mirror of
https://github.com/R0m1k3/Priceflow.git
synced 2026-10-19 21:28:26 +02:00
56 lines
2.0 KiB
Python
56 lines
2.0 KiB
Python
"""Add confidence and AI metadata
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Revision ID: a1b2c3d4e5f6
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Revises: 6ecb6f39fd8c
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Create Date: 2025-11-19 13:55:00.000000
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"""
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from collections.abc import Sequence
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import sqlalchemy as sa
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from alembic import op
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from app.models import Base
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target_metadata = Base.metadata
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# revision identifiers, used by Alembic.
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revision: str = "a1b2c3d4e5f6"
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down_revision: str | None = "6ecb6f39fd8c"
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branch_labels: str | Sequence[str] | None = None
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depends_on: str | Sequence[str] | None = None
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def upgrade() -> None:
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"""Add confidence scores and AI metadata to price_history and items tables."""
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# Add columns to price_history table
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op.add_column("price_history", sa.Column("price_confidence", sa.Float(), nullable=True))
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op.add_column("price_history", sa.Column("in_stock_confidence", sa.Float(), nullable=True))
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op.add_column("price_history", sa.Column("ai_model", sa.String(), nullable=True))
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op.add_column("price_history", sa.Column("ai_provider", sa.String(), nullable=True))
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op.add_column("price_history", sa.Column("prompt_version", sa.String(), nullable=True))
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op.add_column("price_history", sa.Column("repair_used", sa.Boolean(), nullable=True, server_default="false"))
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# Add columns to items table for quick access to latest confidence
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op.add_column("items", sa.Column("current_price_confidence", sa.Float(), nullable=True))
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op.add_column("items", sa.Column("in_stock_confidence", sa.Float(), nullable=True))
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def downgrade() -> None:
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"""Remove confidence scores and AI metadata columns."""
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# Remove columns from items table
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op.drop_column("items", "in_stock_confidence")
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op.drop_column("items", "current_price_confidence")
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# Remove columns from price_history table
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op.drop_column("price_history", "repair_used")
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op.drop_column("price_history", "prompt_version")
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op.drop_column("price_history", "ai_provider")
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op.drop_column("price_history", "ai_model")
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op.drop_column("price_history", "in_stock_confidence")
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op.drop_column("price_history", "price_confidence")
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