🧈 Mr. Butterfingers 🧈

I’m going to show you how *incredibly easy* it is to add some AI-magic to the search bar in your sites & apps in 2025 using @typesense. Say you’re building a cars site & you have a search bar on top. You have cars. Cars have attributes. You have well structured data like make, model, color, year, hp, mileage, etc. Cool. Along comes a user & types this into your search bar: “A black SUV with less than 30K miles in Houston for less than 20K”. ☠️🫣 If you’ve built any kind of search experience you probably know how hard it is to map free-form text like that to specific attributes in your dataset. Like how do you know that 20K is talking about cost, and black is talking about the overall color and not the color of the seats, and then account for the zillion other ways your users can write the same query? If you haven’t encountered this, let me tell you that it is HARD to use simple full-text search or even fancy semantic search or hybrid search to pull this off. Traditionally you’d have to train and build what’s called intent detection ML models to do this well. Ain’t nobody got time for that! 🤓 Enter @Typesense - an open source, cutting edge, light-weight alternative to Elasticsearch / Algolia. As of v29.0, it now has a built-in feature that cleverly uses the magic of LLMs, to parse your users’ queries, and convert them automatically into a set of filters and sorts, and then executes that query and returns results. So in our example “A black SUV with less than 30K miles in Houston for less than 20K” gets converted by Typesense automatically into this search query: Notice how the free-form user query was correctly mapped to the attributes and values in our cars dataset under the hood. It’s literally one API call to Typesense, to make this magic work: The curl request will return results like this: And you’d display those results in your UI. That’s it. What used to take teams of ML experts, is now one API call away. No PhD required. You now have an AI-powered search bar that’s ready for the most brazenly complicated user queries. How about this one: No problemo! That get's translated to: 🪄 ``` filter_by: "transmission_type:AUTOMATIC" ``` (Only 4 images per tweet, so only text for that one) Even though `transmission_type` only has - `Automatic` and - `Manual` across all records, Typesense is able to automatically convert the user’s intent in “I don’t know how to drive shift” to the fact that we should only show them vehicles with automatic transmission. Easy-peasy. Here’s a step-by-step guide on how to implement Natural Language Search in your own sites and apps: typesense.org/docs/29.0/api/…