video1.0<iframe src="https://www.loom.com/embed/a5cb417115684a3e82a5fd3f20266489" frameborder="0" width="830" height="622" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>622830Loomhttps://www.loom.com622830https://cdn.loom.com/sessions/thumbnails/a5cb417115684a3e82a5fd3f20266489-00001.gif292.2218https://jasonjmcghee.github.io/portable-hnsw/ In this video, I demonstrate a solution I developed over the weekend that allows for natural language search in the browser without the need for a vector database. I show how you can search for specific content based on fuzzy semantic meaning, using a custom index algorithm and transformers JS. The solution offers flexibility and scalability, allowing for large indexes and efficient search queries. No action is requested from the viewers, but I invite you to explore this new approach to browser-based search.