Hybrid Search

introduction to hybrid search

Overview

Hybrid search allows you to combine keyword search using a variant of the TF-IDF algorithm with vector search. The end result is vector similarity search + traditional fuzzy search with text and vector. You can also give weightings of each vector field towards the search, e.g. image_vector_ weights 100%, whilst description_vector_ 50%. This also supports filtering to only search through filtered results and facets to get the overview of products available when a minimum score is set.

Use Cases

We can sometimes get better results from combining traditional search with vector search. This is useful because it takes into consideration the exact words we type a well as the meaning of the strung-together text. Vector AI allows us to do this using the hybrid search API. You can find out more about its use case and an application in combining with vector search.

API

If you are interested in the API documentation, you can find that here.