Returning the most similar vectors
Querying vectors is foundational to so many AI applications. It involves embedding a user input, comparing it to the vectors in the database, and returning the most similar vectors.
In this exercise, you've been provided with a mystery vector called vector and you'll use it to query your index called 'datacamp-index'.
This exercise is part of the course
Vector Databases for Embeddings with Pinecone
Exercise instructions
- Initialize the Pinecone connection with your API key.
- Retrieve the three records with vectors that are most similar to
vector.
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')
# Retrieve the top three most similar records
query_result = ____
print(query_result)