def __init__(self, configuration, agent_id):
"""
Initialize the internal structures of this agent.
:param configuration: a dictionary representing the configuration file
:param agent_id: an integer, this agent's id
"""
super(ConversationalMultiAgent, self).__init__()
self.agent_id = agent_id
# Flag to alternate training between roles
self.train_system = True
# Dialogue statistics
self.dialogue_episode = 1
# Note that since this is a multi-agent setting, dialogue_turn refers
# to this agent's turns only
self.dialogue_turn = 0
self.num_successful_dialogues = 0
self.num_task_success = 0
self.cumulative_rewards = 0
self.total_dialogue_turns = 0
self.minibatch_length = 200
self.train_interval = 50
self.train_epochs = 3
# Alternate training between the agents
self.train_alternate_training = True
self.train_switch_trainable_agents_every = self.train_interval
self.configuration = configuration
# True values here would imply some default modules
self.USE_USR_SIMULATOR = False
self.USER_SIMULATOR_NLG = False
self.USE_NLU = False
self.USE_NLG = False
self.USE_SPEECH = False
self.USER_HAS_INITIATIVE = True
self.SAVE_LOG = True
# The dialogue will terminate after MAX_TURNS (this agent will issue
# a bye() dialogue act.
self.MAX_TURNS = 10
self.ontology = None
self.database = None
self.domain = None
self.dialogue_manager = None
self.user_model = None
self.nlu = None
self.nlg = None
self.agent_role = None
self.agent_goal = None
self.goal_generator = None
self.goals_path = None
self.prev_state = None
self.curr_state = None
self.prev_usr_utterance = None
self.prev_sys_utterance = None
self.prev_action = None
self.prev_reward = None
self.prev_success = None
self.prev_task_success = None
self.user_model = UserModel()
# The size of the experience pool is a hyperparameter.
# Do not have an experience window larger than the current batch,
# as past experience may not be relevant since both agents learn.
self.recorder = DialogueEpisodeRecorder(size=self.minibatch_length)
# TODO: Get reward type from the config
self.reward_func = SlotFillingReward()
# self.reward_func = SlotFillingGoalAdvancementReward()
if self.configuration:
agent_id_str = 'AGENT_' + str(self.agent_id)
# Error checks for options the config must have
if not self.configuration['GENERAL']:
raise ValueError('Cannot run Plato without GENERAL settings!')
elif not self.configuration['GENERAL']['interaction_mode']:
raise ValueError('Cannot run Plato without an interaction '
'mode!')
elif not self.configuration['DIALOGUE']:
raise ValueError('Cannot run Plato without DIALOGUE settings!')
elif not self.configuration[agent_id_str]:
raise ValueError('Cannot run Plato without at least '
'one agent!')
# Dialogue domain self.settings
if 'DIALOGUE' in self.configuration and \
self.configuration['DIALOGUE']:
if 'initiative' in self.configuration['DIALOGUE']:
self.USER_HAS_INITIATIVE = bool(
self.configuration['DIALOGUE']['initiative'] == 'user')
if self.configuration['DIALOGUE']['domain']:
self.domain = self.configuration['DIALOGUE']['domain']
if self.configuration['DIALOGUE']['ontology_path']:
if os.path.isfile(
self.configuration['DIALOGUE']['ontology_path']):
self.ontology = \
Ontology.Ontology(
self.configuration['DIALOGUE']['ontology_path']
)
else:
raise FileNotFoundError(
'Domain file %s not '
'found' %
self.configuration['DIALOGUE']['ontology_path'])
if self.configuration['DIALOGUE']['db_path']:
if os.path.isfile(
self.configuration['DIALOGUE']['db_path']):
if 'db_type' in self.configuration['DIALOGUE']:
if self.configuration['DIALOGUE']['db_type'] == \
'sql':
self.database = DataBase.SQLDataBase(
self.configuration['DIALOGUE']['db_path'])
else:
self.database = DataBase.DataBase(
