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FabledCurator/backend/app/models/head_auto_apply_run.py
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db: reconcile the models with the deployed schema (#3275)
Milestone 328's acceptance test compared a database built by the real
0001..0087 chain against one built from the models, and found ~130
places where they disagree. This closes them.

Almost all were the MODEL being wrong, so almost all of this is model
edits with no DDL — the database already had these things, nothing in it
changes, and no deploy is needed for this part:

* 92 columns gained server_default. The models carried Python-side
  `default=` only, so the ORM filled the value and the column had no
  database default. Anything inserting outside the ORM behaved
  differently from production.

* Eleven indexes that existed only in migrations are now declared:
  the three backup_run reporting indexes, the two date-ordered
  image_record browse indexes, import_task and presentation_review,
  and the three task_run history indexes. All use text() for their DESC
  ordering and postgresql_where for the partial one.

* Two UNIQUE indexes that autogenerate silently proposed DROPPING,
  because neither is expressible as a UniqueConstraint:
    uq_tag_name_kind_fandom  — an EXPRESSION index over
                               (name, kind, COALESCE(fandom_id, 0))
    uq_post_artist_external_id_null_source — PARTIAL, WHERE source_id
                               IS NULL
  post.py already had a comment describing the second one. The comment
  was right; nothing declared it.

* The two external_link enum CHECKs (host, status) — rule 36 territory,
  and absent from the model entirely.

* Two indexes were named explicitly. A bare index=True generated
  ix_tag_alias_canonical_tag_id where the database has
  ix_tag_alias_canonical, so autogenerate proposed a drop+create of an
  index that was already there under another name. Same for
  tag_suggestion_rejection.

Only ONE thing needed DDL, as 0088: tag.fandom_id is declared
index=True but no migration ever created that index.

Deliberately NOT here: image_record.sha256. The model says unique=True;
0001 created a plain index. Duplicates are possible today and the ORM
believes otherwise. The fix depends on whether duplicates already exist
— if they do, that is a dedupe decision, not a constraint — so it waits
on an answer about live data.

The real severity of #3275 is not the squash. It is that --autogenerate
has been unsafe on this project: run against the old models it would
have proposed dropping eleven indexes and two uniqueness guarantees.
2026-08-30 14:42:30 -04:00

48 lines
2.0 KiB
Python

"""HeadAutoApplyRun — persisted lifecycle of an earned-auto-apply sweep (#114).
A graduated head can apply its tag to images it scores above the head's
auto-apply threshold, without a human. This row tracks one such sweep (or a
dry-run PREVIEW of it) so the result survives navigation and the admin card can
show what fired / what would fire. Mirrors HeadTrainingRun. State machine:
running → ready / error. The `report` JSONB holds per-concept counts
(applied / projected / scanned).
"""
from datetime import datetime
from typing import Any
from sqlalchemy import Boolean, DateTime, Integer, String, Text, func
from sqlalchemy.dialects.postgresql import JSONB
from sqlalchemy.orm import Mapped, mapped_column
from .base import Base
class HeadAutoApplyRun(Base):
__tablename__ = "head_auto_apply_run"
id: Mapped[int] = mapped_column(Integer, primary_key=True)
# dry_run=True is a PREVIEW: scores + counts what WOULD apply, writes nothing
# (preview/apply parity, rule 93).
dry_run: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False, server_default="false")
params: Mapped[dict[str, Any]] = mapped_column(JSONB, nullable=False)
status: Mapped[str] = mapped_column(
String(16), nullable=False, default="running", index=True,
server_default="running",
)
# running | ready | error
started_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, server_default=func.now()
)
finished_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)
# Total tags applied across all heads this sweep (0 for a clean dry-run).
n_applied: Mapped[int | None] = mapped_column(Integer, nullable=True)
# Per-concept breakdown: [{tag_id, name, applied, scanned, threshold}, ...].
report: Mapped[dict[str, Any] | None] = mapped_column(JSONB, nullable=True)
error: Mapped[str | None] = mapped_column(Text, nullable=True)
last_progress_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)