input: 
  from tensorflow.keras.layers import Input, Dense, Embedding, GRU
  from tensorflow.keras.models import Model
  from tensorflow.keras.utils import plot_model
  
  def generate_natural_language_response(model: Model, query: str) -> str:
      """Generates a natural language response based on the input query using the provided model.
      >>> generate_natural_language_response(model, "What time is it?")
      '12:30 PM'
      >>> generate_natural_language_response(model, "How are you today?")
      'I am fine, thank you.'
      """
  
output:     
      input_layer = Input(shape=(len(query),))
      embedding_layer = Embedding(input_dim=10000, output_dim=128)(input_layer)
      gru_layer = GRU(128)(embedding_layer)
      output_layer = Dense(1, activation='linear')(gru_layer)
      model = Model(inputs=input_layer, outputs=output_layer)
      response = model.predict(query)
      return response[0]
  