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
import rasa_core
from rasa_core.agent import Agent
from rasa_core.policies.keras_policy import KerasPolicy
from rasa_core.policies.memoization import MemoizationPolicy
from rasa_core.interpreter import RasaNLUInterpreter
from rasa_core.utils import EndpointConfig
from rasa_core.run import serve_application

logger = logging.getLogger(__name__)

def train_dialogue(domain_file = 'chat_domain.yml',
					model_path = './models/dialogue',
					training_data_file = './data/stories.md'):
					
	agent = Agent(domain_file, policies = [MemoizationPolicy(), KerasPolicy()])
	data = agent.load_data(training_data_file)	
	agent.train(
				data,
				epochs = 300,
				batch_size = 50,
				validation_split = 0.2)
				
	agent.persist(model_path)
	return agent
	
def run_bot(serve_forever=True):
	interpreter = RasaNLUInterpreter('./models/nlu/default/iitnlu')
	action_endpoint = EndpointConfig(url="http://localhost:5055/webhook")
	agent = Agent.load('./models/dialogue', interpreter=interpreter, action_endpoint=action_endpoint)
	rasa_core.run.serve_application(agent ,channel='cmdline')
		
	return agent
	
if __name__ == '__main__':
	#train_dialogue()
	run_bot()