Using vector search in MySQL

This video gives a walkthrough of how to use PlanetScale MySQL vectors in an application. In the video, you'll learn how to fetch information form the Hacker News Algolia API, generate embeddings for them, store them into a database, create an vector index, and then query the database based on vector approximate nearest neighbors (ANN) search.

0:00 Introduction
0:43 HNRank overview
1:40 Vectors embeddings in PlanetScale
1:50 Database schema
3:30 Checking the schema
3:52 Fetching data and generating embeddings
6:01 Checking results and creating a vector index
8:10 Updating the server
14:19 Updating the client
17:10 Testing the web application
18:03 Wrap-up

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[ahmad-murery]

The first time I dealt with embedding was to build an app that allows you to chat with documents, I struggled to to get the results/answers properly formatted.
Now, It seems easier for me to understand what's going on and I should revisit my code.


Thanks Ben!

[andriisukhariev]

somehow even being your customer for almost a year and waiting for this feature to arrive, being even enrolled to waiting list very first days, and keep using planetscale on daily basis - i still missed that you released beta version and figured out only by going and checking if you finally did anything about it… guyz.. something is wrong here…