Multivector: knn search: distance between entrypoint and query node: got a nil or zero-length vector at docID 1115 about weaviate HOT 5 OPEN

SOURCE_COLLECTION_NAME = "OpenAI_MenuItemEmbeddings"
CURRENT_COLLECTION_NAME = "OpenAI_MenuItemEmbeddings_SWAP"

# Grab the collection
menu_item_embeddings_collection = client.collections.get(CURRENT_COLLECTION_NAME)
menu_item_embeddings_collection_source = client.collections.get(SOURCE_COLLECTION_NAME)


# Migrate function to copy data from source to current
# We will use this when the vector cache becomes corrupt
def migrate_data(collection_src: Collection, collection_tgt: Collection):
    response = collection_src.aggregate.over_all(total_count=True)
    print("Found {} objects in source collection".format(response.total_count))
    with collection_tgt.batch.fixed_size(batch_size=100) as batch:
        for q in tqdm(collection_src.iterator(include_vector=True)):
            batch.add_object(
                properties=q.properties,
                vector=q.vector,
                uuid=q.uuid
            )

    return True

# We don't have a reliable way to check if the vector cache is corrupt, so we will comment/uncomment this line as needed
# migrate_data(menu_item_embeddings_collection_source, menu_item_embeddings_collection)