def train_dialogue_model(domain_file, stories_file, output_path, kwargs):
agent = Agent(domain_file, policies=[MemoizationPolicy(), KerasPolicy()])
agent.train(stories_file, validation_split=0.1, **kwargs)
agent.persist(output_path)
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import logging
from examples.concerts.policy import ConcertPolicy
from conversationinsights.agent import Agent
from conversationinsights.policies.memoization import MemoizationPolicy
if __name__ == '__main__':
logging.basicConfig(level="INFO")
training_data_file = 'examples/concerts/data/stories.md'
model_path = 'examples/concerts/models/policy/init'
agent = Agent("examples/concerts/concert_domain.yml",
policies=[MemoizationPolicy(),
ConcertPolicy()])
agent.train(training_data_file,
augmentation_factor=50,
max_history=2,
epochs=500,
batch_size=10,
validation_split=0.2)
agent.persist(model_path)