refactor: strip AI pipeline to binary photo/other classifier

Drops face recognition, OCR, object detection, and semantic embeddings.
The sole remaining vision task is a CLIP-based binary classifier
(photography vs other); photos in "other" get needs_review=true so
screenshots, documents, memes and scans can be triaged from a new
filter pill in the UI.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

frontend/src/components/dialogs/SettingsDialog.tsx

@@ -16,10 +16,6 @@ import {
   FolderSearch,
   Shield,
   Brain,
-  ScanText,
-  UserSquare2,
-  Boxes,
-  Tags as TagsIcon,
   RotateCcw,
 } from 'lucide-react'
 import clsx from 'clsx'
@@ -1107,56 +1103,20 @@ interface AiFeaturesTabProps {
   ) => Promise<void>
 }
 
-// Flags are keyed by the backend's canonical name ("vision.enabled",
-// "vision.ocr.enabled", ...). The metadata here just adds presentation
-// (label, short description, icon) so the tab layout stays data-driven.
 const FLAG_META: Array<{
   id: string
   label: string
   description: string
   icon: React.ReactNode
-  // Optional "run this backfill" hook — lets the user kick off a stage's
-  // backfill right from the toggle row without hopping to a separate UI.
-  backfillTask?: 'embed' | 'ocr' | 'detect' | 'faces' | 'classify'
 }> = [
   {
     id: 'vision.enabled',
-    label: 'Vision pipeline (master switch)',
+    label: 'Vision classifier',
     description:
-      'When off, every AI stage below is skipped — including newly uploaded photos. ' +
-      'Existing results stay intact.',
+      'Binary photo-vs-other classifier. Flags screenshots, documents, memes and ' +
+      'scans with "needs review" so they can be triaged.',
     icon: <Sparkles className="h-3.5 w-3.5" />,
   },
-  {
-    id: 'vision.ocr.enabled',
-    label: 'Text recognition (OCR)',
-    description: 'Extract printed / handwritten text from photos so it becomes searchable.',
-    icon: <ScanText className="h-3.5 w-3.5" />,
-    backfillTask: 'ocr',
-  },
-  {
-    id: 'vision.detector.enabled',
-    label: 'Object detection',
-    description: 'Tag photos with detected objects (person, car, dog, …) via YOLOv8n.',
-    icon: <Boxes className="h-3.5 w-3.5" />,
-    backfillTask: 'detect',
-  },
-  {
-    id: 'vision.faces.enabled',
-    label: 'Face recognition',
-    description:
-      'Find and cluster faces across the library (RetinaFace + ArcFace). ' +
-      'Expensive on big libraries — disable if you don\'t need the People view.',
-    icon: <UserSquare2 className="h-3.5 w-3.5" />,
-    backfillTask: 'faces',
-  },
-  {
-    id: 'vision.classifier.enabled',
-    label: 'Content classification',
-    description: 'Zero-shot CLIP tags for scenes / activities (beach, wedding, …).',
-    icon: <TagsIcon className="h-3.5 w-3.5" />,
-    backfillTask: 'classify',
-  },
 ]
 
 function AiFeaturesTab({ busy, runAction }: AiFeaturesTabProps) {
@@ -1183,12 +1143,11 @@ function AiFeaturesTab({ busy, runAction }: AiFeaturesTabProps) {
     queryClient.invalidateQueries({ queryKey: ['features'] })
   }
 
-  type BackfillTask = 'embed' | 'ocr' | 'detect' | 'faces' | 'classify' | null
-  const runBackfill = (task: BackfillTask) =>
+  const runBackfill = () =>
     runAction(
-      `ai-backfill:${task ?? 'all'}`,
-      () => adminApi.triggerAiBackfill({ task }),
-      task ? `Backfill queued for ${task}` : 'Full backfill queued',
+      `ai-backfill:all`,
+      () => adminApi.triggerAiBackfill({}),
+      'Classifier backfill queued',
       (r) => `Celery task ${r.task_id}`,
     )
 
@@ -1286,17 +1245,6 @@ function AiFeaturesTab({ busy, runAction }: AiFeaturesTabProps) {
                     </div>
                   </div>
 
-                  {meta.backfillTask && state.effective && !masterOff && (
-                    <div className="mt-2">
-                      <ActionButton
-                        loading={!!busy[`ai-backfill:${meta.backfillTask}`]}
-                        onClick={() => runBackfill(meta.backfillTask!)}
-                      >
-                        <RefreshCw className="h-3.5 w-3.5" />
-                        Run {meta.backfillTask} backfill
-                      </ActionButton>
-                    </div>
-                  )}
                 </div>
               )
             })}
@@ -1306,35 +1254,17 @@ function AiFeaturesTab({ busy, runAction }: AiFeaturesTabProps) {
 
       <Section icon={<Cpu className="h-4 w-4" />} title="Manual pipeline triggers">
         <p className="text-xs text-text-muted">
-          Run a full pass across the enabled stages, recompute face
-          clusters, or force a fresh filesystem scan. All three are safe
-          to run repeatedly — the backfill only touches photos that
-          don\'t yet have a given output, and the rescan skips files
-          that are already indexed.
+          Run the classifier over any photos that haven't been classified yet,
+          or force a fresh filesystem scan. Both are safe to run repeatedly.
         </p>
         <div className="mt-3 flex flex-wrap gap-2">
           <ActionButton
             loading={!!busy['ai-backfill:all']}
-            onClick={() => runBackfill(null)}
+            onClick={() => runBackfill()}
             disabled={masterOff}
           >
             <Sparkles className="h-4 w-4" />
-            Run full vision backfill
-          </ActionButton>
-          <ActionButton
-            loading={!!busy['recluster']}
-            onClick={() =>
-              runAction(
-                'recluster',
-                () => adminApi.triggerFaceRecluster(),
-                'Face recluster queued',
-                (r) => `Celery task ${r.task_id}`,
-              )
-            }
-            disabled={masterOff || !flags['vision.faces.enabled']?.effective}
-          >
-            <UserSquare2 className="h-4 w-4" />
-            Recluster faces
+            Run classifier backfill
           </ActionButton>
           <ActionButton
             loading={!!busy['rescan-full']}