feat: rich product metadata extraction from STEP files

Extract volume, surface area, part count, assembly hierarchy, and
complexity from STEP files via OCC B-rep analysis.

Backend:
- extract_rich_metadata() in step_processor.py: computes per-part volume
  (BRepGProp), surface area, triangle/vertex count, assembly depth,
  instance count, complexity score, largest part identification
- cad_metadata JSONB column on Product model (DB migration)
- Auto-populated during STEP processing (non-fatal, 10s timeout)
- Also stored in cad_files.mesh_attributes["rich_metadata"]
- Batch re-extract endpoint: POST /admin/settings/reextract-rich-metadata

AI Agent:
- search_products returns part_count, volume_cm3, complexity, largest_part
- query_database tool description documents cad_metadata schema

Frontend:
- ProductDetail page: CAD Metadata section with stat cards
  (parts, volume, surface area, complexity, triangles, assembly depth)
- Admin System Tools: "Re-extract Rich Metadata" button for backfill

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/app/tasks/step_tasks.py

@@ -8,6 +8,7 @@ Celery discovers tasks by import path, so these re-exports are required.
 from app.domains.pipeline.tasks.extract_metadata import (  # noqa: F401
     process_step_file,
     reextract_cad_metadata,
+    reextract_rich_metadata_task,
 )
 from app.domains.pipeline.tasks.render_thumbnail import (  # noqa: F401
     render_step_thumbnail,