How to do batches of vector search?

How to do batches of vector search? Each batch contains multiple queries and multiple databases, and queries only search for corresponding database in the batch. For example:

import cupy as cp

batch_size = 16
n_samples = 5000
n_features = 50
n_queries = 1000
dataset = cp.random.random_sample((batch_size, n_samples, n_features),
                                  dtype=cp.float32)
# Build index
index = cagra.build(cagra.IndexParams(), dataset)
# Search using the built index
queries = cp.random.random_sample((batch_size, n_queries, n_features),
                                  dtype=cp.float32)
# doing some indexing and searchs, queries only search for corresponding database

I've searched whole doc and issues. Really appreciate your answer!

The issue provides no file or test to start from. Begin by checking the cuVS CAGRA and CuPy documentation for batched datasets and queries, then determine whether corresponding database/query searches are supported; done means providing a documented way to perform the requested batched search or clearly identifying the limitation.