bvandeusen
6959e1220c
This reverts 2529b51. Not a retreat — a reordering, on the operator's
call, and the better sequence.
The squash's acceptance test (run 4971) found ~130 places where the ORM
models do not describe the deployed schema (#3275), including a
unique=True the database never had and two UNIQUE indexes that exist
only in migrations. Collapsing now would have baked all of that into the
one file a public installer starts from.
So: fix the drift first as ordinary migrations on the intact chain, let
the operator deploy so their database moves to the corrected head, and
only then collapse. The baseline is then generated from reconciled
models and reproduces a schema worth reproducing.
Nothing is lost by reverting. The baseline was never deployed, and
regenerating it after the fixes is strictly better than patching this
copy — it will come out of autogenerate correct rather than needing the
same hand-finishing twice.
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
"""drop the dead per-tag centroid subsystem (#1189 cleanup)
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The v2 pivot replaced per-tag SigLIP centroids with learned heads + CCIP.
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Nothing read the centroids anymore — they were recomputed (on merge + a daily
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beat) but never consumed for suggestions or auto-apply. Remove the storage +
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its two now-unused settings columns. (The recompute tasks, beat, endpoint,
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service, and UI card are removed in the same change.)
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Revision ID: 0066
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Revises: 0065
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Create Date: 2026-06-30
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"""
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from typing import Sequence, Union
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import sqlalchemy as sa
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from alembic import op
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revision: str = "0066"
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down_revision: Union[str, None] = "0065"
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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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op.drop_table("tag_reference_embedding")
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op.drop_column("ml_settings", "centroid_similarity_threshold")
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op.drop_column("ml_settings", "min_reference_images")
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def downgrade() -> None:
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op.add_column(
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"ml_settings",
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sa.Column(
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"min_reference_images", sa.Integer(), nullable=False,
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server_default="5",
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),
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)
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op.add_column(
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"ml_settings",
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sa.Column(
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"centroid_similarity_threshold", sa.Float(), nullable=False,
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server_default="0.55",
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),
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)
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op.create_table(
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"tag_reference_embedding",
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sa.Column("tag_id", sa.Integer(), nullable=False),
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sa.Column("embedding", sa.LargeBinary(), nullable=False),
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sa.Column("reference_count", sa.Integer(), nullable=False),
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sa.Column("model_version", sa.String(length=128), nullable=False),
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sa.Column(
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"updated_at", sa.DateTime(timezone=True),
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server_default=sa.func.now(), nullable=False,
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),
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sa.ForeignKeyConstraint(["tag_id"], ["tag.id"], ondelete="CASCADE"),
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sa.PrimaryKeyConstraint("tag_id"),
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)
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