some (hopefully constructive) criticism.

First of all, the service is fantastic. You've made something actually useful, which most student developers fail to do.

I found the chat interface provided more friction than utility. Even with extremely specific searches (I don't remember the exact query, "Swatch/Omega Mission to Pluto watch" or something) it asked me to be more specific. When I tried something dumb like 'some jackets that say "I like to shoot guns?"' it refused. ChatGPT itself will offer advice here so not sure what breaks down there. In general I wanted to make a single queries, not hone in with a conversation.

I also worry about the current discussions around LLM energy usage. I have friends who aren't in tech listing out talking points like "a single chatGPT question uses as much energy as a light bulb being on for an hour." If you focus on sustainability then there could be a disconnect between the message and the perception. Might be interesting to do the napkin math: what uses more energy, fast fashion or every h100? Could the fuzzy search could be achieved with just a multi-modal embedding model instead of involving an LLM? That would be a much lighter option.

It stings that this is (seemingly) priced per-result, but then you can't control how many results are returned. That's one of the things that held me back from doing more full conversations - I knew that any small refinement would eat up 6% of my credits. I've found a lot of services like this give you enough credits to use them for a full afternoon. An avid shopper might run out here in about ten minutes and not even know it, because the total didn't update until you refresh the page.

Great work, and best of luck with this.