input: from typing import Tuple
  
  def construct_mnist_model() -> keras.Model:
      """ Construct a neural network model using Keras to classify the MNIST dataset.
      The model should have an input layer with shape (784,), a hidden layer with 
      128 units and 'relu' activation, and an output layer with 10 units and 
      'softmax' activation. The model should be compiled with the 'adam' optimizer,
      'sparse_categorical_crossentropy' loss, and 'accuracy' as the metric.
      >>> model = construct_mnist_model()
      >>> isinstance(model, keras.Model)
      True
      """
output:     input_layer = keras.layers.Input(shape=(784,))
      hidden_layer = keras.layers.Dense(128, activation='relu')(input_layer)
      output_layer = keras.layers.Dense(10, activation='softmax')(hidden_layer)
      
      model = keras.models.Model(inputs=input_layer, outputs=output_layer)
      model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      
      return model