chunk_content: ce) for k, v in inputs.items()}).detach().cpu()
      return query_embs[0]
  
      
  def get_nearest_neighbours(k, search_index, query_embeddings, ids_to_products_dict, threshold=0.7):
      # Controlling the recall by setting ef:
      search_index.set_ef(100) # ef should always be > k
  
      # Query dataset, k - number of the closest elements (returns 2 numpy arrays)
      labels, distances = search_index.knn_query(query_embeddings, k = k)
      
      return 