How to use Chroma to store and query vector embeddings
This article unravels the powerful combination of Chroma and vector embeddings, demonstrating how you can efficiently store and query the embeddings within this open-source vector database. The tutorial guides you through each step, from setting up the Chroma server to crafting Python applications to interact with it, offering a gateway to innovative data management and exploration possibilities.
Tags: chroma, vectordatabase, vectorembeddings, semanticsearch