📄️ 📘 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.
📄️ 📘 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.
📄️ 📘 Implementing Vector Search
There are two components that you will need to implement vector search into your application.
📄️ 👐 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.
📄️ 👐 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.
📄️ 👐 Add Semantic Search to Your Application
You now know everything you need to add vector search capabilities to your application.
📄️ 🦸♂️ 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.
🗃️ 🏡 Create Vectors
3 items