alembic/versions/0081_stricter_auto_apply_defaults.py

@@ -0,0 +1,43 @@
+"""stricter auto-apply defaults (milestone 139) — cut auto-apply misfires
+
+head_auto_apply_min_positives 30→50 and ccip_auto_apply_threshold 0.92→0.95
+(operator-asked 2026-07-06). The head graduation precision bar stays 0.97 — the
+operator confirmed the general-tag confidence was already well tuned; only the
+support floor + the CCIP match confidence are raised. The model defaults change
+for fresh installs; here we bump the existing singleton row IFF it is still at
+the previous default, so a deliberate operator change is NOT clobbered.
+
+Revision ID: 0081
+Revises: 0080
+Create Date: 2026-07-06
+"""
+from typing import Sequence, Union
+
+from alembic import op
+
+revision: str = "0081"
+down_revision: Union[str, None] = "0080"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.execute(
+        "UPDATE ml_settings SET head_auto_apply_min_positives = 50 "
+        "WHERE head_auto_apply_min_positives = 30"
+    )
+    op.execute(
+        "UPDATE ml_settings SET ccip_auto_apply_threshold = 0.95 "
+        "WHERE ccip_auto_apply_threshold = 0.92"
+    )
+
+
+def downgrade() -> None:
+    op.execute(
+        "UPDATE ml_settings SET head_auto_apply_min_positives = 30 "
+        "WHERE head_auto_apply_min_positives = 50"
+    )
+    op.execute(
+        "UPDATE ml_settings SET ccip_auto_apply_threshold = 0.92 "
+        "WHERE ccip_auto_apply_threshold = 0.95"
+    )

backend/app/celery_app.py

@@ -147,6 +147,11 @@ def make_celery() -> Celery:
                 "task": "backend.app.tasks.ml.scheduled_ccip_auto_apply",
                 "schedule": 86400.0,  # no-op unless ccip_auto_apply_enabled
             },
+            "retract-auto-tags-daily": {
+                "task": "backend.app.tasks.ml.scheduled_retract_auto_tags",
+                "schedule": 86400.0,  # soft auto-apply: drop auto-tags now below
+                # their threshold (m139); no-op unless the auto-apply switch is on
+            },
             "snapshot-head-metrics-daily": {
                 "task": "backend.app.tasks.maintenance.snapshot_head_metrics",
                 "schedule": 86400.0,

backend/app/models/ml_settings.py

@@ -63,7 +63,9 @@ class MLSettings(Base):
         Boolean, nullable=False, default=True
     )
     head_auto_apply_min_positives: Mapped[int] = mapped_column(
-        Integer, nullable=False, default=30
+        # Support floor raised 30→50 (operator-asked 2026-07-06): a head needs
+        # more human labels before it may fire without a human.
+        Integer, nullable=False, default=50
     )
     # CCIP character-match cosine cut (#114). 0.85 default — the v1 flat 0.75
     # over-fired (high-reference characters matched a scatter of images); 0.85
@@ -78,7 +80,9 @@ class MLSettings(Base):
         Boolean, nullable=False, default=True
     )
     ccip_auto_apply_threshold: Mapped[float] = mapped_column(
-        Float, nullable=False, default=0.92
+        # Raised 0.92→0.95 (operator-asked 2026-07-06) so only very confident
+        # character matches auto-tag.
+        Float, nullable=False, default=0.95
     )
     # Default = SigLIP 2 (so400m, 512px) for new installs (migration 0069);
     # existing libraries keep their stored value until the operator re-embeds.

backend/app/services/gallery_service.py

@@ -22,7 +22,15 @@ from sqlalchemy import Select, and_, distinct, exists, func, or_, select
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy.orm import aliased
 
-from ..models import Artist, ImageProvenance, ImageRecord, Post, Source, Tag
+from ..models import (
+    Artist,
+    ImageProvenance,
+    ImageRecord,
+    Post,
+    Source,
+    Tag,
+    TagPositiveConfirmation,
+)
 from ..models.tag import PRESENTATION_SYSTEM_TAGS, image_tag
 from .pagination import decode_cursor, encode_cursor
 from .tag_query import (
@@ -731,8 +739,14 @@ class GalleryService:
         # Self-join Tag to resolve a character's fandom NAME (not just id) so the
         # modal chip can label it without an N+1 (shared tag_query helpers).
         fandom_alias = fandom_join_alias()
+        # source drives the auto-applied badge; confirmed = operator affirmed the
+        # tag (positive + retraction-shielded, milestone 139).
+        confirmed = exists().where(
+            TagPositiveConfirmation.image_record_id == image_id,
+            TagPositiveConfirmation.tag_id == Tag.id,
+        ).label("confirmed")
         tag_stmt = (
-            select(*tag_columns(fandom_alias))
+            select(*tag_columns(fandom_alias), image_tag.c.source, confirmed)
             .select_from(
                 Tag.__table__
                 .join(image_tag, image_tag.c.tag_id == Tag.id)

backend/app/services/ml/ccip.py

@@ -13,7 +13,7 @@ exact CCIP difference metric/threshold gets validated against the model during
 the hands-on eval. numpy is imported lazily (API worker has it via pgvector).
 """
 
-from sqlalchemy import func, select
+from sqlalchemy import exists, func, select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from ...models import (
@@ -23,8 +23,10 @@ from ...models import (
     MLSettings,
     Tag,
     TagKind,
+    TagPositiveConfirmation,
 )
 from ...models.tag import image_tag
+from .training_data import _AUTO_SOURCES
 
 # Cosine-similarity floor to call a figure the same character. The live setting
 # (ml_settings.ccip_match_threshold) drives it; this is only the fallback when no
@@ -111,6 +113,17 @@ async def _ref_signature(session: AsyncSession) -> tuple:
     return (n_tags, n_regs, max_id, n_hygiene)
 
 
+def _positive_char_tag():
+    """Condition on the joined character image_tag: HUMAN-applied or operator-
+    confirmed — NOT an unconfirmed auto-apply. Keeps an auto-tagged character from
+    self-seeding CCIP references, so a ccip_auto misfire can't reinforce itself
+    (milestone 139) — mirrors the head-training positive exclusion."""
+    return image_tag.c.source.not_in(_AUTO_SOURCES) | exists().where(
+        TagPositiveConfirmation.image_record_id == image_tag.c.image_record_id,
+        TagPositiveConfirmation.tag_id == image_tag.c.tag_id,
+    )
+
+
 async def character_references(session: AsyncSession) -> dict[int, list]:
     """Per character-tag CCIP reference vectors: figure/face-region CCIP
     embeddings on UNAMBIGUOUS (single-character) images carrying that tag.
@@ -128,6 +141,7 @@ async def character_references(session: AsyncSession) -> dict[int, list]:
             )
             .join(Tag, Tag.id == image_tag.c.tag_id)
             .where(Tag.kind == TagKind.character)
+            .where(_positive_char_tag())
             .where(ImageRegion.kind.in_(_FIGURE_KINDS))
             .where(ImageRegion.ccip_embedding.is_not(None))
             .where(ImageRegion.image_record_id.in_(_single_character_images()))

backend/app/services/ml/character_prototypes.py

@@ -31,9 +31,16 @@ from ...models import (
     MLSettings,
     Tag,
     TagKind,
+    TagPositiveConfirmation,
 )
 from ...models.tag import image_tag
-from .ccip import _FIGURE_KINDS, _hygiene_tagged_images, _single_character_images
+from .ccip import (
+    _FIGURE_KINDS,
+    _hygiene_tagged_images,
+    _l2norm,
+    _positive_char_tag,
+    _single_character_images,
+)
 