self.configuration['DIALOGUE']['db_path'])
else:
# Default to SQL
self.database = DataBase.SQLDataBase(
self.configuration['DIALOGUE']['db_path'])
else:
raise FileNotFoundError(
'Database file %s not '
'found' %
self.configuration['DIALOGUE']['db_path'])
if 'goals_path' in self.configuration['DIALOGUE']:
if os.path.isfile(
self.configuration['DIALOGUE']['goals_path']):
self.goals_path = \
self.configuration['DIALOGUE']['goals_path']
else:
raise FileNotFoundError(
'Goals file %s not '
'found' %
self.configuration['DIALOGUE']['goals_path'])
# General settings
if 'GENERAL' in self.configuration and \
self.configuration['GENERAL']:
if 'experience_logs' in self.configuration['GENERAL']:
dialogues_path = None
if 'path' in \
self.configuration['GENERAL']['experience_logs']:
dialogues_path = \
self.configuration['GENERAL'][
'experience_logs']['path']
if 'load' in \
self.configuration['GENERAL'][
'experience_logs'] and \
bool(
self.configuration[
'GENERAL'
]['experience_logs']['load']
):
if dialogues_path and os.path.isfile(dialogues_path):
self.recorder.load(dialogues_path)
else:
raise FileNotFoundError(
'Dialogue Log file %s not found (did you '
'provide one?)' % dialogues_path)
if 'save' in \
self.configuration['GENERAL']['experience_logs']:
self.recorder.set_path(dialogues_path)
self.SAVE_LOG = bool(self.configuration['GENERAL']
['experience_logs']['save'])
if self.configuration['GENERAL']['interaction_mode'] == \
'simulation':
self.USE_USR_SIMULATOR = True
# NLU Settings
if 'NLU' in self.configuration[agent_id_str] and \
self.configuration[agent_id_str]['NLU'] and \
self.configuration[agent_id_str]['NLU']['nlu']:
nlu_args = dict(
zip(['ontology', 'database'],
[self.ontology, self.database]))
if self.configuration[agent_id_str]['NLU']['nlu'] == 'dummy':
self.nlu = DummyNLU(nlu_args)
self.USE_NLU = True
elif self.configuration[agent_id_str]['NLU']['nlu'] == \
'CamRest':
if self.configuration[agent_id_str]['NLU']['model_path']:
nlu_args['model_path'] = \
self.configuration[
agent_id_str
]['NLU']['model_path']
self.nlu = CamRestNLU(nlu_args)
self.USE_NLU = True
else:
raise ValueError(
'Cannot find model_path in the config.')
# NLG Settings
if 'NLG' in self.configuration[agent_id_str] and \
self.configuration[agent_id_str]['NLG'] and \
self.configuration[agent_id_str]['NLG']['nlg']:
if self.configuration[agent_id_str]['NLG']['nlg'] == 'dummy':
self.nlg = DummyNLG()
elif self.configuration[agent_id_str]['NLG']['nlg'] == \
'CamRest':
if self.configuration[agent_id_str]['NLG']['model_path']:
self.nlg = CamRestNLG({
'model_path':
self.configuration[agent_id_str]['NLG']
['model_path']
})
else:
raise ValueError(
'Cannot find model_path in the config.')
if self.nlg:
self.USE_NLG = True
# Retrieve agent role
if 'role' in self.configuration[agent_id_str]:
self.agent_role = self.configuration[agent_id_str]['role']
else:
raise ValueError('ConversationalMultiAgent: No role assigned '
'for agent {0} in '
'config!'.format(self.agent_id))
if self.agent_role == 'user':
if self.ontology and self.database:
self.goal_generator = GoalGenerator(
ontology=self.ontology,
database=self.database,
goals_file=self.goals_path)
else:
raise ValueError('Conversational Multi Agent (user): '
'Cannot generate goal without ontology '
'and database.')
dm_args = dict(
zip([
'settings', 'ontology', 'database', 'domain', 'agent_id',
'agent_role'
], [
self.configuration, self.ontology, self.database, self.domain,
self.agent_id, self.agent_role
]))
dm_args.update(self.configuration['AGENT_' + str(agent_id)]['DM'])
self.dialogue_manager = DialogueManager.DialogueManager(dm_args)
def __init__(self, configuration):
"""
Initialize the internal structures of this agent.
