Vector Databases: From Embeddings to Applications/

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Storing Audio and Metadata Embeddings to Vector Database

Storing Audio and Metadata Embeddings to Vector Database

Learn to store the embeddings we generated for our music dataset in the vector database.

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We’ll use Chroma DB to store our embeddings. Let’s jump right in.

Create a chroma client

First, we import chromadb and initialize a persistent Chroma client. This setup ensures that the database is saved and loaded on our local machine, with data being automatically persisted and reloaded upon startup if it exists.

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import chromadb
client = chromadb.PersistentClient(path="/usr/local/musicRecommendationSystemDir/database")

Create collections for storing

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