query()
:
top_k
: the number of results to return.n_probes
: the number of clusters to search for each query vector.return_distances
: whether to return distances with the IDs.greedy
: whether to perform a greedy search (higher recall but slower).query()
:
get_item
, which retrieves and decrypts items contents (if they were added in upsert
). For more details, see the Get Items guide.
50,000
vectors in your index, you should train the index. Without doing so, queries will run slower. For more details, see Training an Encrypted Index.