feat: add embeddings pipeline and semantic search endpoint

Wire the full embedding flow:
- Rewrite Embedding model to use pgvector Vector(512) with HNSW index
- Add embed_photo, vision_fanout, backfill_vision Celery tasks on
  dedicated `vision` queue
- Hook vision_fanout into generate_thumbnails completion
- Add POST /api/v1/photos/search with hybrid RRF ranking (semantic-only
  for now; FTS leg added in PR5)
- Stub ocr_photo, detect_objects, extract_faces tasks for later PRs

Migration 0003 drops/recreates the embeddings table (was never populated).

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

backend/app/tasks/celery.py

@@ -9,7 +9,7 @@ celery_app = Celery(
     'mulita',
     broker=settings.celery_broker_url,
     backend=settings.celery_result_backend,
-    include=['app.tasks.scan', 'app.tasks.thumbs']
+    include=['app.tasks.scan', 'app.tasks.thumbs', 'app.tasks.vision']
 )
 
 # Configure Celery
@@ -22,6 +22,12 @@ celery_app.conf.update(
     task_routes={
         'app.tasks.thumbs.*': {'queue': 'high'},
         'app.tasks.scan.*': {'queue': 'low'},
+        'app.tasks.vision.*': {'queue': 'vision'},
+        'embed_photo': {'queue': 'vision'},
+        'ocr_photo': {'queue': 'vision'},
+        'detect_objects': {'queue': 'vision'},
+        'extract_faces': {'queue': 'vision'},
+        'vision_fanout': {'queue': 'vision'},
     },
     task_default_queue='default',
     task_default_exchange='default',