feat(suggestions): auto-accept threshold + retroactive blocklist sweep
Two capabilities that work together to turn the suggestion system from
a 'review every noisy chip' UX into a 'curated tags only, configurable
auto-apply' UX for a solo-user library.
Auto-accept threshold
Service (tag_suggestions.py):
- New default auto_accept_general_threshold = 0.95 in _DEFAULTS
- get_suggestions splits general-category hits at/above the threshold
into a separate auto_accept_candidates list; the core 'character'/
'copyright'/'general' keys stay the same shape for existing callers
- get_bulk_suggestions ignores the new key (no side effects in bulk)
Route (main.py GET /image/<id>/suggestions):
- For each candidate: find-or-create Tag(kind='user', name=name), attach
to image, log SuggestionFeedback(source='wd14'|etc, decision='accepted')
- Response adds 'auto_accepted: [{id, name, display_name, kind,
confidence, source}, ...]' so the modal can review + undo
Config endpoints (main.py):
GET /api/suggestions/config/auto-accept-threshold
POST /api/suggestions/config/auto-accept-threshold {threshold}
Values > 1.0 effectively disable the feature
UI (view-modal.js):
- New renderAutoAccepted block at top of suggestions section with
green-tinted chips carrying ✕ (undo for this image, logs rejection)
and ⊘ (blocklist + remove from all images)
- loadSuggestions refreshes the tag pill list when auto_accepted has
items so the user sees them in the Tags section too
Settings:
- Maintenance tab gains a number input + save button backed by
/api/suggestions/config/auto-accept-threshold
Retroactive blocklist sweep
New Celery task app.tasks.maintenance.sweep_blocklisted_tag_from_images
on the maintenance queue. Enqueued automatically when a name is added
via POST /api/suggestions/blocklist or appears new in the bulk replace.
Task body: finds kind='user' Tag matching the name, deletes its
image_tags rows, deletes the Tag itself. Scope limited to kind='user'
so deliberate character/fandom/artist tags sharing a blocklisted name
aren't silently destroyed.
Verification (local dev):
- Threshold GET/POST round-trip correct (default 0.95, persisted in
tag_suggestion_config)
- Image 633 at threshold=0.9: 4 general tags auto-applied, each with
a SuggestionFeedback row, returned in auto_accepted
- Blocklist add of 'sweeptestonly' with an attached test tag: Redis
maintenance queue depth = 1, task body removes 1 image_tags row +
the Tag row
- get_bulk_suggestions still works (auto_accept_candidates key skipped)
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
@@ -242,13 +242,109 @@ document.addEventListener('DOMContentLoaded', () => {
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try {
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const r = await fetch(`/image/${imageId}/suggestions`);
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const j = await r.json();
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if (j.ok) renderSuggestions(j.suggestions || {}, imageId);
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else clearSuggestions();
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if (!j.ok) { clearSuggestions(); return; }
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// Render regular suggestions first — it wipes innerHTML. Then prepend
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// the auto-accepted block so both coexist.
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renderSuggestions(j.suggestions || {}, imageId);
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renderAutoAccepted(j.auto_accepted || [], imageId);
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if ((j.auto_accepted || []).length > 0) {
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suggestionsSection.style.display = '';
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}
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// Auto-accepted tags are now attached to the image — refresh the
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// pill list so the user sees them in the Tags section.
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if ((j.auto_accepted || []).length > 0 && typeof loadTags === 'function') {
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await loadTags(imageId);
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}
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} catch {
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clearSuggestions();
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}
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}
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function renderAutoAccepted(items, imageId) {
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if (!suggestionsList) return;
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// Remove any prior auto-accepted block from the current modal view.