:param configuration: a dictionary representing the configuration file
:param agent_id: an integer, this agent's id
"""
super(ConversationalSingleAgent, self).__init__()
self.configuration = configuration
# There is only one agent in this setting
self.agent_id = 0
# Dialogue statistics
self.dialogue_episode = 0
self.dialogue_turn = 0
self.num_successful_dialogues = 0
self.num_task_success = 0
self.cumulative_rewards = 0
self.total_dialogue_turns = 0
self.minibatch_length = 500
self.train_interval = 50
self.train_epochs = 10
# True values here would imply some default modules
self.USE_USR_SIMULATOR = False
self.USER_SIMULATOR_NLU = False
self.USER_SIMULATOR_NLG = False
self.USE_NLG = False
self.USE_SPEECH = False
self.USER_HAS_INITIATIVE = True
self.SAVE_LOG = True
# The dialogue will terminate after MAX_TURNS (this agent will issue
# a bye() dialogue act.
self.MAX_TURNS = 15
self.dialogue_turn = -1
self.ontology = None
self.database = None
self.domain = None
self.dialogue_manager = None
self.user_model = None
self.user_simulator = None
self.user_simulator_args = {}
self.nlu = None
self.nlg = None
self.agent_role = None
self.agent_goal = None
self.goal_generator = None
self.curr_state = None
self.prev_state = None
self.curr_state = None
self.prev_usr_utterance = None
self.prev_sys_utterance = None
self.prev_action = None
self.prev_reward = None
self.prev_success = None
self.prev_task_success = None
self.user_model = UserModel()
self.recorder = DialogueEpisodeRecorder()
# TODO: Handle this properly - get reward function type from config
self.reward_func = SlotFillingReward()
# self.reward_func = SlotFillingGoalAdvancementReward()
if self.configuration:
# Error checks for options the config must have
if not self.configuration['GENERAL']:
raise ValueError('Cannot run Plato without GENERAL settings!')
elif not self.configuration['GENERAL']['interaction_mode']:
raise ValueError('Cannot run Plato without an '
'interaction mode!')
elif not self.configuration['DIALOGUE']:
raise ValueError('Cannot run Plato without DIALOGUE settings!')
elif not self.configuration['AGENT_0']:
raise ValueError('Cannot run Plato without at least '
'one agent!')
