Fiftyone, Qdrant.
= get_text_embedding(prompt, model) type(query_vector) Search the Qdrant VectorStore for content Matching Query1 results = client.search_batch( collection_name=COLLECTION_NAME, requests=[ models.SearchRequest( vector=models.NamedVector( name="text-dense", vector=query_vector[0], ), limit=5, ), ], )