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suggestionsList.querySelectorAll('.suggestions-auto-accepted').forEach(el => el.remove());
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if (!items || items.length === 0) return;
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const block = document.createElement('div');
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block.className = 'suggestions-auto-accepted';
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const label = document.createElement('div');
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label.className = 'suggestions-category-label';
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label.textContent = `Auto-accepted (${items.length})`;
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block.appendChild(label);
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const chips = document.createElement('div');
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chips.className = 'suggestions-chips';
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for (const item of items) {
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chips.appendChild(buildAutoAcceptedChip(item, imageId));
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}
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block.appendChild(chips);
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suggestionsList.prepend(block);
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}
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function buildAutoAcceptedChip(item, imageId) {
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const chip = document.createElement('div');
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chip.className = 'suggestion-chip suggestion-chip-auto';
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chip.dataset.tagId = String(item.id);
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chip.dataset.tagName = item.name;
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chip.dataset.source = item.source || 'wd14';
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chip.dataset.confidence = String(item.confidence || 0);
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chip.title = `Auto-accepted from ${item.source || 'wd14'} at ${Math.round((item.confidence || 0) * 100)}%`;
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const pct = Math.round((item.confidence || 0) * 100);
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chip.innerHTML = `
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<span class="sugg-body">
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<span class="sugg-label">${escapeHtml(item.display_name || item.name)}</span>
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<span class="sugg-confidence">${pct}%</span>
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</span>
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<button type="button" class="sugg-btn sugg-undo" aria-label="Undo (remove from this image)" title="Remove from this image">✕</button>
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<button type="button" class="sugg-btn sugg-block" aria-label="Blocklist this tag" title="Never suggest '${escapeHtml(item.name)}' again — removes from all images">⊘</button>
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`;
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chip.querySelector('.sugg-undo')?.addEventListener('click', () => undoAutoAccepted(chip, imageId));
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chip.querySelector('.sugg-block')?.addEventListener('click', () => blocklistSuggestion(chip, imageId));
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return chip;
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}
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async function undoAutoAccepted(chip, imageId) {
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if (chip.dataset.disabled === 'true') return;
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chip.dataset.disabled = 'true';
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chip.style.pointerEvents = 'none';
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const name = chip.dataset.tagName;
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try {
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// Remove the tag from this image (uses the same remove endpoint the
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// manual tag-pill '×' button uses).
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const fd = new FormData();
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fd.append('name', name);
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const r = await fetch(`/image/${imageId}/tags/remove`, { method: 'POST', body: fd });
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const j = await r.json();
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if (!j.ok) {
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chip.dataset.disabled = 'false';
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chip.style.pointerEvents = '';
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if (tagActionFeedback) tagActionFeedback.textContent = `Couldn't undo: ${j.error || 'error'}`;
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return;
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}
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// Log the rejection for ML feedback so future threshold tuning sees this.
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try {
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await fetch(`/image/${imageId}/suggestions/reject`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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tag_name: name,
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source: chip.dataset.source || 'wd14',
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confidence: Number(chip.dataset.confidence) || 0,
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}),
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});
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} catch {
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// best-effort
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}
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if (tagActionFeedback) tagActionFeedback.textContent = `Removed '${name}'`;
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animateChipOut(chip);
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if (typeof loadTags === 'function') loadTags(imageId);
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} catch {
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chip.dataset.disabled = 'false';
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chip.style.pointerEvents = '';
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}
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}
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function animateChipOut(chip) {
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chip.classList.add('leaving');
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setTimeout(() => { chip.remove(); }, 200);
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+40
-1
@@ -1020,7 +1020,46 @@ header {
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border-color: rgba(255, 180, 0, 0.6);
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}
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/* Settings: blocklist textarea */
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/* Auto-accepted suggestion block (top of suggestions section) */
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.suggestions-auto-accepted {
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margin-bottom: 0.75rem;
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padding: 0.5rem;
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background: rgba(139, 231, 139, 0.04);
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border: 1px solid rgba(139, 231, 139, 0.2);
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border-radius: 6px;
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}
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.suggestions-auto-accepted .suggestions-category-label {
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color: #8be78b;
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font-weight: 600;
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}
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.suggestion-chip.suggestion-chip-auto {
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border-color: rgba(139, 231, 139, 0.3);
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background: rgba(139, 231, 139, 0.08);
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}
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.suggestion-chip .sugg-btn.sugg-undo {
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color: #e78b8b;
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border-color: rgba(231, 139, 139, 0.35);
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}
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.suggestion-chip .sugg-btn.sugg-undo:hover {
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background: rgba(231, 139, 139, 0.12);
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border-color: rgba(231, 139, 139, 0.6);
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}
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/* Settings: threshold number input + blocklist textarea */
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.settings-input {
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padding: 0.4rem 0.6rem;
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border: 1px solid rgba(255, 255, 255, 0.2);
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border-radius: 6px;
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background: rgba(255, 255, 255, 0.08);
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color: var(--text);
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font-size: 0.95rem;
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}
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.settings-input:focus {
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outline: none;
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border-color: var(--btn-primary);
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background: rgba(255, 255, 255, 0.12);
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}
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.settings-textarea {
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width: 100%;
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padding: 0.5rem 0.75rem;
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