NMSLIB is an open-source library for efficient approximate nearest-neighbor search in non-metric spaces. Its canonical HNSW implementation supports compact, practical similarity-search indexes for dense embeddings. section 13.5.4
A typical NMSLIB workflow is:
- Normalize embeddings, add them in a batch, and commit the index with createIndex. section 13.5.4
- Prefer offline rebuilding for read-heavy applications when write-time performance is a concern. section 13.5.4
Semantic autocomplete
An index built from 12,375 concept embeddings returns terms related to “bag,” including “bag liner,” “airbag,” and “paper bag.” Querying “mountain hike” produces close suggestions such as “mountain hiking” and “mountain trail.” section 13.5.4