 # Deterministic per-tag capping so a rebuild of an UNCHANGED reference set
 # resamples identically (stable prototypes, no churn between refreshes).
@@ -63,7 +70,16 @@ def _global_signature(session: Session) -> str:
         .join(Tag, Tag.id == image_tag.c.tag_id)
         .where(Tag.is_system.is_(True))
     ).scalar_one()
-    return f"{n_tags}:{n_regs}:{max_id or 0}:{n_hygiene}"
+    # Character confirmations affect the reference set now that auto-tags only
+    # seed references once confirmed (milestone 139) — so a confirm must trip the
+    # gate, or the per-character diff (which reflects it) never runs.
+    n_conf = session.execute(
+        select(func.count())
+        .select_from(TagPositiveConfirmation)
+        .join(Tag, Tag.id == TagPositiveConfirmation.tag_id)
+        .where(Tag.kind == TagKind.character)
+    ).scalar_one()
+    return f"{n_tags}:{n_regs}:{max_id or 0}:{n_hygiene}:{n_conf}"
 
 
 def _current_fingerprints(session: Session) -> dict[int, str]:
@@ -84,6 +100,7 @@ def _current_fingerprints(session: Session) -> dict[int, str]:
         )
         .join(Tag, Tag.id == image_tag.c.tag_id)
         .where(Tag.kind == TagKind.character)
+        .where(_positive_char_tag())
         .where(ImageRegion.kind.in_(_FIGURE_KINDS))
         .where(ImageRegion.ccip_embedding.is_not(None))
         .where(ImageRegion.image_record_id.in_(_single_character_images()))
@@ -104,6 +121,7 @@ def _rebuild_one(session: Session, tag_id: int, cap: int) -> int:
             image_tag.c.image_record_id == ImageRegion.image_record_id,
         )
         .where(image_tag.c.tag_id == tag_id)
+        .where(_positive_char_tag())
         .where(ImageRegion.kind.in_(_FIGURE_KINDS))
         .where(ImageRegion.ccip_embedding.is_not(None))
         .where(ImageRegion.image_record_id.in_(_single_character_images()))
@@ -173,3 +191,76 @@ def refresh_character_prototypes(
     settings.ccip_ref_signature = sig
     session.commit()
     return {"skipped": False, "rebuilt": rebuilt, "removed": removed}
+
+
+def retract_auto_applied_ccip(session: Session) -> int:
+    """Soft auto-apply for CCIP character tags (milestone 139): re-score every
+    standing source='ccip_auto' character tag against that character's prototypes
+    and REMOVE the ones whose best figure match is now BELOW
+    ccip_auto_apply_threshold. Skips operator-confirmed tags. SILENT — a low score
+    isn't proof the tag was wrong (that's reserved for an operator removal). No-op
+    unless ccip_auto_apply_enabled. A character with no prototypes yet, or an image
+    with no figure vectors, is left alone (can't judge → keep). Returns
+    n_retracted."""
+    import numpy as np
+
+    settings = session.execute(
+        select(MLSettings).where(MLSettings.id == 1)
+    ).scalar_one()
+    if not settings.ccip_auto_apply_enabled:
+        return 0
+    thr = float(settings.ccip_auto_apply_threshold)
+    pairs = session.execute(
+        select(image_tag.c.image_record_id, image_tag.c.tag_id)
+        .where(image_tag.c.source == "ccip_auto")
+    ).all()
+    if not pairs:
+        return 0
+    confirmed = {
+        (iid, tid) for iid, tid in session.execute(
+            select(
+                TagPositiveConfirmation.image_record_id,
+                TagPositiveConfirmation.tag_id,
+            )
+        ).all()
+    }
+    # Each involved character's normalized prototype matrix, loaded once.
+    proto: dict[int, object] = {}
+    for tid in {tid for _iid, tid in pairs}:
+        vecs = [
+            v for (v,) in session.execute(
+                select(CharacterPrototype.ccip_embedding)
+                .where(CharacterPrototype.tag_id == tid)
+            )
+        ]
+        if vecs:
+            proto[tid] = _l2norm(
+                np.vstack([np.asarray(v, dtype=np.float32) for v in vecs]), np
+            )
+    retracted = 0
+    for iid, tid in pairs:
+        if (iid, tid) in confirmed or tid not in proto:
+            continue                                   # confirmed / no prototypes
+        qvecs = [
+            v for (v,) in session.execute(
+                select(ImageRegion.ccip_embedding)
+                .where(ImageRegion.image_record_id == iid)
+                .where(ImageRegion.kind.in_(_FIGURE_KINDS))
+                .where(ImageRegion.ccip_embedding.is_not(None))
+            )
+        ]
+        if not qvecs:
+            continue                                   # no figure vectors → keep
+        Q = _l2norm(
+            np.vstack([np.asarray(v, dtype=np.float32) for v in qvecs]), np
+        )
+        if float((Q @ proto[tid].T).max()) < thr:
+            session.execute(
+                image_tag.delete()
+                .where(image_tag.c.image_record_id == iid)
+                .where(image_tag.c.tag_id == tid)
+                .where(image_tag.c.source == "ccip_auto")
+            )
+            retracted += 1
+    session.commit()
+    return retracted

backend/app/services/ml/heads.py

@@ -22,7 +22,7 @@ import logging
 from datetime import UTC, datetime
 from typing import Any
 
-from sqlalchemy import delete, func, select
+from sqlalchemy import delete, exists, func, select
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy.orm import Session
 
@@ -35,10 +35,12 @@ from ...models import (
     Tag,
     TagHead,
     TagKind,
+    TagPositiveConfirmation,
     TagSuggestionRejection,
 )
 from ...models.tag import image_tag
 from .training_data import (
+    _AUTO_SOURCES,
     _auto_apply_point,
     _hygiene_excluded_ids,
     _ids_with_tag,
@@ -137,13 +139,20 @@ def _embedder_version(session: Session) -> str:
 
 
 def _eligible_tag_ids(session: Session, min_pos: int) -> list[int]:
-    """Concept tags (general/character) with >= min_pos labelled images — the
-    set that gets a head. Counts all sources; source-aware filtering (#1133) is
-    a separate, optional refinement."""
+    """Concept tags (general/character) with >= min_pos POSITIVE images — the set
+    that gets a head. Counts human-applied + operator-confirmed tags only;
+    unconfirmed auto-applied predictions do NOT count toward eligibility (they
+    don't train the head — milestone 139), so a concept can't graduate on its own
+    guesses."""
+    confirmed = exists().where(
+        TagPositiveConfirmation.image_record_id == image_tag.c.image_record_id,
+        TagPositiveConfirmation.tag_id == image_tag.c.tag_id,
+    )
     rows = session.execute(
         select(Tag.id)
         .join(image_tag, image_tag.c.tag_id == Tag.id)
         .where(Tag.kind.in_(_HEAD_KINDS))
+        .where(image_tag.c.source.not_in(_AUTO_SOURCES) | confirmed)
         .group_by(Tag.id)
         .having(func.count(image_tag.c.image_record_id) >= min_pos)
     ).all()
@@ -180,11 +189,20 @@ def _head_fingerprints(session: Session, tag_ids: list[int]) -> dict[int, str]:
         .group_by(TagSuggestionRejection.tag_id)
     ).all()
     rej_map = {t: (c, m) for t, c, m in rej}
+    # Confirmations promote an auto-applied tag to a positive (milestone 139), so
+    # a confirm must move the fingerprint too — else a manual Retrain right after
+    # confirming wouldn't fold the tag in (the nightly full run would).
+    conf = session.execute(
+        select(TagPositiveConfirmation.tag_id, func.count())
+        .where(TagPositiveConfirmation.tag_id.in_(tag_ids))
+        .group_by(TagPositiveConfirmation.tag_id)
+    ).all()
+    conf_map = dict(conf)
     out = {}
     for t in tag_ids:
         pc, pm = pos_map.get(t, (0, None))
         rc, rm = rej_map.get(t, (0, None))
-        out[t] = f"{pc}:{pm}:{rc}:{rm}"
+        out[t] = f"{pc}:{pm}:{rc}:{rm}:{conf_map.get(t, 0)}"
     return out
 
 
@@ -723,3 +741,64 @@ def auto_apply_sweep(
         for h in range(len(rows))
     ]
     return {"n_applied": sum(applied), "concepts": concepts}
+
+
+def retract_auto_applied_heads(session: Session) -> int:
+    """Soft auto-apply (milestone 139): re-score every standing source='head_auto'
+    tag against its CURRENT head and REMOVE the ones now BELOW the head's
+    auto_apply_threshold — i.e. the head sharpened (or the operator raised the bar)
+    and no longer supports them. Skips operator-confirmed tags
+    (TagPositiveConfirmation). SILENT: a low score isn't proof the tag was wrong,
+    so no hard negative is recorded — that's reserved for an operator removal.
+    No-op unless head_auto_apply_enabled. Only re-scores the images that ALREADY
+    carry the auto-tag (bounded), never the whole library. Returns n_retracted."""
+    import numpy as np
+
+    settings = _settings(session)
+    if not settings.head_auto_apply_enabled:
+        return 0
+    heads = session.execute(
+        select(
+            TagHead.tag_id, TagHead.weights, TagHead.bias,
+            TagHead.auto_apply_threshold,
+        )
+        .where(TagHead.embedding_version == settings.embedder_model_version)
+        .where(TagHead.auto_apply_threshold.is_not(None))
+    ).all()
+    retracted = 0
+    for tag_id, weights, bias, thr in heads:
+        auto_ids = [
+            iid for (iid,) in session.execute(
+                select(image_tag.c.image_record_id)
+                .where(image_tag.c.tag_id == tag_id)
+                .where(image_tag.c.source == "head_auto")
+            )
+        ]
+        if not auto_ids:
+            continue
+        confirmed = {
+            iid for (iid,) in session.execute(
+                select(TagPositiveConfirmation.image_record_id)
+                .where(TagPositiveConfirmation.tag_id == tag_id)
+                .where(TagPositiveConfirmation.image_record_id.in_(auto_ids))
+            )
+        }
+        candidates = [i for i in auto_ids if i not in confirmed]
+        emb = _load_embeddings(session, candidates)
+        cids = [i for i in candidates if i in emb]
+        if not cids:
+            continue
+        Xn = _l2norm(np.vstack([emb[i] for i in cids]).astype(np.float32), np)
+        w = np.asarray(weights, dtype=np.float32)
+        probs = 1.0 / (1.0 + np.exp(-(Xn @ w + float(bias))))
+        below = [cids[k] for k in np.where(probs < float(thr))[0]]
+        for iid in below:
+            session.execute(
+                image_tag.delete()
+                .where(image_tag.c.image_record_id == iid)
+                .where(image_tag.c.tag_id == tag_id)
+                .where(image_tag.c.source == "head_auto")
+            )
+            retracted += 1
+        session.commit()
+    return retracted

backend/app/services/ml/training_data.py

@@ -17,9 +17,20 @@ from typing import Any
 from sqlalchemy import func, select
 from sqlalchemy.orm import Session
 
-from ...models import ImageRecord, Tag, TagSuggestionRejection
+from ...models import (
+    ImageRecord,
+    Tag,
+    TagPositiveConfirmation,
+    TagSuggestionRejection,
+)
 from ...models.tag import image_tag
 
+# Auto-apply sources whose tags are PROVISIONAL: they never train a head (or seed
+# a CCIP reference) unless the operator confirms them (milestone 139). Keeping
+# auto-applied predictions out of training is what makes them "soft" — a misfire
+# can't reinforce itself, so the retraction sweep can actually drop it.
+_AUTO_SOURCES = ("head_auto", "ccip_auto", "ml_auto")
+
 
 def _hygiene_excluded_ids(session: Session) -> set[int]:
     """Ids of images carrying ANY system tag (wip / banner / editor
@@ -45,9 +56,23 @@ def _hygiene_excluded_ids(session: Session) -> set[int]:
 
 
 def _ids_with_tag(session: Session, tag_id: int) -> list[int]:
+    """Image ids that count as POSITIVES for this tag's head: human-applied
+    (manual / accepted) tags PLUS any auto-applied tag the operator explicitly
+    confirmed (TagPositiveConfirmation). Unconfirmed auto-applied tags are
+    EXCLUDED — they are provisional and must not train the head that judges
+    them (milestone 139)."""
+    confirmed = (
+        select(TagPositiveConfirmation.image_record_id)
+        .where(TagPositiveConfirmation.tag_id == tag_id)
+    )
     return [
         r[0] for r in session.execute(
-            select(image_tag.c.image_record_id).where(image_tag.c.tag_id == tag_id)
+            select(image_tag.c.image_record_id)
+            .where(image_tag.c.tag_id == tag_id)
+            .where(
+                image_tag.c.source.not_in(_AUTO_SOURCES)
+                | image_tag.c.image_record_id.in_(confirmed)
+            )
         ).all()
     ]
 

backend/app/services/tag_query.py

@@ -91,4 +91,11 @@ def serialize_tag(row) -> dict:
         "fandom_id": row.fandom_id,
         "fandom_name": row.fandom_name,
         "is_system": bool(getattr(row, "is_system", False)),
+        # Applied-tag context: only the image-scoped selects (list_for_image /
+        # get_image_with_tags) provide these; autocomplete / directory don't →
+        # default. `source` drives the auto-applied badge; `confirmed` = the
+        # operator affirmed the tag (a training positive, shielded from the
+        # retraction sweep — milestone 139).
+        "source": getattr(row, "source", None),
+        "confirmed": bool(getattr(row, "confirmed", False)),
     }

backend/app/services/tag_service.py

@@ -9,7 +9,14 @@ from sqlalchemy import and_, case, exists, func, select, text, update
 from sqlalchemy.dialects.postgresql import insert as pg_insert
 from sqlalchemy.ext.asyncio import AsyncSession
 
-from ..models import HeadMetric, Tag, TagHead, TagKind, image_tag
+from ..models import (
+    HeadMetric,
+    Tag,
+    TagHead,
+    TagKind,
+    TagPositiveConfirmation,
+    image_tag,
+)
 from .db_helpers import get_or_create
 from .tag_query import fandom_join_alias, tag_columns
 
@@ -288,8 +295,14 @@ class TagService:
         character chip with its fandom without an N+1 (mirrors the
         autocomplete/directory resolution)."""
         fandom_alias = fandom_join_alias()
+        # source drives the auto-applied badge; confirmed = operator affirmed the
+        # tag (positive + retraction-shielded, milestone 139).
+        confirmed = exists().where(
+            TagPositiveConfirmation.image_record_id == image_id,
+            TagPositiveConfirmation.tag_id == Tag.id,
+        ).label("confirmed")
         stmt = (
-            select(*tag_columns(fandom_alias))
+            select(*tag_columns(fandom_alias), image_tag.c.source, confirmed)
             .select_from(
                 Tag.__table__
                 .join(image_tag, image_tag.c.tag_id == Tag.id)