# Dialogue domain self.settings
if 'DIALOGUE' in self.configuration and \
self.configuration['DIALOGUE']:
if 'initiative' in self.configuration['DIALOGUE']:
self.USER_HAS_INITIATIVE = bool(
self.configuration['DIALOGUE']['initiative'] == 'user')
self.user_simulator_args['us_has_initiative'] = \
self.USER_HAS_INITIATIVE
if self.configuration['DIALOGUE']['domain']:
self.domain = self.configuration['DIALOGUE']['domain']
if self.configuration['DIALOGUE']['ontology_path']:
if os.path.isfile(
self.configuration['DIALOGUE']['ontology_path']):
self.ontology = Ontology.Ontology(
self.configuration['DIALOGUE']['ontology_path'])
else:
raise FileNotFoundError(
'Domain file %s not found' %
self.configuration['DIALOGUE']['ontology_path'])
if self.configuration['DIALOGUE']['db_path']:
if os.path.isfile(
self.configuration['DIALOGUE']['db_path']):
if 'db_type' in self.configuration['DIALOGUE']:
if self.configuration['DIALOGUE']['db_type'] == \
'sql':
self.database = DataBase.SQLDataBase(
self.configuration['DIALOGUE']['db_path'])
else:
self.database = DataBase.DataBase(
self.configuration['DIALOGUE']['db_path'])
else:
# Default to SQL
self.database = DataBase.SQLDataBase(
self.configuration['DIALOGUE']['db_path'])
else:
raise FileNotFoundError(
'Database file %s not found' %
self.configuration['DIALOGUE']['db_path'])
if 'goals_path' in self.configuration['DIALOGUE']:
if os.path.isfile(
self.configuration['DIALOGUE']['goals_path']):
self.goals_path = \
self.configuration['DIALOGUE']['goals_path']
else:
raise FileNotFoundError(
'Goals file %s not found' %
self.configuration['DIALOGUE']['goals_path'])
# General settings
if 'GENERAL' in self.configuration and \
self.configuration['GENERAL']:
if 'experience_logs' in self.configuration['GENERAL']:
dialogues_path = None
if 'path' in \
self.configuration['GENERAL']['experience_logs']:
dialogues_path = \
self.configuration['GENERAL'][
'experience_logs']['path']
if 'load' in \
self.configuration['GENERAL']['experience_logs'] \
and bool(
self.configuration['GENERAL'][
'experience_logs']['load']
):
if dialogues_path and os.path.isfile(dialogues_path):
self.recorder.load(dialogues_path)
else:
raise FileNotFoundError(
'Dialogue Log file %s not found (did you '
'provide one?)' % dialogues_path)
if 'save' in \
self.configuration['GENERAL']['experience_logs']:
self.recorder.set_path(dialogues_path)
self.SAVE_LOG = bool(self.configuration['GENERAL']
['experience_logs']['save'])
if self.configuration['GENERAL']['interaction_mode'] == \
'simulation':
self.USE_USR_SIMULATOR = True
elif self.configuration['GENERAL']['interaction_mode'] == \
'speech':
self.USE_SPEECH = True
self.asr = speech_rec.Recognizer()
# Agent Settings
# Usr Simulator
# Check for specific simulator self.settings, otherwise
# default to agenda
if 'USER_SIMULATOR' in self.configuration['AGENT_0']:
# Agent 0 simulator configuration
a0_sim_config = self.configuration['AGENT_0']['USER_SIMULATOR']
if a0_sim_config and a0_sim_config['simulator']:
# Default settings
self.user_simulator_args['ontology'] = self.ontology
self.user_simulator_args['database'] = self.database
self.user_simulator_args['um'] = self.user_model
self.user_simulator_args['patience'] = 5
if a0_sim_config['simulator'] == 'agenda':
if 'patience' in a0_sim_config:
self.user_simulator_args['patience'] = \
int(a0_sim_config['patience'])
if 'pop_distribution' in a0_sim_config:
if isinstance(a0_sim_config['pop_distribution'],
list):
self.user_simulator_args['pop_distribution'] =\
a0_sim_config['pop_distribution']
else:
self.user_simulator_args['pop_distribution'] =\
eval(a0_sim_config['pop_distribution'])
if 'slot_confuse_prob' in a0_sim_config:
self.user_simulator_args['slot_confuse_prob'] = \
float(a0_sim_config['slot_confuse_prob'])
if 'op_confuse_prob' in a0_sim_config:
self.user_simulator_args['op_confuse_prob'] = \
float(a0_sim_config['op_confuse_prob'])
if 'value_confuse_prob' in a0_sim_config:
self.user_simulator_args['value_confuse_prob'] = \
float(a0_sim_config['value_confuse_prob'])
if 'goal_slot_selection_weights' in a0_sim_config:
self.user_simulator_args[
'goal_slot_selection_weights'] = a0_sim_config[
'goal_slot_selection_weights']
if 'nlu' in a0_sim_config:
self.user_simulator_args['nlu'] = \
a0_sim_config['nlu']
if self.user_simulator_args['nlu'] == 'dummy':
self.user_simulator_args['database'] = \
self.database
self.USER_SIMULATOR_NLU = True
if 'nlg' in a0_sim_config:
self.user_simulator_args['nlg'] = \
a0_sim_config['nlg']
if self.user_simulator_args['nlg'] == 'CamRest':
if a0_sim_config:
self.user_simulator_args[
'nlg_model_path'] = a0_sim_config[
'nlg_model_path']
self.USER_SIMULATOR_NLG = True
else:
raise ValueError(
'Usr Simulator NLG: Cannot find '
'model_path in the config.')
