feat(ml): drop image_record.tagger_predictions — image_prediction is sole store (#768 step 3)

Read cutover verified in prod (suggestions + allowlist read image_prediction;
backfill complete at 908k rows / 51k images). Removes the old JSON column and
everything that fed it:

- ImageRecord.tagger_predictions column removed; migration 0046 DROPs it.
  tagger_model_version kept as the "tagged / current?" signal the backfill
  sweep reads (needs-tagging check switched to tagger_model_version IS NULL).
- tag_and_embed no longer dual-writes the JSON — image_prediction is the only
  write path.
- importer re-import reset drops the JSON line (image_prediction rows are
  already deleted on re-import).
- Retired the one-time #768 backfill task + the #764 prune task, their admin
  endpoints, and their Maintenance cards (Backfill/PrunePredictionsCard).
- Tests seed/assert via image_prediction; stale column refs removed.

Disk reclaim is NOT automatic: DROP COLUMN is a catalog change. Run
`VACUUM FULL image_record` off-hours afterward to return the ~100 GB to the OS
so DB backups go small (#739). image_prediction (~90 MB) stays in pg_dump — it's
the source of truth now.

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

frontend/src/components/settings/BackfillPredictionsCard.vue

@@ -1,50 +0,0 @@
-<template>
-  <!-- #768: one-time copy of stored tagger predictions from the
-       image_record.tagger_predictions JSON into the normalized
-       image_prediction table. Migration 0045 creates the empty table; this
-       populates it for the existing library. -->
-  <v-card>
-    <v-card-title>Backfill normalized predictions</v-card-title>
-    <v-card-text>
-      <p class="text-body-2 mb-3">
-        Copies each image's stored tagger predictions into the new
-        <code>image_prediction</code> table (the source the suggestions and
-        allowlist now read from). Run this <strong>once</strong> after the
-        upgrade so existing images get their suggestions back — newly tagged
-        images populate it automatically. Batched, resumable and idempotent;
-        safe to run more than once and to leave running in the background.
-      </p>
-      <v-btn color="primary" rounded="pill" :loading="busy" @click="run">
-        <v-icon start>mdi-database-import-outline</v-icon> Backfill 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 { ref } from 'vue'
-
-import { useApi } from '../../composables/useApi.js'
-import { toast } from '../../utils/toast.js'
-import QueueStatusBar from './QueueStatusBar.vue'
-
-const api = useApi()
-const busy = ref(false)
-const queued = ref(false)
-
-async function run () {
-  busy.value = true
-  queued.value = false
-  try {
-    await api.post('/api/admin/maintenance/backfill-predictions')
-    queued.value = true
-    toast({ text: 'Prediction backfill queued', type: 'success' })
-  } catch (e) {
-    toast({ text: e?.body?.detail || e?.message || 'Failed to queue', type: 'error' })
-  } finally {
-    busy.value = false
-  }
-}
-</script>

frontend/src/components/settings/MaintenancePanel.vue

@@ -12,8 +12,6 @@
       <ThumbnailBackfillCard />
     </div>
     <MLThresholdSliders class="mt-4" />
-    <BackfillPredictionsCard class="mt-4" />
-    <PrunePredictionsCard class="mt-4" />
     <AllowlistTable class="mt-4" />
     <AliasTable class="mt-4" />
     <DbMaintenanceCard class="mt-6" />
@@ -33,8 +31,6 @@ import MLBackfillCard from './MLBackfillCard.vue'
 import CentroidRecomputeCard from './CentroidRecomputeCard.vue'
 import ThumbnailBackfillCard from './ThumbnailBackfillCard.vue'
 import MLThresholdSliders from './MLThresholdSliders.vue'
-import BackfillPredictionsCard from './BackfillPredictionsCard.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

@@ -1,58 +0,0 @@
-<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>