"""image_prediction table + backfill from image_record.tagger_predictions

Normalizes the per-image tagger predictions out of the JSON blob into a
queryable table (#768). Backfills from the existing JSON in one set-based
INSERT…SELECT over json_each — fast because the #764 prune already shrank
each row to its >=0.70 entries. The old image_record.tagger_predictions
column is left in place here (vestigial) and dropped in a follow-up once the
code cutover is verified — dropping it needs an ACCESS EXCLUSIVE lock on the
hot image_record table (the 0044 lock class), so it's deferred to a
quiesced-worker window.

Revision ID: 0045
Revises: 0044
Create Date: 2026-06-10

"""
from typing import Sequence, Union

import sqlalchemy as sa
from alembic import op

revision: str = "0045"
down_revision: Union[str, None] = "0044"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None


def upgrade() -> None:
    op.create_table(
        "image_prediction",
        sa.Column("id", sa.Integer(), primary_key=True),
        sa.Column(
            "image_record_id", sa.Integer(),
            sa.ForeignKey("image_record.id", ondelete="CASCADE"),
            nullable=False,
        ),
        sa.Column("raw_name", sa.String(length=255), nullable=False),
        sa.Column("category", sa.String(length=64), nullable=False),
        sa.Column("score", sa.Float(), nullable=False),
        sa.UniqueConstraint(
            "image_record_id", "raw_name", name="image_raw_name",
        ),
    )
    op.create_index(
        "ix_image_prediction_image", "image_prediction", ["image_record_id"],
    )
    op.create_index(
        "ix_image_prediction_name_score", "image_prediction",
        ["raw_name", "score"],
    )
    # Backfill from the JSON blob. json_each expands {name: {category,
    # confidence}} into one row per prediction. category defaults to 'general'
    # to mirror the suggestion read path; rows with no confidence are skipped.
    op.execute(
        """
        INSERT INTO image_prediction (image_record_id, raw_name, category, score)
        SELECT ir.id,
               je.key,
               COALESCE(je.value ->> 'category', 'general'),
               (je.value ->> 'confidence')::double precision
        FROM image_record ir,
             json_each(ir.tagger_predictions) je
        WHERE ir.tagger_predictions IS NOT NULL
          AND je.value ->> 'confidence' IS NOT NULL
        ON CONFLICT (image_record_id, raw_name) DO NOTHING
        """
    )


def downgrade() -> None:
    op.drop_index("ix_image_prediction_name_score", "image_prediction")
    op.drop_index("ix_image_prediction_image", "image_prediction")
    op.drop_table("image_prediction")