backend/app/tasks/ml.py

@@ -592,3 +592,23 @@ def scheduled_ccip_auto_apply() -> str:
                     applied += 1
             session.commit()
         return f"applied={applied}"
+
+
+@celery.task(
+    name="backend.app.tasks.ml.scheduled_retract_auto_tags",
+    soft_time_limit=1800, time_limit=2100,
+)
+def scheduled_retract_auto_tags() -> str:
+    """Soft auto-apply (milestone 139): retract standing head_auto/ccip_auto tags
+    the model no longer supports (score now below the auto-apply threshold),
+    skipping operator-confirmed ones. Silent (no hard negative). No-op unless the
+    respective auto-apply switch is on. Returns 'head=N ccip=M'."""
+    from ..services.ml.character_prototypes import retract_auto_applied_ccip
+    from ..services.ml.heads import retract_auto_applied_heads
+
+    SessionLocal = _sync_session_factory()
+    with SessionLocal() as session:
+        n_head = retract_auto_applied_heads(session)
+    with SessionLocal() as session:
+        n_ccip = retract_auto_applied_ccip(session)
+    return f"head={n_head} ccip={n_ccip}"

frontend/src/components/modal/SuggestionsCategoryGroup.vue

@@ -1,14 +1,25 @@
 <template>
   <div class="fc-sgroup">
-    <button
-      v-if="collapsible"
-      class="fc-sgroup__header fc-sgroup__header--btn"
-      @click="open = !open"
-    >
-      <v-icon size="small">{{ open ? 'mdi-chevron-down' : 'mdi-chevron-right' }}</v-icon>
-      {{ label }} ({{ items.length }})
-    </button>
-    <div v-else class="fc-sgroup__header">{{ label }}</div>
+    <div class="fc-sgroup__header-row">
+      <button
+        v-if="collapsible"
+        class="fc-sgroup__header fc-sgroup__header--btn"
+        @click="open = !open"
+      >
+        <v-icon size="small">{{ open ? 'mdi-chevron-down' : 'mdi-chevron-right' }}</v-icon>
+        {{ label }} ({{ items.length }})
+      </button>
+      <div v-else class="fc-sgroup__header">{{ label }}</div>
+      <!-- "Confirm what's right, reject the rest": clears every still-unhandled
+           suggestion in this section at once. Reversible (each stays flagged
+           rejected with one-click un-reject), so no confirm dialog. -->
+      <button
+        v-if="rejectableCount > 0"
+        class="fc-sgroup__reject-rest" type="button"
+        :title="`Reject the ${rejectableCount} remaining ${label} suggestion${rejectableCount === 1 ? '' : 's'}`"
+        @click="$emit('reject-all')"
+      >Reject rest</button>
+    </div>
 
     <div v-show="open" class="fc-sgroup__items">
       <SuggestionItem
@@ -25,7 +36,7 @@
 </template>
 
 <script setup>
-import { ref } from 'vue'
+import { computed, ref } from 'vue'
 import SuggestionItem from './SuggestionItem.vue'
 
 const props = defineProps({
@@ -34,24 +45,45 @@ const props = defineProps({
   collapsible: { type: Boolean, default: false },
   defaultOpen: { type: Boolean, default: true }
 })
-defineEmits(['accept', 'alias', 'remove-alias', 'dismiss', 'undismiss'])
+defineEmits(['accept', 'alias', 'remove-alias', 'dismiss', 'undismiss', 'reject-all'])
 
+// Still-unhandled suggestions (not yet rejected) — how many "Reject rest" clears.
+const rejectableCount = computed(() => props.items.filter((s) => !s.rejected).length)
 const open = ref(props.collapsible ? props.defaultOpen : true)
 </script>
 
 <style scoped>
 .fc-sgroup { margin-bottom: 10px; }
+.fc-sgroup__header-row {
+  display: flex; align-items: center; gap: 8px;
+  margin-bottom: 4px;
+}
 .fc-sgroup__header {
+  flex: 1 1 auto; min-width: 0;
   font-family: 'Inter', sans-serif;
   font-size: 11px; font-weight: 600;
   text-transform: uppercase; letter-spacing: 0.06em;
   color: rgb(var(--v-theme-on-surface-variant, var(--v-theme-on-surface)));
-  margin-bottom: 4px;
 }
 .fc-sgroup__header--btn {
   display: flex; align-items: center; gap: 4px;
   background: none; border: none; cursor: pointer;
-  padding: 0; width: 100%; text-align: left;
+  padding: 0; text-align: left;
   font: inherit; text-transform: uppercase; letter-spacing: 0.06em;
 }
+/* Section-level "reject the remaining" — subtle until hovered so it doesn't
+   compete with the per-row verdicts. */
+.fc-sgroup__reject-rest {
+  flex: 0 0 auto;
+  background: none; border: none; cursor: pointer;
+  font-family: 'Inter', sans-serif;
+  font-size: 10px; font-weight: 600;
+  text-transform: uppercase; letter-spacing: 0.04em;
+  color: rgb(var(--v-theme-error));
+  padding: 2px 5px; border-radius: 4px;
+}
+.fc-sgroup__reject-rest:hover { background: rgb(var(--v-theme-error), 0.1); }
+.fc-sgroup__reject-rest:focus-visible {
+  outline: 2px solid rgb(var(--v-theme-error)); outline-offset: 1px;
+}
 </style>

frontend/src/components/modal/SuggestionsPanel.vue

@@ -25,6 +25,7 @@
         collapsible :default-open="true"
         @accept="onAccept" @alias="onAlias" @remove-alias="onRemoveAlias"
         @dismiss="onDismiss" @undismiss="onUndismiss"
+        @reject-all="onRejectAll('system')"
       />
       <SuggestionsCategoryGroup
         v-for="cat in peopleCats" :key="cat"
@@ -32,6 +33,7 @@
         :label="labelFor(cat)" :items="store.byCategory[cat] || []"
         @accept="onAccept" @alias="onAlias" @remove-alias="onRemoveAlias"
         @dismiss="onDismiss" @undismiss="onUndismiss"
+        @reject-all="onRejectAll(cat)"
       />
       <SuggestionsCategoryGroup
         v-if="store.byCategory.general && store.byCategory.general.length"
@@ -39,6 +41,7 @@
         collapsible :default-open="true"
         @accept="onAccept" @alias="onAlias" @remove-alias="onRemoveAlias"
         @dismiss="onDismiss" @undismiss="onUndismiss"
+        @reject-all="onRejectAll('general')"
       />
     </div>
 
@@ -76,6 +79,16 @@ const emit = defineEmits(['accepted', 'dismissed'])
 // re-focus the tag input — same return-to-input behaviour as accept.
 function onDismiss (s) { store.dismiss(s); emit('dismissed') }
 function onUndismiss (s) { store.undismiss(s); emit('dismissed') }
+// Section-level "Reject rest": dismiss every still-unhandled suggestion in the
+// category, then return focus to the input like a single reject does.
+async function onRejectAll (category) {
+  try {
+    await store.dismissRemaining(category)
+    emit('dismissed')
+  } catch (e) {
+    toast({ text: `Reject failed: ${e.message}`, type: 'error' })
+  }
+}
 const store = useSuggestionsStore()
 const modalStore = useModalStore()
 const host = props.host || modalStore

frontend/src/components/modal/TagAutocomplete.vue

@@ -97,6 +97,7 @@
 import { computed, nextTick, onMounted, ref, watch } from 'vue'
 import { useTagStore } from '../../stores/tags.js'
 import { useSuggestionsStore } from '../../stores/suggestions.js'
+import { useInflightToken } from '../../composables/useInflightToken.js'
 import FandomPicker from './FandomPicker.vue'
 
 const emit = defineEmits(['pick-existing', 'pick-new', 'accept-suggestion', 'cancel'])
@@ -183,17 +184,26 @@ const parsed = computed(() => {
 const parsedKind = computed(() => parsed.value.kind)
 const parsedName = computed(() => parsed.value.name)
 
