Filtering with Metadata
Utilize metadata to refine your similarity searches, adding contextual constraints to your queries.
Filter Your Vector Searches
Imagine searching for products, but only wanting "electronics" that are "under $50". This is where metadata filtering comes in handy!
Vector databases let you store extra information, called metadata, alongside your vectors. This lesson teaches you how to use this metadata to refine your similarity searches in Pinecone.
Understanding Metadata
Metadata is simply "data about data." In Pinecone, it's a set of key-value pairs attached to each vector.
- Key: A string representing a property (e.g.,
"category","price","author"). - Value: Can be a string, number, boolean, or even a list of strings/numbers.
It helps describe the item your vector represents.
All lessons in this course
- Filtering with Metadata
- Managing Namespaces
- Real-time Updates & Deletions
- Hybrid Search with Sparse-Dense Vectors