elif self.user_simulator_args['nlg'] == 'dummy':
self.USER_SIMULATOR_NLG = True
if 'goals_file' in a0_sim_config:
self.user_simulator_args['goals_file'] = \
a0_sim_config['goals_file']
if 'policy_file' in a0_sim_config:
self.user_simulator_args['policy_file'] = \
a0_sim_config['policy_file']
self.user_simulator = AgendaBasedUS(
self.user_simulator_args)
elif a0_sim_config['simulator'] == 'dtl':
if 'policy_file' in a0_sim_config:
self.user_simulator_args['policy_file'] = \
a0_sim_config['policy_file']
self.user_simulator = DTLUserSimulator(
self.user_simulator_args)
else:
raise ValueError(
'Error! Cannot start DAct-to-Language '
'simulator without a policy file!')
else:
# Fallback to agenda based simulator with default settings
self.user_simulator = AgendaBasedUS(
self.user_simulator_args)
# NLU Settings
if 'NLU' in self.configuration['AGENT_0'] and \
self.configuration['AGENT_0']['NLU'] and \
self.configuration['AGENT_0']['NLU']['nlu']:
nlu_args = dict(
zip(['ontology', 'database'],
[self.ontology, self.database]))
if self.configuration['AGENT_0']['NLU']['nlu'] == 'dummy':
self.nlu = DummyNLU(nlu_args)
elif self.configuration['AGENT_0']['NLU']['nlu'] == 'CamRest':
if self.configuration['AGENT_0']['NLU']['model_path']:
nlu_args['model_path'] = \
self.configuration['AGENT_0']['NLU']['model_path']
self.nlu = CamRestNLU(nlu_args)
else:
raise ValueError(
'Cannot find model_path in the config.')
# NLG Settings
if 'NLG' in self.configuration['AGENT_0'] and \
self.configuration['AGENT_0']['NLG'] and \
self.configuration['AGENT_0']['NLG']['nlg']:
if self.configuration['AGENT_0']['NLG']['nlg'] == 'dummy':
self.nlg = DummyNLG()
elif self.configuration['AGENT_0']['NLG']['nlg'] == 'CamRest':
if self.configuration['AGENT_0']['NLG']['model_path']:
self.nlg = CamRestNLG({
'model_path':
self.configuration['AGENT_0']['NLG']['model_path']
})
else:
raise ValueError(
'Cannot find model_path in the config.')
if self.nlg:
self.USE_NLG = True
# Retrieve agent role
if 'role' in self.configuration['AGENT_0']:
self.agent_role = self.configuration['AGENT_0']['role']
else:
raise ValueError(
'ConversationalAgent: No role assigned for agent {0} in '
'config!'.format(self.agent_id))
if self.agent_role == 'user':
if self.ontology and self.database:
self.goal_generator = GoalGenerator(ontology=self.ontology,
database=self.database)
else:
raise ValueError(
'Conversational Multi Agent (user): Cannot generate '
'goal without ontology and database.')
dm_args = dict(
zip([
'settings', 'ontology', 'database', 'domain', 'agent_id',
'agent_role'
], [
self.configuration, self.ontology, self.database, self.domain,
self.agent_id, self.agent_role
]))
dm_args.update(self.configuration['AGENT_0']['DM'])
self.dialogue_manager = DialogueManager.DialogueManager(dm_args)