### Changes:
- Added `HNSWIndexOptimized` class in `src/hnsw/hnswIndexOptimized.ts`:
- Supports large datasets with product quantization for dimensionality reduction.
- Enables disk-based index storage via a configurable storage adapter.
- Introduces `HNSWOptimizedConfig` interface for advanced configuration:
- Includes memory thresholds, product quantization (subvectors, centroids), and disk-based indexing options.
- Implements methods for adding, searching, and managing indexed vectors with enhanced scalability.
- Introduced `ProductQuantizer` utility:
- Handles vector quantization with training and reconstruction capabilities.
- Reduces vector dimensions, improving memory and performance efficiency.
- Added accessor methods in `src/hnsw/hnswIndex.ts` for configuration and index metadata (e.g., dimension, max level, entry point).
### Purpose:
Enhanced the HNSW implementation to support optimized indexing and search for large datasets, addressing scalability challenges via product quantization and optional disk-based storage. This update elevates the library's performance and applicability for memory-constrained environments.
David Snelling
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