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.
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"""suggestion_threshold default 0.50 → 0.70
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Revision ID: 0033
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Revises: 0032
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Create Date: 2026-06-02
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Operator-flagged 2026-06-02 — the 0.50 default (set on 2026-06-01) is
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too noisy in practice; raise to 0.70 for both suggestion categories.
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Only conditionally updates singletons whose current value is still the
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2026-06-01 default (0.50). Operators who deliberately tuned their row
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to some other value (0.55, 0.65, 0.80, etc. via the Settings UI) keep
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their pick — the migration only catches the unchanged-default case.
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"""
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from typing import Sequence, Union
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from alembic import op
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revision: str = "0033"
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down_revision: Union[str, None] = "0032"
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branch_labels: Union[str, Sequence[str], None] = None
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depends_on: Union[str, Sequence[str], None] = None
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def upgrade() -> None:
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op.execute(
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"UPDATE ml_settings "
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"SET suggestion_threshold_character = 0.70 "
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"WHERE id = 1 AND suggestion_threshold_character = 0.50"
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)
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op.execute(
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"UPDATE ml_settings "
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"SET suggestion_threshold_general = 0.70 "
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"WHERE id = 1 AND suggestion_threshold_general = 0.50"
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)
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def downgrade() -> None:
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op.execute(
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"UPDATE ml_settings "
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"SET suggestion_threshold_character = 0.50 "
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"WHERE id = 1 AND suggestion_threshold_character = 0.70"
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)
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op.execute(
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"UPDATE ml_settings "
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"SET suggestion_threshold_general = 0.50 "
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"WHERE id = 1 AND suggestion_threshold_general = 0.70"
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)
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@@ -16,13 +16,14 @@ class MLSettings(Base):
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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id: Mapped[int] = mapped_column(Integer, primary_key=True)
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suggestion_threshold_character: Mapped[float] = mapped_column(
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suggestion_threshold_character: Mapped[float] = mapped_column(
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Float, nullable=False, default=0.50
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Float, nullable=False, default=0.70
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)
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)
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# Default lowered 0.95 → 0.50 on 2026-06-01 — operator-flagged that
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# Default raised 0.50 → 0.70 on 2026-06-02 — operator-flagged 0.50
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# 0.95 hid most general suggestions. Operator-tunable via Settings →
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# surfaced too many low-confidence picks; 0.70 keeps the rail
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# ML if too noisy.
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# signal-rich while still surfacing more than the original 0.95
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# which hid almost everything. Operator-tunable via Settings → ML.
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suggestion_threshold_general: Mapped[float] = mapped_column(
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suggestion_threshold_general: Mapped[float] = mapped_column(
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Float, nullable=False, default=0.50
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Float, nullable=False, default=0.70
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)
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)
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centroid_similarity_threshold: Mapped[float] = mapped_column(
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centroid_similarity_threshold: Mapped[float] = mapped_column(
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Float, nullable=False, default=0.55
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Float, nullable=False, default=0.55
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