bvandeusen
3610ba495f
Read cutover verified in prod (suggestions + allowlist read image_prediction; backfill complete at 908k rows / 51k images). Removes the old JSON column and everything that fed it: - ImageRecord.tagger_predictions column removed; migration 0046 DROPs it. tagger_model_version kept as the "tagged / current?" signal the backfill sweep reads (needs-tagging check switched to tagger_model_version IS NULL). - tag_and_embed no longer dual-writes the JSON — image_prediction is the only write path. - importer re-import reset drops the JSON line (image_prediction rows are already deleted on re-import). - Retired the one-time #768 backfill task + the #764 prune task, their admin endpoints, and their Maintenance cards (Backfill/PrunePredictionsCard). - Tests seed/assert via image_prediction; stale column refs removed. Disk reclaim is NOT automatic: DROP COLUMN is a catalog change. Run `VACUUM FULL image_record` off-hours afterward to return the ~100 GB to the OS so DB backups go small (#739). image_prediction (~90 MB) stays in pg_dump — it's the source of truth now. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
105 lines
3.3 KiB
Python
105 lines
3.3 KiB
Python
"""Alias resolution + CRUD.
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A tag_alias maps (model_name, model_category) -> canonical Tag. Resolution
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happens at suggestion-read time so the raw image_prediction rows stay unmolested.
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"""
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from collections.abc import Sequence
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from dataclasses import dataclass
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from sqlalchemy import delete, select
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from sqlalchemy.dialects.postgresql import insert
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from sqlalchemy.ext.asyncio import AsyncSession
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from ...models import Tag, TagAlias
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@dataclass(frozen=True)
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class AliasRow:
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alias_string: str
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alias_category: str
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canonical_tag_id: int
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canonical_tag_name: str
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class AliasService:
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def __init__(self, session: AsyncSession):
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self.session = session
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async def resolve(self, name: str, category: str) -> Tag | None:
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"""Return the canonical Tag for (name, category), or None if no alias."""
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stmt = (
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select(Tag)
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.join(TagAlias, TagAlias.canonical_tag_id == Tag.id)
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.where(TagAlias.alias_string == name)
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.where(TagAlias.alias_category == category)
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)
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return (await self.session.execute(stmt)).scalar_one_or_none()
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async def resolve_many(
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self, pairs: list[tuple[str, str]]
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) -> dict[tuple[str, str], Tag]:
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"""Batch-resolve. Returns only the pairs that have an alias.
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Used by SuggestionService so it does one query instead of N.
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"""
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if not pairs:
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return {}
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strings = {p[0] for p in pairs}
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stmt = (
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select(TagAlias, Tag)
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.join(Tag, Tag.id == TagAlias.canonical_tag_id)
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.where(TagAlias.alias_string.in_(strings))
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)
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rows = (await self.session.execute(stmt)).all()
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wanted = set(pairs)
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out: dict[tuple[str, str], Tag] = {}
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for alias, tag in rows:
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key = (alias.alias_string, alias.alias_category)
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if key in wanted:
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out[key] = tag
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return out
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async def create(
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self, alias_string: str, alias_category: str, canonical_tag_id: int
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) -> None:
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"""Idempotent create (ON CONFLICT DO NOTHING)."""
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stmt = insert(TagAlias).values(
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alias_string=alias_string,
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alias_category=alias_category,
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canonical_tag_id=canonical_tag_id,
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)
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stmt = stmt.on_conflict_do_nothing(
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index_elements=["alias_string", "alias_category"]
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)
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await self.session.execute(stmt)
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async def remove(self, alias_string: str, alias_category: str) -> None:
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await self.session.execute(
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delete(TagAlias)
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.where(TagAlias.alias_string == alias_string)
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.where(TagAlias.alias_category == alias_category)
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)
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async def list_all(self) -> Sequence[AliasRow]:
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stmt = (
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select(
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TagAlias.alias_string,
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TagAlias.alias_category,
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TagAlias.canonical_tag_id,
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Tag.name,
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)
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.join(Tag, Tag.id == TagAlias.canonical_tag_id)
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.order_by(TagAlias.alias_string.asc())
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)
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rows = (await self.session.execute(stmt)).all()
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return [
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AliasRow(
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alias_string=r[0],
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alias_category=r[1],
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canonical_tag_id=r[2],
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canonical_tag_name=r[3],
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)
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for r in rows
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]
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