Vectors in SQLite! (with libSQL)

In this video, I explore how to improve related article recommendations on a website by leveraging SQLite with experimental vector support in libSQL, a package created by Turso. Follow along as we use OpenAI’s API to generate embeddings, store them in a database, and calculate nearest neighbors for more relevant content suggestions. Want to learn more SQLite? Check out my SQLite course: Mentioned Links: Turso: libSQL: Nuno Maduro’s OpenAI PHP client: My video about using SQLite for my site: Follow me: Twitter: LinkedIn: Website: - find articles, podcasts, courses, and more. Chapters: 00:00 - Introduction and Website Overview 00:26 - SQLite Database for the Website 00:39 - LibSQL Vector Support Introduction 01:21 - Creating Article Embeddings with OpenAI API 02:32 - Cleaning Article Contents 03:06 - Generating Embeddings from Article Data 04:55 - Storing Embeddings in libSQL 06:00 - Setting up Database for Embeddings 07:00 - Indexing and Storing Embeddings in SQLite 08:45 - Writing SQL Query for Related Articles 10:15 - Querying Article Embeddings for Nearest Neighbors 12:00 - Testing and Fetching Related Articles 14:10 - Improved Related Articles Display 16:00 - Conclusion and Future Plans