As you can see, the Generator base class is similar to the Discriminator:

class Generator(object):
    def __init__(self, width = 28, height= 28, channels = 1, 
                 latent_size=100):
        # Initialize Variables

    def model(self):
        # Build the generator model and returns it
        return model

    def summary(self):
        # Prints the Model Summary to the screen

    def save_model(self):
        # Saves the model structure to a file in the data folder

The main difference will be in the different init and model statements when we get to that recipe. The generator is a simple sequential model. The sequential model just represents a way of constructing and connecting layers in a neural network together.