/plushcap/analysis/timescale/timescale-implementing-filtered-semantic-search-using-pgvector-and-javascript-2

Implementing Filtered Semantic Search Using Pgvector and JavaScript

What's this blog post about?

This article explores semantic search with filters and demonstrates how you can implement it using pgvector and JavaScript. Semantic search focuses on understanding the meaning and intent behind a query, while filters refine search results by narrowing them down based on specific attributes. The role of PostgreSQL in implementing filtered semantic search is also discussed, along with its extensions like pgvector, pgai, and pgvectorscale. These open-source extensions transform PostgreSQL into a powerful tool for vector handling and building machine learning applications. Finally, the article provides a step-by-step guide on how to implement filtered semantic search using Javascript/Typescript with pgvector and PostgreSQL.

Company
Timescale

Date published
Dec. 2, 2024

Author(s)
Team Timescale

Word count
2547

Language
English

Hacker News points
None found.


By Matt Makai. 2021-2024.