feat(admin): prune_low_confidence_predictions backfill task + UI (#764)

The one-time backfill that actually shrinks the DB: drops stored
tagger_predictions entries below ml_settings.tagger_store_floor from every
image_record row, and clamps any allowlist min_confidence below the floor up
to it. Keep predicate (confidence >= floor) mirrors Tagger.infer's store gate
so backfilled rows match new imports. Keyset by id ASC, idempotent,
self-resumes on the soft time limit; runs on the maintenance_long lane.

pg_dump copies live data only, so this alone fixes the #739 backup timeout —
the reclaim (VACUUM FULL / pg_repack on image_record) is a separate, optional
disk-return step, brief because post-prune the live data is tiny.

- admin.prune_low_confidence_predictions_task + POST /api/admin/maintenance/prune-predictions
- PrunePredictionsCard in the Maintenance panel (shows the current floor)
- tests: registration + prune-keeps->=floor/drops-<floor + allowlist clamp

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

frontend/src/components/settings/MaintenancePanel.vue

@@ -12,6 +12,7 @@
       <ThumbnailBackfillCard />
     </div>
     <MLThresholdSliders class="mt-4" />
+    <PrunePredictionsCard class="mt-4" />
     <AllowlistTable class="mt-4" />
     <AliasTable class="mt-4" />
     <DbMaintenanceCard class="mt-6" />
@@ -31,6 +32,7 @@ import MLBackfillCard from './MLBackfillCard.vue'
 import CentroidRecomputeCard from './CentroidRecomputeCard.vue'
 import ThumbnailBackfillCard from './ThumbnailBackfillCard.vue'
 import MLThresholdSliders from './MLThresholdSliders.vue'
+import PrunePredictionsCard from './PrunePredictionsCard.vue'
 import AllowlistTable from './AllowlistTable.vue'
 import AliasTable from './AliasTable.vue'
 import DbMaintenanceCard from './DbMaintenanceCard.vue'

frontend/src/components/settings/PrunePredictionsCard.vue

@@ -0,0 +1,58 @@
+<template>
+  <!-- #764: drop stored tagger predictions below the store floor to shrink
+       image_record's TOAST (the sub-0.70 score tail had grown it to ~100 GB). -->
+  <v-card>
+    <v-card-title>Prune low-confidence predictions</v-card-title>
+    <v-card-text>
+      <p class="text-body-2 mb-3">
+        Removes stored tagger predictions below the current store floor
+        (<strong>{{ floorPct }}</strong>) from every image, and clamps any
+        allowlist threshold below the floor up to it. This is what shrinks the
+        database — the low-confidence tail was the bulk of its size. Idempotent
+        and resumable; safe to run more than once. Afterward, reclaim the freed
+        space with <code>VACUUM FULL</code> / <code>pg_repack</code> on
+        <code>image_record</code>.
+      </p>
+      <v-btn color="primary" rounded="pill" :loading="busy" @click="run">
+        <v-icon start>mdi-database-minus-outline</v-icon> Prune predictions now
+      </v-btn>
+      <span v-if="queued" class="ml-3 text-caption text-success">Queued ✓</span>
+      <QueueStatusBar queue="maintenance_long" queue-label="Maintenance (long)" />
+    </v-card-text>
+  </v-card>
+</template>
+
+<script setup>
+import { computed, onMounted, ref } from 'vue'
+
+import { useApi } from '../../composables/useApi.js'
+import { toast } from '../../utils/toast.js'
+import { useMLStore } from '../../stores/ml.js'
+import QueueStatusBar from './QueueStatusBar.vue'
+
+const api = useApi()
+const ml = useMLStore()
+const busy = ref(false)
+const queued = ref(false)
+
+const floorPct = computed(() => {
+  const f = ml.settings?.tagger_store_floor
+  return f == null ? '—' : `${Math.round(f * 100)}%`
+})
+
+onMounted(() => { if (!ml.settings) ml.loadSettings() })
+
+async function run () {
+  busy.value = true
+  queued.value = false
+  try {
+    await api.post('/api/admin/maintenance/prune-predictions')
+    queued.value = true
+    toast({ text: 'Prediction prune queued', type: 'success' })
+  } catch (e) {
+    toast({ text: e?.body?.detail || e?.message || 'Failed to queue', type: 'error' })
+  } finally {
+    busy.value = false
+  }
+}
+</script>