Add hybrid semantic search with optional cross-encoder reranking

Implements a three-stage search pipeline:
1. BM25 keyword search via FTS5 with column weights
2. Semantic search via Snowflake arctic-embed-s bi-encoder + HNSW index
3. Optional cross-encoder reranking (on by default, toggleable in settings)

Top 20 results are reranked for precision, next 10 appended from RRF
for coverage, giving 30 total results across 3 pages.

- New embeddings.py with ONNX Runtime inference, text chunking, HNSW
  index management, RRF fusion, and cross-encoder reranking
- Meta description extraction for authentic page snippets with centroid
  extractive fallback
- Stopword filtering in FTS5 queries to avoid overly strict matching
- /reindex page for batch embedding of existing pages
- Semantic embedding of remote pages during subscription sync
- ~125MB dependency footprint (onnxruntime, tokenizers, hnswlib, numpy)
- Models: 34MB bi-encoder + 22MB cross-encoder (downloaded on first use)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.gitignore

@@ -1,3 +1,7 @@
 __pycache__/
 tinyweb_identity
 index.db
+index.db-shm
+index.db-wal
+models/
+index.hnsw