+// Inflight guard: the debounce only clears the TIMER, so once a fetch has fired
+// it still races later ones — a slower earlier-prefix response ("s") could land
+// after "sex" and overwrite the dropdown with stale, wrong-prefix matches
+// (operator-flagged 2026-07-06). Gate each response on a token so only the latest
+// query's results are applied.
+const acInflight = useInflightToken()
 let debounceId = null
 watch(query, () => {
   highlight.value = 0
   if (debounceId) clearTimeout(debounceId)
+  acInflight.cancel()
   debounceId = setTimeout(async () => {
     const q = parsedName.value
     if (!q) { hits.value = []; return }
     // Autocomplete across ALL kinds. When the user typed a prefix the
     // matches list is naturally narrower because the parsed name is
     // shorter; we don't filter server-side by kind.
-    hits.value = await store.autocomplete(q, null, 10)
+    const t = acInflight.claim()
+    const res = await store.autocomplete(q, null, 10)
+    if (t.isCurrent()) hits.value = res
   }, 200)
 })
 

frontend/src/components/modal/TagChip.vue

@@ -16,8 +16,20 @@
       >mdi-shield-outline</v-icon><span
         v-if="tag.fandom_id" class="fc-tag-chip__fandom"
         :title="tag.fandom_name ? `Fandom: ${tag.fandom_name}` : 'Has a fandom'"
-      >→<template v-if="fandomLabel">&nbsp;{{ fandomLabel }}</template></span>
+      >→<template v-if="fandomLabel">&nbsp;{{ fandomLabel }}</template></span><span
+        v-if="unconfirmedAuto" class="fc-tag-chip__auto"
+        title="Auto-applied — provisional: it won't train the model and can be retracted until you confirm it."
+      >auto</span>
     </v-chip>
+    <!-- Keep/confirm an auto-applied tag: promotes it to a training positive and
+         shields it from the retraction sweep (milestone 139). Only shown for
+         provisional (unconfirmed) auto-tags. -->
+    <button
+      v-if="unconfirmedAuto" class="fc-tag-chip__confirm" type="button"
+      :title="`Keep “${tag.name}” — confirm this auto-tag so it trains the model and won't be retracted`"
+      :aria-label="`Confirm ${tag.name}`"
+      @click.stop="$emit('confirm', tag)"
+    ><v-icon size="14">mdi-check</v-icon></button>
     <!-- Modal-safe kebab is baked into KebabMenu (this chip lives in the
          teleported image modal — #711). System tags hide it entirely: rename
          is refused server-side (the hygiene machinery keys on the row) and
@@ -43,6 +55,8 @@ import { useTagStore } from '../../stores/tags.js'
 import { useApi } from '../../composables/useApi.js'
 import KebabMenu from '../common/KebabMenu.vue'
 
+const AUTO_SOURCES = ['head_auto', 'ccip_auto', 'ml_auto']
+
 const props = defineProps({
   tag: { type: Object, required: true },
   // When set (the tagging panels), hovering the chip asks the backend which crop
@@ -51,11 +65,19 @@ const props = defineProps({
   // the hover is inert (no injected target, or no image to ground against).
   imageId: { type: Number, default: null },
 })
-defineEmits(['remove', 'rename', 'set-fandom', 'navigate'])
+defineEmits(['remove', 'rename', 'set-fandom', 'navigate', 'confirm'])
 
 const store = useTagStore()
 const api = useApi()
 
+// An auto-applied tag the operator hasn't confirmed yet — provisional (milestone
+// 139): it doesn't train the model and the retraction sweep can drop it. Shows
+// the "auto" badge + a Keep/confirm button. `source`/`confirmed` come from the
+// applied-tags payload (list_for_image / get_image_with_tags).
+const unconfirmedAuto = computed(() =>
+  AUTO_SOURCES.includes(props.tag.source) && !props.tag.confirmed
+)
+
 // #1206 Step 4: applied-tag grounding. `fcSuggestionHover` is provided by the
 // image viewer / Explore host (a no-op elsewhere). Applied tags aren't scored
 // live, so we fetch the winning region on demand and cache it per (image, tag).
@@ -120,4 +142,26 @@ function iconFor (k) { return KIND_ICONS[k] || 'mdi-tag' }
 .fc-tag-chip__kebab { opacity: 0.7; }
 .fc-tag-chip:hover .fc-tag-chip__kebab { opacity: 1; }
 .fc-tag-chip__fandom { opacity: 0.7; font-size: 0.85em; }
+/* "auto" = provisional (auto-applied, unconfirmed). Quiet pill inside the chip. */
+.fc-tag-chip__auto {
+  display: inline-block; vertical-align: middle; margin-left: 4px;
+  font-size: 9px; font-weight: 700;
+  text-transform: uppercase; letter-spacing: 0.04em;
+  color: rgb(var(--v-theme-on-surface-variant));
+  background: rgb(var(--v-theme-surface-light));
+  border: 1px solid rgb(var(--v-theme-on-surface-variant), 0.3);
+  padding: 0 4px; border-radius: 999px;
+}
+/* Keep/confirm — a success-tinted check next to a provisional auto-tag. */
+.fc-tag-chip__confirm {
+  flex: 0 0 auto;
+  display: inline-flex; align-items: center; justify-content: center;
+  width: 20px; height: 20px; border-radius: 50%;
+  border: none; background: transparent; cursor: pointer;
+  color: rgb(var(--v-theme-success));
+}
+.fc-tag-chip__confirm:hover { background: rgb(var(--v-theme-success), 0.14); }
+.fc-tag-chip__confirm:focus-visible {
+  outline: 2px solid rgb(var(--v-theme-success)); outline-offset: 1px;
+}
 </style>

frontend/src/components/modal/TagPanel.vue

@@ -6,7 +6,7 @@
         v-for="tag in host.current?.tags || []"
         :key="tag.id" :tag="tag" :image-id="host.currentImageId"
         @remove="onRemove" @rename="openRename" @set-fandom="openSetFandom"
-        @navigate="onNavigate"
+        @navigate="onNavigate" @confirm="onConfirm"
       />
       <span v-if="!host.current?.tags?.length" class="text-caption">No tags yet.</span>
     </div>
@@ -65,6 +65,7 @@
 <script setup>
 import { ref } from 'vue'
 import { useRouter } from 'vue-router'
+import { useApi } from '../../composables/useApi.js'
 import { useModalStore } from '../../stores/modal.js'
 import { useSuggestionsStore } from '../../stores/suggestions.js'
 import TagChip from './TagChip.vue'
@@ -83,6 +84,7 @@ const modalStore = useModalStore()
 const host = props.host || modalStore
 const suggestions = useSuggestionsStore()
 const router = useRouter()
+const api = useApi()
 const errorMsg = ref(null)
 const tagInputRef = ref(null)
 
@@ -106,6 +108,18 @@ defineExpose({ focusTagInput })
 // Every tag mutation hands focus back to the input so the operator can keep
 // typing the next tag without re-clicking — matches the accept-suggestion flow
 // (operator-asked 2026-06-26; the Explore workspace leans on this hard).
+// Confirm/keep an auto-applied tag (milestone 139): records the affirmation so
+// the tag becomes a training positive AND is shielded from the retraction sweep,
+// then reloads so the chip drops its "auto" badge + Keep button.
+async function onConfirm(tag) {
+  errorMsg.value = null
+  try {
+    await api.post(`/api/images/${host.currentImageId}/tags/${tag.id}/confirm`)
+    await host.reloadTags()
+  }
+  catch (e) { errorMsg.value = e.message }
+}
+
 async function onRemove(tagId) {
   errorMsg.value = null
   try {

frontend/src/components/posts/PostCard.vue

@@ -200,13 +200,13 @@ async function fullImageIds () {
 }
 
 async function openModal (imageId) {
-  modal.open(imageId, { postImageIds: await fullImageIds() })
+  modal.open(imageId, { playlistIds: await fullImageIds() })
 }
 
 async function openModalAtMore () {
   const ids = await fullImageIds()
   const first = ids[visibleCount.value] ?? ids[0]
-  if (first != null) modal.open(first, { postImageIds: ids })
+  if (first != null) modal.open(first, { playlistIds: ids })
 }
 
