Training and running dialogue model

dialog.py

def train_dialogue(domain_file = 'customer_domain.yml',
					model_path = './models/dialogue',
					training_data_file = './data/stories.md'):

	agent = Agent(domain_file, policies = [MemoizationPolicy(), KerasPolicy()])

	agent.train(
				training_data_file,
				epochs = 300,
				batch_size = 50,
				validation_split = 0.2)

	agent.persist(model_path)
	return agent

def run_customer_bot(serve_forever=True):
	interpreter = RasaNLUInterpreter('./models/nlu/default/customernlu')
	agent = Agent.load('./models/dialogue', interpreter = interpreter)

	if serve_forever:
		agent.handle_channel(ConsoleInputChannel())

	return agent