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/thumbs.py

@@ -317,6 +317,15 @@ async def _generate_thumbnails_async(photo_id: str, task):
             await session.commit()
             
             logger.info(f"Thumbnails generated for photo {photo_id}")
+
+            # Dispatch vision pipeline (embedding, OCR, detection, faces)
+            # after thumbs are ready so vision tasks have images to read.
+            try:
+                from app.tasks.vision import vision_fanout
+                vision_fanout.delay(photo_id)
+            except Exception as e:
+                logger.warning(f"Could not dispatch vision_fanout for {photo_id}: {e}")
+
             return {'status': 'success', 'photo_id': photo_id}
             
         except Exception as e: