def main():
"""Simple implementation of nlu_cli."""
args = parse_args()
mood = args.mood
# Create both Personas for the user and the system
user_persona = Persona("user", mood, 5)
simulated_persona = args.personality_profile
#simulated_persona = Persona(args.personality_profile)
# initiate conversation
conversation_history = Conversation([user_persona, simulated_persona])
ongoing_conversation = True
while ongoing_conversation:
# Query user for utterance
utterance, mood = nlu_cli(mood)
# update conversation history
conversation_history.add_utterance(utterance)
# update user persona
if user_persona.personality.mood != mood:
user_persona.personality.set_mood(mood)
print("output NLU_CLI data:\n")
utterance.print_out()
print("\n", mood, "\n")
print("output conversation_history updated\n")
conversation_history.print_out()
print("output user_persona.mood updated\n")
user_persona.print_out()
if utterance.dialogue_act == DA.farewell:
ongoing_conversation = False
def main():
args = parse_args()
mood = args.mood
# Ask user for their unique name: TODO have bot ask and parse this in convo
username = input("Enter your name: ").strip()
# Create both Personas for the user and the system
user_persona = Persona(username, mood, 5)
chatbot = args.personality_profile
# personality dict:
persona_dict = {user_persona.name: user_persona, chatbot.name: chatbot}
# TODO Actually implement ConversationHistory, rather than one conversation
conversation_history = Conversation({user_persona.name, chatbot.name})
# TODO check if there exists a conversation history between the user and bot
ongoing_conversation = True
while ongoing_conversation:
# Query user for utterance
utterance, mood = nlu_cli(mood, user_persona.name)
print("\n")
# update conversation history
conversation_history.add_utterance(utterance)
# update user persona
if user_persona.personality.mood != mood:
user_persona.personality.set_mood(mood)
# TODO Save topic sentiment for user_persona!
# TODO update simulated persona(s) for future versions, non-prototype
# Simulated Personality must determine how to respond and what to say
# This is mostly outside of NLG, although the what to say part somewhat
# overlaps with NLG task of content determination.
try:
response_utterance = intelligent_agent.decide_response(
conversation_history, chatbot.name, persona_dict)
except:
response_utterance = tactic.psychiatrist(utterance, chatbot.name)
# TODO ensure NLG expects meta text!
# TODO OR, make it so IA's tactics create the text.
# Utterance text should never be none, it will instead be a string of
# keywords for tactics to fill in their place.
# ie. greeting username, question_experience ?
# = "Hello Bob, how was your day?"
# call NLG module to generate actual text, if needed.
#response_utterance = nlg.generate_response_text(
# response_metadata, chatbot, conversation_history) \
# if response_metadata.text is None else response_metadata
print(response_utterance)
# update conversation history
conversation_history.add_utterance(response_utterance)
if response_utterance.dialogue_act == DA.farewell:
ongoing_conversation = False
