So the extension scrapes all your bookmarks' content, selects key parts of it (we have a naive heuristic for now), embeds them using Sentence Transformer, and indexes them in the browser local storage with Orama's vector DB. When you want to search, we embed the query and do a vector search against the index to get the semantically most similar ones. All in-browser so no data going to any API.
Didn't try victor, is that just for nodejs runtime or does it run at the edge as well? Orama's been pretty good, at least semantically. Haven't done any speed benchmarking so not sure if it's as fast as say HNSW.
I would assume it runs on the edge, since it runs in the browser via WASM. It's also implemented in Rust, which provides some flexibility. It will likely depend on the specific edge runtime though. The runtime would need something resembling a file system.
The thing I like about Victor is that it uses OPFS for storage when running in the browser, meaning it doesn't keep everything in memory. I looked at Orama a bit and from my reading I think they keep everything in memory, although I didn't dig too deep and would like to be wrong about that.
This is similar to Voy [1], which runs entirely in memory.
Unfortunately, for my own usage running in memory feels like a non-starter since the data size is unbounded.
Thank you! Yeah history is something we've been asked multiple times now. I'm sure this could be extended easily once we solve a few things (scraping pages faster and being smarter about what text we embed, parsing out irrelevant stuff). Will keep you posted.
Thank you! Will take a look at these. We mostly made this to solve something for ourselves and as a learning exercise, but hoping this may resonate with others too
we were gonna get it published on the web store after some initial feedback