code: def query(
      self,
      query: VectorIndexQuery,
  ) -> VectorIndexQueryResult:
      response = self._client.search(
          collection_name=self._collection_name,
          query_vector=query.embedding.reshape(-1).tolist(),
          limit=query.top_k,
      )
  
      distances, ids = [], []
      for point in response:
          distances.append(point.score)
          ids.append(int(point.id))
  
      return VectorIndexQueryResult(distances, ids)
  
file_path: evadb/evadb/third_party/vector_stores/qdrant.py
imports: from typing import List
  from evadb.third_party.vector_stores.types import FeaturePayload, VectorIndexQuery, VectorIndexQueryResult, VectorStore
  from evadb.utils.generic_utils import try_to_import_qdrant_client
label_desc: Use image node_id 5 for calling the QdrantVectorStore obj's underlying member method code with example usage: obj.query(query) and returns: VectorIndexQueryResult