perf(codex-lens): optimize search performance with vectorized operations

Performance Optimizations:
- VectorStore: NumPy vectorized cosine similarity (100x+ faster)
  - Cached embedding matrix with pre-computed norms
  - Lazy content loading for top-k results only
  - Thread-safe cache invalidation
- SQLite: Added PRAGMA mmap_size=30GB for memory-mapped I/O
- FTS5: unicode61 tokenizer with tokenchars='_' for code identifiers
- ChainSearch: files_only fast path skipping snippet generation
- ThreadPoolExecutor: shared pool across searches

New Components:
- DirIndexStore: single-directory index with FTS5 and symbols
- RegistryStore: global project registry with path mappings
- PathMapper: source-to-index path conversion utility
- IndexTreeBuilder: hierarchical index tree construction
- ChainSearchEngine: parallel recursive directory search

Test Coverage:
- 36 comprehensive search functionality tests
- 14 performance benchmark tests
- 296 total tests passing (100% pass rate)

Benchmark Results:
- FTS5 search: 0.23-0.26ms avg (3900-4300 ops/sec)
- Vector search: 1.05-1.54ms avg (650-955 ops/sec)
- Full semantic: 4.56-6.38ms avg per query

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

codex-lens/src/codexlens/storage/sqlite_store.py

@@ -43,6 +43,8 @@ class SQLiteStore:
                 conn.execute("PRAGMA journal_mode=WAL")
                 conn.execute("PRAGMA synchronous=NORMAL")
                 conn.execute("PRAGMA foreign_keys=ON")
+                # Memory-mapped I/O for faster reads (30GB limit)
+                conn.execute("PRAGMA mmap_size=30000000000")
                 self._pool[thread_id] = conn
 
             self._local.conn = conn
@@ -384,7 +386,8 @@ class SQLiteStore:
                 language UNINDEXED,
                 content,
                 content='files',
-                content_rowid='id'
+                content_rowid='id',
+                tokenize="unicode61 tokenchars '_'"
             )
             """
         )