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>
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"""add cad_metadata to products
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Revision ID: a68e8c6fb61b
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Revises: 69964e910545
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Create Date: 2026-03-15 17:44:08.184376
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"""
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from typing import Sequence, Union
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from alembic import op
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import sqlalchemy as sa
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from sqlalchemy.dialects import postgresql
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# revision identifiers, used by Alembic.
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revision: str = 'a68e8c6fb61b'
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down_revision: Union[str, None] = '69964e910545'
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branch_labels: Union[str, Sequence[str], None] = None
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depends_on: Union[str, Sequence[str], None] = None
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def upgrade() -> None:
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# ### commands auto generated by Alembic - please adjust! ###
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op.add_column('products', sa.Column('cad_metadata', postgresql.JSONB(astext_type=sa.Text()), nullable=True))
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# ### end Alembic commands ###
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def downgrade() -> None:
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# ### commands auto generated by Alembic - please adjust! ###
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op.drop_column('products', 'cad_metadata')
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# ### end Alembic commands ###
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