In this article, you will learn how sentence embeddings work and how to build a fully client-side semantic search engine using Transformers.js, with no server, no API key, and no backend infrastructure required.
Topics we will cover include:
How sentence embeddings and cosine similarity form the foundation of semantic search.
How to generate and cache embeddings using the Transformers.js feature-extraction pipeline, including batching and Web Worker offloading.
How to build a complete, reusable SemanticSearch class and persist its index across page loads.
