> Find me hotels in Capetown that have a pool by the beach .Should cost between 200 dollars to 800 dollars a night
I built this 18 months ago at an OTA platform. We parse the query and identify which terms are locations, which are hotel features, which are room amenities etc. Then we apply those filters (we have thousands of attributes that can be filtered on, but cannot display all of them in the UI) and display the hotel search results in the regular UI. The input query is also through the normal search box.
This does not need and should not be done in a chatbot UX. All the implementation is on the backend and the right display is the already existing UI. This is semantic search and it comes as a standard capability in ElasticSearch, Supabase etc. Though we built our own version.
We built something like this too (in a different field), but it's actually quit hard to deal with all the edge cases that people might want to search for:
e.g. if the user asks "Find hotels in Capetown [...] that have availability for this christmas or new year": if your backend, or the response format that you're forcing the LLM to give, doesn't have the ability to do an OR on the date range, you can't give results that the user wants, so the LLM tries to do as best it can, and the user ends up getting only hotels which are available for both Christmas and new year (thus missing some that have availability for one or the other), or the LLM does some other unwanted thing. For us, users would even ask "June or August", and then got July included because that was the closest thing the backend / UI could do.
So this approach is actually less flexible than a chat interface, where the LLM can figure out "Ah, I need to do two separate hotel search MCP calls, and then merge the results to not show the same hotel twice".
We didn't support the time dimensions, but I think it could be done without too much issue. You suggest displaying search results in a chat interface but that doesn't work because there are easily hundreds of hotel results for most searches. The user would need to click on a thumbnail in chat into the list of search results on the OTA.
You want it in a chat with other tools and intelligence so that you can give softer preferences and for it to judge reviews and the like. Perhaps even look at the room layout and photos to see if it is something you would like. There are good reasons to surround the tool you describe with AI.
I don't think such massive amounts of text should be parsed at runtime. Hotels can have 100s or 1000s of reviews. We batch created attributes for hotels based on reviews, and when a semantic search was run, those attributes were matched.
I built this 18 months ago at an OTA platform. We parse the query and identify which terms are locations, which are hotel features, which are room amenities etc. Then we apply those filters (we have thousands of attributes that can be filtered on, but cannot display all of them in the UI) and display the hotel search results in the regular UI. The input query is also through the normal search box.
This does not need and should not be done in a chatbot UX. All the implementation is on the backend and the right display is the already existing UI. This is semantic search and it comes as a standard capability in ElasticSearch, Supabase etc. Though we built our own version.