dialogue_management_model.py

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

import logging

from rasa_core.agent import Agent
from rasa_core.channels.console import ConsoleInputChannel
from rasa_core.interpreter import RegexInterpreter
from rasa_core.policies.keras_policy import KerasPolicy
from rasa_core.policies.memoization import MemoizationPolicy
from rasa_core.interpreter import RasaNLUInterpreter

logger=logging.getLogger(__name__)

def train_dialogue(domain_file='weather_domain.yml', model_path='./models/dialogue',training_data_file='./data/stories.md'):
	agent=Agent(domain_file,policies=[MemoizationPolicy(),KerasPolicy()])
	agent.train(training_data_file,max_history=3,epochs=300,batch_size=50,validation_split=0.2,augmentation_factor=50)
	agent.persist(model_path)
	return agent

def run_weather_bot(serve_forever=True):
	interpreter=RasaNLUInterpreter('./models/nlu/default/weathernlu')
	agent=Agent.load('./models/dialogue',interpreter=interpreter)
	
	if serve_forever:
		agent.handle_channel(ConsoleInputChannel())
	return agent

if __name__ == '__main__':
	train_dialogue()
	run_weather_bot()