @@ class Config:
             embed_dtype=os.environ.get("SIGLIP_DTYPE", "float16"),
             embed_model_override=os.environ.get("EMBED_MODEL_NAME", ""),
             auto_start=os.environ.get("AUTO_START", "").lower() in ("1", "true", "yes"),
+            auto_scale=os.environ.get("AUTO_SCALE", "true").lower() in ("1", "true", "yes"),
             person_weights=os.environ.get("PERSON_WEIGHTS", "yolo11n.pt"),
             person_conf=float(os.environ.get("PERSON_CONF", "0.35")),
             anatomy_weights=os.environ.get("ANATOMY_WEIGHTS", ""),