I migrated a vector db from pinecone to typesense. Using PHP, in pinecone ( to search ) I had to first create an embedding of the query using OpenAI model, then query the db by that vector... In typesense I understand this is all automatic when I use this approach? • It generates the vector when I upsert the doc • It automatically does a vector similarity search when using

$search_parameters = [
  'q'                          => 'chair',
  'query_by'                   => 'embedding',
  'prefix'                     => false,
  'remote_embedding_timeout_ms'=> 5000,
  'remote_embedding_num_try'   => 3
];

$client->collections['products']->documents->search($search_parameters);

That is correct? Well, it appears to work, just not sure it is really how its intended to be used.