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jarvis-server/jarvis/skills/intent_manager.py

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import json
from adapt.engine import DomainIntentDeterminationEngine
from padatious import IntentContainer
from jarvis.utils import utils
adapt_engine = DomainIntentDeterminationEngine()
padatious_intents_container = IntentContainer('intent_cache')
intents_handlers_adapt = dict()
intents_handlers_padatious = dict()
def register_entity_adapt(entity_value, entity_type, domain):
adapt_engine.register_entity(entity_value=entity_value, entity_type=entity_type, domain=domain)
# print("[Adapt]: Added entity with type " + entity_type + " for " + domain)
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def register_entity_padatious(entity_name, list):
padatious_intents_container.add_entity(entity_name, list)
# print("[Padatious]: Added entity with name " + entity_name + " with " str(len(list)) + "examples.")
def register_regex_adapt(regex, domain):
adapt_engine.register_regex_entity(regex, domain)
# print("[Adapt]: Added new regex for " + domain)
def register_intent_adapt(intent, domain):
adapt_engine.register_intent_parser(intent, domain=domain)
print("[Adapt]: Registered new intent " + intent.name + " for skill " + domain + ".")
def register_intent_padatious(intent_name, list_of_intent_examples):
padatious_intents_container.add_intent(intent_name, list_of_intent_examples)
print("[Padatious]: Registered new intent " + intent_name + " with " + str(
len(list_of_intent_examples)) + " examples.")
def train_padatious():
padatious_intents_container.train()
def load_all_skills():
for handler in intents_handlers_adapt:
function_handler = intents_handlers_adapt.get(handler)
intent_builder = getattr(function_handler[0], "_data", [])[0]
skill_name = function_handler[1]
register_intent_adapt(intent_builder.build(), domain=skill_name)
for handler in intents_handlers_padatious:
function_handler = intents_handlers_padatious.get(handler)
intent_data_examples = function_handler[1]
register_intent_padatious(handler, intent_data_examples)
def handle(intent_name, data):
module_path_str = None
handler_method_name = None
if intent_name in intents_handlers_adapt:
# something like handler_play_song_spotify (used to call the handler method from the skill imported below)
handler_method_name = intents_handlers_adapt.get(intent_name)[2]
# something like jarvis.skill.entertainment.spotify (used to import the create_skill method to create a new object)
module_path_str = intents_handlers_adapt.get(intent_name)[3]
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if intent_name in intents_handlers_padatious:
handler_method_name = intents_handlers_padatious.get(intent_name)[0]
module_path_str = intents_handlers_padatious.get(intent_name)[2]
if module_path_str is not None and handler_method_name is not None:
# import the create_skill method from the skill using the skill module path
create_skill_method = utils.import_method_from_string(module_path_str, "create_skill")
skill_init_data = {'client_ip': data['client_ip'], 'client_port': data['client_port']}
# create a new object of the right skill for the utterance
skill = create_skill_method(skill_init_data)
# import and call the handler method from the skill
getattr(skill, handler_method_name)(data=data)
def recognise(sentence, client_ip=None, client_port=None):
sentence = sentence.lower()
print(sentence)
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data = dict()
data['client_ip'] = client_ip
data['client_port'] = client_port
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data['utterance'] = sentence
best_intent_adapt = get_best_intent_adapt(sentence)
best_intent_padatious = get_best_intent_padatious(sentence)
confidence_adapt = get_confidence(best_intent_adapt)
confidence_padatious = get_confidence(best_intent_padatious)
if confidence_adapt < 0.2 and confidence_padatious < 0.2:
return "I didn't understand..."
else:
return handle_intent(data,
best_intent_adapt if confidence_adapt > confidence_padatious else best_intent_padatious)
def get_confidence(intent):
if intent is None:
return 0
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if 'confidence' in intent:
return intent['confidence']
elif hasattr(intent, 'conf'):
return intent.conf
else:
return 0
def get_best_intent_adapt(sentence):
if len(intents_handlers_adapt) > 0:
try:
best_intents = adapt_engine.determine_intent(sentence, 100)
best_intent = next(best_intents)
return best_intent
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except StopIteration:
pass
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return None # No match (Adapt)
def get_best_intent_padatious(sentence):
if len(intents_handlers_padatious) > 0:
result = padatious_intents_container.calc_intent(sentence)
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return result
else:
return None # No match (Padatious)
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def handle_intent(data, intent):
if 'intent_type' in intent:
return handle_adapt_intent(data, intent)
elif hasattr(intent, 'name'):
return handle_padatious_intent(data, intent)
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def handle_adapt_intent(data, best_intent):
for key, val in best_intent.items():
if key != 'intent_type' and key != 'target' and key != 'confidence':
data[key] = val
handle(best_intent['intent_type'], data=data)
return best_intent
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def handle_padatious_intent(data, result):
data.update(result.matches) # adding the matches from padatious to the data
handle(result.name, data)
return json.dumps(str(result))