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FabledCurator/backend/app/models/ml_settings.py
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bvandeusen 1fd594baaf
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chore(ml): suggestion_threshold default 0.50 → 0.70
Operator-flagged 2026-06-02 — the 0.50 default (set on 2026-06-01)
surfaces too many low-confidence picks in the modal's Suggestions
rail. 0.70 keeps the rail signal-rich while still showing more than
the original 0.95 (which hid almost everything).

Alembic 0033 updates the singleton row conditionally — only rows
still at the old 0.50 default flip to 0.70. Operators who tuned to
some other value via Settings → ML keep their pick.

Settings UI already exposes both sliders (MLThresholdSliders.vue),
so further tuning continues to work without a deploy.
2026-06-02 18:38:12 -04:00

43 lines
1.7 KiB
Python

"""MLSettings — single-row table holding ML pipeline tunables."""
from datetime import datetime
from sqlalchemy import CheckConstraint, DateTime, Float, Integer, String, func
from sqlalchemy.orm import Mapped, mapped_column
from .base import Base
class MLSettings(Base):
__tablename__ = "ml_settings"
# Bare name — Base.metadata's naming convention prepends ck_<table>_,
# producing the final ck_ml_settings_singleton (matches migration 0003).
__table_args__ = (CheckConstraint("id = 1", name="singleton"),)
id: Mapped[int] = mapped_column(Integer, primary_key=True)
suggestion_threshold_character: Mapped[float] = mapped_column(
Float, nullable=False, default=0.70
)
# Default raised 0.50 → 0.70 on 2026-06-02 — operator-flagged 0.50
# surfaced too many low-confidence picks; 0.70 keeps the rail
# signal-rich while still surfacing more than the original 0.95
# which hid almost everything. Operator-tunable via Settings → ML.
suggestion_threshold_general: Mapped[float] = mapped_column(
Float, nullable=False, default=0.70
)
centroid_similarity_threshold: Mapped[float] = mapped_column(
Float, nullable=False, default=0.55
)
min_reference_images: Mapped[int] = mapped_column(
Integer, nullable=False, default=5
)
tagger_model_version: Mapped[str] = mapped_column(
String(128), nullable=False, default="camie-tagger-v2"
)
embedder_model_version: Mapped[str] = mapped_column(
String(128), nullable=False, default="siglip-so400m-patch14-384"
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), nullable=False, server_default=func.now()
)