refactor(ml): retire the Camie tagger + allowlist bulk-apply (#1189)
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Heads + CCIP are the tag source and head auto-apply is the earned propagation.
The Camie tagger ran only to feed the allowlist bulk-apply (its ImagePrediction
rows had no other consumer), and the allowlist was a SECOND, un-earned auto-apply
path firing in parallel with heads on every accept — exactly the un-earned spray
the v2 pivot replaced. Retire both.

Behavior change: accepting a suggestion now applies the tag to THAT image only
(source='ml_accepted', a head-training positive) — it no longer allowlists +
fans the tag across the library via Camie. Propagation is heads' earned
auto-apply. (Loses instant cold-start propagation for booru-vocab tags; that was
un-earned and bypassed the precision gate.)

- tag_and_embed is now EMBED-ONLY (no Camie load/infer, no ImagePrediction
  writes); backfill enqueues it for images with no embedding.
- Removed: services/ml/tagger.py, apply_allowlist_tags + helpers + daily beat +
  every enqueue caller (accept/alias/merge/per-image), api/allowlist.py +
  blueprint, ImagePrediction + TagAllowlist models/tables (migration 0067),
  AllowlistTable.vue + allowlist store, the accept coverage-projection payload.
- AllowlistService gutted to accept/dismiss/undismiss/reject (the rejection store
  the rail still needs); accept returns nothing, API returns {accepted, tag_id}.
- tag merge no longer repoints/triggers the allowlist; _keep_as_alias now keys on
  ML-applied image_tag sources (incl. head_auto) instead of the allowlist.
- UI: MLBackfillCard relabelled to embedding-only; accept toast simplified;
  MaintenancePanel drops the allowlist tile.

Left for a follow-up hygiene pass (now-inert, harmless): the dead settings
columns (tagger_store_floor, tagger_model_version, suggestion_threshold_*,
video_min_tag_frames), image_record.tagger_model_version, MLThresholdSliders
trim, and the Camie model download in download_models.py.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
This commit is contained in:
2026-06-30 13:04:31 -04:00
parent 3d77a38a25
commit 485387ff0b
31 changed files with 159 additions and 1710 deletions
@@ -0,0 +1,66 @@
"""retire the Camie tagger + allowlist bulk-apply (#1189)
The v2 pivot made heads + CCIP the tag source and head auto-apply the earned
propagation. The Camie tagger ran only to feed the allowlist bulk-apply (its
predictions had no other consumer), and the allowlist was a second, un-earned
auto-apply path parallel to heads. Both are retired — drop their storage.
(image_prediction = Camie's per-image predictions; tag_allowlist = the bulk-
apply allowlist. Nothing references INTO these tables, so the drop is clean.)
Revision ID: 0067
Revises: 0066
Create Date: 2026-06-30
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
revision: str = "0067"
down_revision: Union[str, None] = "0066"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
op.drop_table("image_prediction")
op.drop_table("tag_allowlist")
def downgrade() -> None:
op.create_table(
"tag_allowlist",
sa.Column("tag_id", sa.Integer(), nullable=False),
sa.Column(
"min_confidence", sa.Float(), nullable=False, server_default="0.9"
),
sa.Column(
"created_at", sa.DateTime(timezone=True),
server_default=sa.func.now(), nullable=False,
),
sa.ForeignKeyConstraint(["tag_id"], ["tag.id"], ondelete="CASCADE"),
sa.PrimaryKeyConstraint("tag_id"),
sa.CheckConstraint(
"min_confidence >= 0 AND min_confidence <= 1",
name="ck_tag_allowlist_confidence_range",
),
)
op.create_table(
"image_prediction",
sa.Column("id", sa.Integer(), primary_key=True),
sa.Column("image_record_id", sa.Integer(), nullable=False),
sa.Column("raw_name", sa.String(length=255), nullable=False),
sa.Column("category", sa.String(length=32), nullable=False),
sa.Column("score", sa.Float(), nullable=False),
sa.ForeignKeyConstraint(
["image_record_id"], ["image_record.id"], ondelete="CASCADE"
),
)
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"],
)