 // --- description "Show more" (text-only, in place, only when truncated) ----

frontend/src/stores/modal.js

@@ -17,12 +17,13 @@ export const useModalStore = defineStore('modal', () => {
   // chip rail. Audit 2026-06-02.
   const inflight = useInflightToken()
 
-  // Post-scoped cycle. When set, prev/next cycles within this array
-  // (used by PostCard image clicks — the modal is scoped to that post's
-  // images). When null, prev/next falls back to current.value.neighbors
-  // (the gallery-store-driven /api/gallery/image/<id> neighbors).
-  const postImageIds = ref(null)
-  const postImageIndex = ref(0)
+  // Scoped playlist. When set, prev/next cycles within THIS ordered id array —
+  // the current gallery filter (GalleryView) or a post's images (PostCard) — so
+  // the modal walks exactly what the user was looking at, not a global order.
+  // When null, prev/next falls back to current.value.neighbors (the
+  // /api/gallery/image/<id> global neighbours).
+  const playlistIds = ref(null)
+  const playlistIndex = ref(0)
 
   async function open (id, opts = {}) {
     // Cancel any in-flight tag mutation or reloadTags from the
@@ -32,13 +33,13 @@ export const useModalStore = defineStore('modal', () => {
     current.value = null  // cleared upfront so it stays null on error
     // Update post-scoped state if caller passed it; otherwise clear so
     // the next open() from gallery context uses neighbors mode.
-    if (opts.postImageIds != null) {
-      postImageIds.value = opts.postImageIds
-      postImageIndex.value = opts.postImageIds.indexOf(id)
-      if (postImageIndex.value < 0) postImageIndex.value = 0
-    } else if (opts.clearPostScope !== false && postImageIds.value != null) {
-      postImageIds.value = null
-      postImageIndex.value = 0
+    if (opts.playlistIds != null) {
+      playlistIds.value = opts.playlistIds
+      playlistIndex.value = opts.playlistIds.indexOf(id)
+      if (playlistIndex.value < 0) playlistIndex.value = 0
+    } else if (opts.clearPlaylist !== false && playlistIds.value != null) {
+      playlistIds.value = null
+      playlistIndex.value = 0
     }
     const t = inflight.claim()
     await run(async () => {
@@ -53,17 +54,17 @@ export const useModalStore = defineStore('modal', () => {
     currentImageId.value = null
     current.value = null
     error.value = null
-    postImageIds.value = null
-    postImageIndex.value = 0
+    playlistIds.value = null
+    playlistIndex.value = 0
   }
 
   async function goPrev () {
-    if (postImageIds.value != null) {
-      if (postImageIndex.value > 0) {
-        const newIdx = postImageIndex.value - 1
-        const newId = postImageIds.value[newIdx]
-        postImageIndex.value = newIdx
-        await open(newId, { postImageIds: postImageIds.value })
+    if (playlistIds.value != null) {
+      if (playlistIndex.value > 0) {
+        const newIdx = playlistIndex.value - 1
+        const newId = playlistIds.value[newIdx]
+        playlistIndex.value = newIdx
+        await open(newId, { playlistIds: playlistIds.value })
       }
       return
     }
@@ -73,12 +74,12 @@ export const useModalStore = defineStore('modal', () => {
   }
 
   async function goNext () {
-    if (postImageIds.value != null) {
-      if (postImageIndex.value < postImageIds.value.length - 1) {
-        const newIdx = postImageIndex.value + 1
-        const newId = postImageIds.value[newIdx]
-        postImageIndex.value = newIdx
-        await open(newId, { postImageIds: postImageIds.value })
+    if (playlistIds.value != null) {
+      if (playlistIndex.value < playlistIds.value.length - 1) {
+        const newIdx = playlistIndex.value + 1
+        const newId = playlistIds.value[newIdx]
+        playlistIndex.value = newIdx
+        await open(newId, { playlistIds: playlistIds.value })
       }
       return
     }
@@ -177,19 +178,19 @@ export const useModalStore = defineStore('modal', () => {
 
   const isOpen = computed(() => currentImageId.value !== null)
   const canPrev = computed(() => {
-    if (postImageIds.value != null) return postImageIndex.value > 0
+    if (playlistIds.value != null) return playlistIndex.value > 0
     return current.value?.neighbors?.prev_id != null
   })
   const canNext = computed(() => {
-    if (postImageIds.value != null) {
-      return postImageIndex.value < (postImageIds.value.length - 1)
+    if (playlistIds.value != null) {
+      return playlistIndex.value < (playlistIds.value.length - 1)
     }
     return current.value?.neighbors?.next_id != null
   })
 
   return {
     currentImageId, current, loading, error,
-    postImageIds, postImageIndex,
+    playlistIds, playlistIndex,
     isOpen, canPrev, canNext,
     open, close, goPrev, goNext,
     reloadTags, removeTag, addExistingTag, createAndAdd,

frontend/src/stores/suggestions.js

@@ -218,6 +218,29 @@ export const useSuggestionsStore = defineStore('suggestions', () => {
     }
   }
 
+  // Reject every still-unhandled suggestion in a category in one go ("confirm
+  // the good ones, reject the rest" — operator-asked 2026-07-06). Canonical tags
+  // persist a rejection and STAY flagged rejected (reversible, one-click
+  // un-reject); raw creates-new-tag rows drop client-side. Dispatched in parallel
+  // so a big section clears fast.
+  async function dismissRemaining(category) {
+    const imageId = currentImageId
+    if (imageId == null) return
+    const targets = (byCategory.value[category] || []).filter((s) => !s.rejected)
+    if (!targets.length) return
+    const canon = targets.filter((s) => s.canonical_tag_id != null)
+    const raw = targets.filter((s) => s.canonical_tag_id == null)
+    await Promise.all(canon.map((s) =>
+      api.post(`/api/images/${imageId}/suggestions/dismiss`, {
+        body: { tag_id: s.canonical_tag_id },
+      })
+    ))
+    if (currentImageId === imageId) {
+      canon.forEach((s) => _setRejectedEverywhere(s, true))
+      raw.forEach((s) => _dropEverywhere(s))
+    }
+  }
+
   // Undo a per-image dismissal — the suggestion reverts to a live row.
   async function undismiss(suggestion) {
     const imageId = currentImageId
@@ -232,7 +255,7 @@ export const useSuggestionsStore = defineStore('suggestions', () => {
 
   return {
     byCategory, allByCategory, loading, error,
-    load, loadAll, accept, aliasAccept, removeAlias, dismiss, undismiss,
-    findPending
+    load, loadAll, accept, aliasAccept, removeAlias, dismiss, dismissRemaining,
+    undismiss, findPending
   }
 })

frontend/src/views/GalleryView.vue

@@ -54,7 +54,10 @@ watch(() => route.query, (q) => {
 })
 
 function openImage(id) {
-  modal.open(id)
+  // Walk the current gallery filter in the modal (#1322) — prev/next moves
+  // through exactly the filtered set the operator is viewing, not global
+  // neighbours. Snapshot of the currently-loaded, filtered, ordered ids.
+  modal.open(id, { playlistIds: store.images.map((i) => i.id) })
 }
 </script>
 

frontend/test/components/postCard.spec.js

@@ -80,6 +80,6 @@ describe('PostCard', () => {
     const w = mountComponent(PostCard, { props: { post }, pinia })
     await w.find('.fc-post-card__hero').trigger('click')
     await flushPromises()
-    expect(openSpy).toHaveBeenCalledWith(10, { postImageIds: [10, 11] })
+    expect(openSpy).toHaveBeenCalledWith(10, { playlistIds: [10, 11] })
   })
 })

tests/test_api_tags.py

@@ -141,6 +141,38 @@ async def test_applied_tag_grounding_returns_winning_region(client, db):
     assert body["grounding"]["kind"] == "concept"
 
