ποΈ π Semantic Search
We can't have a technical event without talking about AI, ML, and LLMs these days. So, let's talk about semantic search.
ποΈ π What Are Vectors?
Simply put, a vector is a list of numbers. For example, a vector of length 3 could be [1, 2, 3]. A vector of length 5 could be [1, 2, 3, 4, 5]. A vector of length 100 could be [1, 2, 3, 4, 5, ..., 100]. The length of a vector is the number of elements it contains.
ποΈ π Implementing Vector Search
There are two components that you will need to implement vector search into your application.
ποΈ π Import Vectorized Data
In the context of this workshop, you might not have enough time to vectorize your own data. Therefore, we have provided a vectorized version of the data for you to use.
ποΈ π Create Vector Search Indexes
To start using Vector Search, you must configure another search index on your database. The process is similar to what you did in the last section.
ποΈ π Add Semantic Search to Your Application
You now know everything you need to add vector search capabilities to your application.
ποΈ π¦ΈββοΈ Pre-filtering Data
Extra activity! Do it if you have extra time or are following along at home. It won't be covered during the hands-on lab.
ποΈ π‘ Create Vectors
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