feat: retire the sketch/doodle WIP title tier, and the review strip asks "Is this a WIP?" (milestone 430)
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The soft tier (#1474) tagged `wip` on any post titled sketch, doodle or scribble: 6,096 of the library's 8,876 wip tags. Its conflict audit flagged most of them, because finished art scores >= 0.5 on some content head, which filled the Gallery strip with 2,086 cards. A "sketch" is usually finished work, so the operator retired the tier. The artist's own "WIP" / "work in progress" title rule and human wip tags stay. - Removed: the soft matcher, source and prefilter; the importer and backfill soft branches; soft_wip_conflict_audit with its task and beat; the wip_soft_title_tagging_enabled setting, API field and toggle; and wip_title_soft from _AUTO_SOURCES. - Migration 0112: a soft tag the operator confirmed, or kept from the strip, becomes `manual`. Every other soft tag is deleted, along with the open review cards whose tag is gone. The column is dropped. - Review strip (#4424): each card asks "Is this a WIP?" (or banner, and so on), and the buttons read "Is a WIP" / "Is not a WIP". The content tag it also scored on is shown as the reason it was flagged. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR
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@@ -97,8 +97,8 @@ def _sigmoid(z, np):
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def _conflict_scores(Xn, Wc, bc, np):
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"""The presentation conflict signal (#141): per row, the MAX content-head
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probability and WHICH head produced it. Shared by the system-tag sweep's guard-2
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and the soft-wip audit — both ask "does this ALSO look like real content?"."""
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probability and WHICH head produced it — the system-tag sweep's guard-2 asks
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"does this ALSO look like real content?"."""
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cprobs = _sigmoid(Xn @ Wc.T + bc, np)
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return cprobs.max(axis=1), cprobs.argmax(axis=1)
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@@ -106,10 +106,9 @@ def _conflict_scores(Xn, Wc, bc, np):
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def _insert_presentation_review(
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session, *, image_record_id, tag_id, conflict_tag_id, conflict_score, mode,
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):
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"""Single-source the ring-loud PresentationReview row shape so the two writers
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(system-tag sweep guard-2 + soft-wip audit) can't drift on columns or `mode` —
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they share the (image_record_id, tag_id) composite PK, so a divergent `mode`
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would be a silent first-writer-wins bug."""
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"""Single-source the ring-loud PresentationReview row shape, so every writer of
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the (image_record_id, tag_id) composite PK agrees on columns and `mode` — a
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divergent `mode` would be a silent first-writer-wins bug."""
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session.execute(
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pg_insert(PresentationReview)
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.values(
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@@ -963,68 +962,6 @@ def system_tag_auto_apply_sweep(
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}
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def soft_wip_conflict_audit(session: Session, dry_run: bool = False) -> dict:
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"""Ring-loud audit for the SOFT WIP-title cohort (#1474). Images auto-tagged
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`wip` from a low-precision sketch/doodle title (source='wip_title_soft') that ALSO
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score >= the process conflict threshold on a content head are probably FINISHED
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art mis-tagged as process — flag them (PresentationReview, mode='process') so the
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review strip surfaces them ("also looks like <X>", Keep tag / Remove tag). Does
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NOT remove the tag; the operator decides. No-op when there are no content heads.
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numpy-only. Returns {n_scanned, n_flagged}."""
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import numpy as np
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from ..wip_title import WIP_TITLE_SOFT_SOURCE, resolve_wip_tag_id
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settings = _settings(session)
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ver = settings.embedder_model_version
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conflict_thr = float(settings.process_conflict_threshold)
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conf = _conflict_heads(session, ver)
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wip_id = resolve_wip_tag_id(session)
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if not conf or wip_id is None:
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return {"n_scanned": 0, "n_flagged": 0}
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Wc = np.vstack([np.asarray(r.weights, dtype=np.float32) for r in conf])
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bc = np.asarray([r.bias for r in conf], dtype=np.float32)
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conf_tag_ids = [r.tag_id for r in conf]
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soft_ids = [iid for (iid,) in session.execute(
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select(image_tag.c.image_record_id)
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.where(image_tag.c.tag_id == wip_id)
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.where(image_tag.c.source == WIP_TITLE_SOFT_SOURCE)
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)]
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# Skip images already flagged for this tag (idempotent re-runs).
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flagged = {iid for (iid,) in session.execute(
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select(PresentationReview.image_record_id)
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.where(PresentationReview.tag_id == wip_id)
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)}
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soft_ids = [i for i in soft_ids if i not in flagged]
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n_flagged = 0
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scanned = 0
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for start in range(0, len(soft_ids), _AUTO_APPLY_CHUNK):
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chunk = soft_ids[start:start + _AUTO_APPLY_CHUNK]
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emb = _load_embeddings(session, chunk)
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cids = [i for i in chunk if i in emb]
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if not cids:
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continue
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scanned += len(cids)
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Xn = _l2norm(np.vstack([emb[i] for i in cids]).astype(np.float32), np)
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max_c, arg_c = _conflict_scores(Xn, Wc, bc, np)
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for k in range(len(cids)):
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if float(max_c[k]) >= conflict_thr:
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n_flagged += 1
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if not dry_run:
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_insert_presentation_review(
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session,
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image_record_id=cids[k], tag_id=wip_id,
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conflict_tag_id=conf_tag_ids[int(arg_c[k])],
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conflict_score=float(max_c[k]),
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mode="process",
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)
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if not dry_run:
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session.commit()
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return {"n_scanned": scanned, "n_flagged": n_flagged}
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def retract_auto_applied_heads(session: Session) -> int:
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"""Soft auto-apply (milestone 139): re-score every standing source='head_auto'
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tag against its CURRENT head and REMOVE the ones now BELOW the head's
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