We don't have the drop coordinates part, but you can ask it '...within 1 hour commute by [transport] of [location]' and then it will create a polygon of all the places that match that.
Thanks for the feedback. We're still working out the ideal way to manage the search, lots of trade-offs depending on what route you go. But there's definitely room for improvement.
For the image search portion specifically, we use Google’s embedding model. We then use vector search (https://cloud.google.com/alloydb/docs/ai/run-vector-similari...) to calculate the distance between the search phrase and pre-calculated embeddings for each image.
Then there’s a bit of ranking and scoring magic to build a results set.