train_dialog.py

# Imports
#-----------
# rasa core
import logging
from rasa_core import training
from rasa_core.actions import Action
from rasa_core.agent import Agent
from rasa_core.domain import Domain
from rasa_core.policies.keras_policy import KerasPolicy
from rasa_core.policies import FallbackPolicy
from rasa_core.policies.memoization import MemoizationPolicy
from rasa_core.featurizers import MaxHistoryTrackerFeaturizer, BinarySingleStateFeaturizer
from rasa_core.interpreter import RegexInterpreter
from rasa_core.interpreter import RasaNLUInterpreter

# Function
#------------
def train_dialog(dialog_training_data_file, domain_file="domain.yml", path_to_model = 'models/dialogue'):
    logging.basicConfig(level='INFO')
    fallback = FallbackPolicy(fallback_action_name="action_handle_unclear", core_threshold=0.2, nlu_threshold=0.1)

    agent = Agent(domain_file,
              policies=[MemoizationPolicy(max_history=1),KerasPolicy(epochs=300,
        batch_size=20), fallback])
    training_data = agent.load_data(dialog_training_data_file)
    agent.train(
        training_data,
        augmentation_factor=50,
        validation_split=0.2)
    agent.persist(path_to_model)

# Train
#--------
train_dialog('data/stories.md', 'domain.yml')


# curl -XPOST http://localhost:5005/webhooks/rest/webhook -d '{"query":"hi","sender","thang"}'