 
+@pytest.mark.asyncio
+async def test_applied_tags_expose_source_and_confirmed(client, db):
+    # The chip UI needs each applied tag's source (auto vs manual) + confirmed
+    # state to badge auto-tags and offer Keep/confirm (milestone 139).
+    from backend.app.models import TagPositiveConfirmation
+    from backend.app.models.tag import image_tag
+
+    img = ImageRecord(
+        path="/images/srcflag.jpg", sha256="sf" * 32, size_bytes=1,
+        mime="image/jpeg", width=1, height=1, origin="imported_filesystem",
+        integrity_status="unknown",
+    )
+    db.add(img)
+    await db.flush()
+    auto = await TagService(db).find_or_create("autotag", TagKind.general)
+    manual = await TagService(db).find_or_create("manualtag", TagKind.general)
+    await db.execute(image_tag.insert().values(
+        image_record_id=img.id, tag_id=auto.id, source="head_auto"))
+    await db.execute(image_tag.insert().values(
+        image_record_id=img.id, tag_id=manual.id, source="manual"))
+    db.add(TagPositiveConfirmation(image_record_id=img.id, tag_id=manual.id))
+    await db.commit()
+
+    resp = await client.get(f"/api/images/{img.id}/tags")
+    assert resp.status_code == 200
+    by_id = {t["id"]: t for t in await resp.get_json()}
+    assert by_id[auto.id]["source"] == "head_auto"
+    assert by_id[auto.id]["confirmed"] is False
+    assert by_id[manual.id]["source"] == "manual"
+    assert by_id[manual.id]["confirmed"] is True     # has a confirmation row
+
+
 @pytest.mark.asyncio
 async def test_applied_tag_grounding_no_head(client, db):
     # A tag with no head can't be localized → has_head False, grounding null; the

tests/test_character_prototypes.py

@@ -12,6 +12,7 @@ from backend.app.models import (
     MLSettings,
     Tag,
     TagKind,
+    TagPositiveConfirmation,
 )
 from backend.app.models.tag import image_tag
 from backend.app.services.ml.character_prototypes import (
@@ -141,6 +142,27 @@ def test_multi_character_image_not_referenced(db_sync):
     assert _proto_count(db_sync, daphne.id) == 0
 
 
+def test_unconfirmed_auto_char_tag_not_referenced(db_sync):
+    # A single-character image whose ONLY character tag was AUTO-applied
+    # (unconfirmed) must NOT seed a prototype — else CCIP self-trains on its own
+    # guess (milestone 139). Confirming it (which trips the global gate) makes it
+    # a reference.
+    raven = _char(db_sync, "Raven")
+    img = _img(db_sync, "z" * 64)
+    _figure(db_sync, img.id)
+    db_sync.execute(image_tag.insert().values(
+        image_record_id=img.id, tag_id=raven.id, source="ccip_auto",
+    ))
+    db_sync.commit()
+    refresh_character_prototypes(db_sync)
+    assert _proto_count(db_sync, raven.id) == 0
+
+    db_sync.add(TagPositiveConfirmation(image_record_id=img.id, tag_id=raven.id))
+    db_sync.commit()
+    refresh_character_prototypes(db_sync)
+    assert _proto_count(db_sync, raven.id) == 1
+
+
 def test_lost_references_are_removed(db_sync):
     raven = _char(db_sync, "Raven")
     img = _img(db_sync, "e" * 64)

tests/test_head_auto_apply.py

@@ -35,7 +35,7 @@ def _img(db, sha: str, emb) -> ImageRecord:
     return img
 
 
-def _head(db, tag_id: int, slot: int, *, threshold=0.5, n_pos=30):
+def _head(db, tag_id: int, slot: int, *, threshold=0.5, n_pos=60):
     s = db.execute(select(MLSettings).where(MLSettings.id == 1)).scalar_one()
     w = [0.0] * 1152
     w[slot] = 1.0
@@ -88,7 +88,7 @@ def test_sweep_dry_run_counts_but_writes_nothing(db_sync):
 
 
 def test_sweep_skips_under_supported_head(db_sync):
-    # n_pos below head_auto_apply_min_positives (default 30) → a precise-looking
+    # n_pos below head_auto_apply_min_positives (default 50) → a precise-looking
     # but under-supported head never fires.
     img = _img(db_sync, "c" * 64, _emb(0))
     tag = Tag(name="weaktag", kind=TagKind.general)

tests/test_head_positive_sources.py

@@ -0,0 +1,69 @@
+"""Soft auto-apply (milestone 139): unconfirmed auto-applied tags do NOT train a
+head. _ids_with_tag (positives) + _eligible_tag_ids (graduation count) count
+human-applied + operator-confirmed tags only. Sklearn-free, so tested via
+db_sync."""
+import pytest
+
+from backend.app.models import ImageRecord, Tag, TagKind, TagPositiveConfirmation
+from backend.app.models.tag import image_tag
+from backend.app.services.ml.heads import _eligible_tag_ids
+from backend.app.services.ml.training_data import _ids_with_tag
+
+pytestmark = pytest.mark.integration
+
+
+def _img(db, sha: str) -> ImageRecord:
+    img = ImageRecord(
+        path=f"/images/{sha}.jpg", sha256=sha, size_bytes=1, mime="image/jpeg",
+        width=1, height=1, origin="imported_filesystem",
+        integrity_status="unknown",
+    )
+    db.add(img)
+    db.flush()
+    return img
+
+
+def _tag(db, name: str) -> Tag:
+    t = Tag(name=name, kind=TagKind.general)
+    db.add(t)
+    db.flush()
+    return t
+
+
+def _apply(db, image_id: int, tag_id: int, source: str) -> None:
+    db.execute(image_tag.insert().values(
+        image_record_id=image_id, tag_id=tag_id, source=source,
+    ))
+
+
+def test_positives_exclude_unconfirmed_auto(db_sync):
+    tag = _tag(db_sync, "glasses")
+    man = _img(db_sync, "a" * 64)
+    auto = _img(db_sync, "b" * 64)
+    conf = _img(db_sync, "c" * 64)
+    acc = _img(db_sync, "d" * 64)
+    _apply(db_sync, man.id, tag.id, "manual")
+    _apply(db_sync, auto.id, tag.id, "head_auto")     # unconfirmed → excluded
+    _apply(db_sync, conf.id, tag.id, "head_auto")     # confirmed → included
+    _apply(db_sync, acc.id, tag.id, "ml_accepted")
+    db_sync.add(TagPositiveConfirmation(image_record_id=conf.id, tag_id=tag.id))
+    db_sync.commit()
+
+    pos = set(_ids_with_tag(db_sync, tag.id))
+    assert pos == {man.id, conf.id, acc.id}
+    assert auto.id not in pos
+
+
+def test_eligibility_counts_positives_only(db_sync):
+    # A concept whose only tags are unconfirmed auto-applies does NOT graduate.
+    tag = _tag(db_sync, "autotag")
+    for i in range(3):
+        _apply(db_sync, _img(db_sync, f"e{i}" * 32).id, tag.id, "head_auto")
+    db_sync.commit()
+    assert tag.id not in _eligible_tag_ids(db_sync, min_pos=2)
+
+    # Two human positives → now eligible at min_pos=2.
+    for i in range(2):
+        _apply(db_sync, _img(db_sync, f"h{i}" * 32).id, tag.id, "manual")
+    db_sync.commit()
+    assert tag.id in _eligible_tag_ids(db_sync, min_pos=2)

