input: Write a function to generate natural language responses using a TensorFlow Keras model. The function should take an input utterance in the form of a string and return the model's prediction for the response.
  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)
  
  def generate_response(utterance):
      return model.predict(utterance)
  
  assert generate_response("What time is it?") is not None
output: 
  def generate_response(utterance):
      return model.predict(utterance)
  