Updating vector metadata
This time, you'll practice updating vectors in the datacamp-index Pinecone index with new metadata. You'll again verify these changes were successful by retrieving the vector and checking its metadata.
This exercise is part of the course
Vector Databases for Embeddings with Pinecone
Exercise instructions
- Initialize the Pinecone connection with your API key.
- Update the vector with ID
"7"with new metadata:"genre"of"thriller"and"year"of2024. - Fetch the vector to check if the metadata has been updated.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Initialize the Pinecone client with your API key
pc = Pinecone(api_key="____")
index = pc.Index('datacamp-index')
# Update the metadata of vector ID 7
____
# Fetch vector ID 7
fetched_vector = ____
print(fetched_vector)