Learn How Vector Stores Work by Building a Recommendation Engine

This tutorial provides a fundamental demonstration of how vector databases operate.

In this example, we will define various parameters, or dimensions, for food critiquing. The engine will then suggest dishes to the user based on these parameters, aligned with their preferences. For vector storage and management, we will utilize Upstash Vector.

Outline:

1- Create an index on Upstash Vector and install the required dependencies.

2- Define dimensions for food critiqueing.

3- Insert data.

4- Create query by asking preferences to user.

5- Show recommended dishes by querying the vector database.

You can find the full tutorial and code in the notebook here.