Offline in-browser semantic search with only a small model sounds like it has some great potential!<p>I'd love to see a more compelling example / demo. The demo page you have is fairly short and the content being searched seems semantically very narrow (it's all text about word embeddings!). As someone who hasn't spent any time trying out similar systems or trying to build something like this, it's difficult for me to come up with queries to actually judge how well this is working, given the small content in the demo page. So overall, that makes the actual demo not very compelling for me. I'm left uncertain how effective it might be for a more realistic use-case.<p>Basically if you had a better demo - larger and more varied example content, and a few example queries to show off what this can do - then I think the whole thing would be more immediately interesting (to me).
I wasn't expecting it, but I actually got some votes <3, so here is a better description:<p>This is a React component for searching/sorting by meaning (not by "characters included in a string", like standard search).<p>It uses a small ML model that runs on client side (inside the component!). When I say small, I mean ~20MB. The model will be downloaded only once (first time) and afterwards imported from browser's cache.<p>You can use this component to search and filter by meaning a dropdown list or an external list (like paragraphs of a webpage). You can search with sentences on sentences, not just with small words/substrings.<p>Here is a demo: <a href="https://mihaiii.github.io/semantic-autocomplete/" rel="nofollow">https://mihaiii.github.io/semantic-autocomplete/</a><p>I believe this is super useful in the real world! :)<p>Let me know if you have any questions or feedback!<p>Thank you!