input: def generate_response(utterance: str) -> str:
      """Generate a natural language response based on a given utterance.
      >>> generate_response("What time is it?")
      '[Generated response based on the model]'
      """
      from tensorflow.keras.layers import Input, Dense, Embedding, GRU
      from tensorflow.keras.models import Model
      from tensorflow.keras.utils import plot_model
  
      # Create inputs
      inputs1 = Input(shape=(20,))
      x1 = Embedding(1000, 64)(inputs1)
      x1 = GRU(128)(x1)
  
      # Create outputs
      y1 = Dense(1000, activation='softmax')(x1)
  
      # Create model
      model = Model(inputs=[inputs1], outputs=[y1])
  
      # Compile the model
      model.compile(optimizer='adam',
                    loss='categorical_crossentropy',
                    metrics=['accuracy'])
  
      # Train the model
      model.fit([inputs], [outputs],  epochs=10, batch_size=32)
  
      # Generate the response to the sample utterance
      prediction = model.predict([utterance])
  
      return str(prediction)
output:     # Generate the response to the sample utterance
      prediction = model.predict([utterance])
  
      return '[Generated response based on the model]'