tests/test_retract_auto_apply.py

@@ -0,0 +1,153 @@
+"""Soft auto-apply (milestone 139): the retraction sweeps drop standing
+head_auto/ccip_auto tags now below their threshold, keep the ones still above,
+and never touch manual or operator-confirmed tags. Sync + sklearn-free (they
+score with STORED weights/vectors), so tested directly via db_sync."""
+import pytest
+from sqlalchemy import select
+
+from backend.app.models import (
+    CharacterPrototype,
+    ImageRecord,
+    ImageRegion,
+    MLSettings,
+    Tag,
+    TagHead,
+    TagKind,
+    TagPositiveConfirmation,
+)
+from backend.app.models.tag import image_tag
+from backend.app.services.ml.character_prototypes import retract_auto_applied_ccip
+from backend.app.services.ml.heads import retract_auto_applied_heads
+
+pytestmark = pytest.mark.integration
+
+
+def _emb(slot: int) -> list[float]:
+    v = [0.0] * 1152
+    v[slot] = 3.0
+    return v
+
+
+def _ccip(slot: int) -> list[float]:
+    v = [0.0] * 768
+    v[slot] = 1.0
+    return v
+
+
+def _img(db, sha: str, emb=None) -> ImageRecord:
+    img = ImageRecord(
+        path=f"/images/{sha}.jpg", sha256=sha, size_bytes=1, mime="image/jpeg",
+        width=1, height=1, origin="imported_filesystem",
+        integrity_status="unknown", siglip_embedding=emb,
+    )
+    db.add(img)
+    db.flush()
+    return img
+
+
+def _figure(db, image_id: int, ccip) -> None:
+    db.add(ImageRegion(
+        image_record_id=image_id, kind="figure",
+        rx=0.0, ry=0.0, rw=1.0, rh=1.0,
+        ccip_embedding=ccip, embedding_version="ccip-test",
+    ))
+    db.flush()
+
+
+def _tag(db, name: str, kind: TagKind) -> Tag:
+    t = Tag(name=name, kind=kind)
+    db.add(t)
+    db.flush()
+    return t
+
+
+def _apply(db, image_id: int, tag_id: int, source: str) -> None:
+    db.execute(image_tag.insert().values(
+        image_record_id=image_id, tag_id=tag_id, source=source,
+    ))
+
+
+def _version(db) -> str:
+    return db.execute(
+        select(MLSettings.embedder_model_version).where(MLSettings.id == 1)
+    ).scalar_one()
+
+
+def _head(db, tag_id: int, slot: int, threshold: float, version: str) -> None:
+    w = [0.0] * 1152
+    w[slot] = 1.0
+    db.add(TagHead(
+        tag_id=tag_id, embedding_version=version, weights=w, bias=0.0,
+        suggest_threshold=0.5, auto_apply_threshold=threshold,
+        n_pos=60, n_neg=180, ap=0.9, precision_cv=0.98, recall=0.7,
+    ))
+    db.flush()
+
+
+def _has_tag(db, image_id: int, tag_id: int) -> bool:
+    return db.execute(
+        select(image_tag.c.tag_id)
+        .where(image_tag.c.image_record_id == image_id)
+        .where(image_tag.c.tag_id == tag_id)
+    ).first() is not None
+
+
+def test_retract_head_auto(db_sync):
+    ver = _version(db_sync)
+    tag = _tag(db_sync, "glasses", TagKind.general)
+    _head(db_sync, tag.id, slot=0, threshold=0.7, version=ver)
+    hi = _img(db_sync, "a" * 64, _emb(0))     # aligned → ~0.73 ≥ 0.7 → keep
+    lo = _img(db_sync, "b" * 64, _emb(5))     # orthogonal → 0.5 < 0.7 → retract
+    man = _img(db_sync, "c" * 64, _emb(5))    # low score but manual → keep
+    conf = _img(db_sync, "d" * 64, _emb(5))   # low score, head_auto, CONFIRMED → keep
+    _apply(db_sync, hi.id, tag.id, "head_auto")
+    _apply(db_sync, lo.id, tag.id, "head_auto")
+    _apply(db_sync, man.id, tag.id, "manual")
+    _apply(db_sync, conf.id, tag.id, "head_auto")
+    db_sync.add(TagPositiveConfirmation(image_record_id=conf.id, tag_id=tag.id))
+    db_sync.commit()
+
+    assert retract_auto_applied_heads(db_sync) == 1
+    assert not _has_tag(db_sync, lo.id, tag.id)     # retracted (below threshold)
+    assert _has_tag(db_sync, hi.id, tag.id)         # kept (still above)
+    assert _has_tag(db_sync, man.id, tag.id)        # kept (manual, not auto)
+    assert _has_tag(db_sync, conf.id, tag.id)       # kept (operator-confirmed)
+
+
+def test_retract_head_auto_noop_when_disabled(db_sync):
+    s = db_sync.execute(select(MLSettings).where(MLSettings.id == 1)).scalar_one()
+    s.head_auto_apply_enabled = False
+    ver = _version(db_sync)
+    tag = _tag(db_sync, "glasses", TagKind.general)
+    _head(db_sync, tag.id, slot=0, threshold=0.7, version=ver)
+    lo = _img(db_sync, "e" * 64, _emb(5))     # would be below threshold
+    _apply(db_sync, lo.id, tag.id, "head_auto")
+    db_sync.commit()
+
+    assert retract_auto_applied_heads(db_sync) == 0
+    assert _has_tag(db_sync, lo.id, tag.id)         # switch off → nothing retracted
+
+
+def test_retract_ccip_auto(db_sync):
+    char = _tag(db_sync, "Raven", TagKind.character)
+    db_sync.add(CharacterPrototype(tag_id=char.id, ccip_embedding=_ccip(0)))
+    hi = _img(db_sync, "f" * 64)              # figure matches prototype → keep
+    lo = _img(db_sync, "g" * 64)             # figure orthogonal → retract
+    conf = _img(db_sync, "h" * 64)           # orthogonal, CONFIRMED → keep
+    man = _img(db_sync, "i" * 64)            # orthogonal, manual → keep
+    _figure(db_sync, hi.id, _ccip(0))
+    _figure(db_sync, lo.id, _ccip(5))
+    _figure(db_sync, conf.id, _ccip(5))
+    _figure(db_sync, man.id, _ccip(5))
+    _apply(db_sync, hi.id, char.id, "ccip_auto")
+    _apply(db_sync, lo.id, char.id, "ccip_auto")
+    _apply(db_sync, conf.id, char.id, "ccip_auto")
+    _apply(db_sync, man.id, char.id, "manual")
+    db_sync.add(TagPositiveConfirmation(image_record_id=conf.id, tag_id=char.id))
+    db_sync.commit()
+
+    assert retract_auto_applied_ccip(db_sync) == 1
+    assert not _has_tag(db_sync, lo.id, char.id)    # retracted (below threshold)
+    assert _has_tag(db_sync, hi.id, char.id)        # kept (match ≥ threshold)
+    assert _has_tag(db_sync, conf.id, char.id)      # kept (operator-confirmed)
+    assert _has_tag(db_sync, man.id, char.id)       # kept (manual, not auto)

tests/test_tag_query.py

@@ -15,6 +15,8 @@ def test_serialize_tag_with_enum_kind():
     assert serialize_tag(row) == {
         "id": 1, "name": "Sasuke Uchiha", "kind": "character",
         "fandom_id": 5, "fandom_name": "Naruto", "is_system": False,
+        # Applied-tag context defaults for rows without image scope (m139).
+        "source": None, "confirmed": False,
     }
 
 
@@ -27,6 +29,7 @@ def test_serialize_tag_with_string_kind_and_no_fandom():
     assert serialize_tag(row) == {
         "id": 2, "name": "solo", "kind": "general",
         "fandom_id": None, "fandom_name": None, "is_system": False,
+        "source": None, "confirmed": False,
     }