166 lines
5.6 KiB
Python
166 lines
5.6 KiB
Python
import json
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from adapt.engine import DomainIntentDeterminationEngine
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from padatious import IntentContainer
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from jarvis.utils import utils
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adapt_engine = DomainIntentDeterminationEngine()
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padatious_intents_container = IntentContainer('intent_cache')
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intents_handlers_adapt = dict()
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intents_handlers_padatious = dict()
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def register_entity_adapt(entity_value, entity_type, domain):
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adapt_engine.register_entity(entity_value=entity_value, entity_type=entity_type, domain=domain)
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# print("[Adapt]: Added entity with type " + entity_type + " for " + domain)
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def register_entity_padatious(entity_name, file_lines_list):
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padatious_intents_container.add_entity(entity_name, file_lines_list)
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# print("[Padatious]: Added entity with name " + entity_name + " with " str(len(list)) + "examples.")
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def register_regex_adapt(regex, domain):
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adapt_engine.register_regex_entity(regex, domain)
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# print("[Adapt]: Added new regex for " + domain)
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def register_intent_adapt(intent, domain):
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adapt_engine.register_intent_parser(intent, domain=domain)
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print("[Adapt]: Registered new intent " + intent.name + " for skill " + domain + ".")
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def register_intent_padatious(intent_name, list_of_intent_examples):
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padatious_intents_container.add_intent(intent_name, list_of_intent_examples)
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print("[Padatious]: Registered new intent " + intent_name + " with " + str(
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len(list_of_intent_examples)) + " examples.")
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def train_padatious():
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padatious_intents_container.train()
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def load_all_skills():
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for handler in intents_handlers_adapt:
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function_handler = intents_handlers_adapt.get(handler)
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intent_builder = getattr(function_handler[0], "_data", [])[0]
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skill_name = function_handler[1]
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register_intent_adapt(intent_builder.build(), domain=skill_name)
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for handler in intents_handlers_padatious:
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function_handler = intents_handlers_padatious.get(handler)
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intent_data_examples = function_handler[1]
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register_intent_padatious(handler, intent_data_examples)
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def handle(intent_name, data):
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module_path_str = None
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handler_method_name = None
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if intent_name in intents_handlers_adapt:
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# something like handler_play_song_spotify (used to call the handler method from the skill imported below)
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handler_method_name = intents_handlers_adapt.get(intent_name)[2]
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# something like jarvis.skill.entertainment.spotify (used to import the create_skill method to create a new object)
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module_path_str = intents_handlers_adapt.get(intent_name)[3]
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if intent_name in intents_handlers_padatious:
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handler_method_name = intents_handlers_padatious.get(intent_name)[0]
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module_path_str = intents_handlers_padatious.get(intent_name)[2]
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if module_path_str is not None and handler_method_name is not None:
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# import the create_skill method from the skill using the skill module path
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create_skill_method = utils.import_method_from_string(module_path_str, "create_skill")
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skill_init_data = {'client_ip': data['client_ip'], 'client_port': data['client_port']}
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# create a new object of the right skill for the utterance
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skill = create_skill_method(skill_init_data)
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# import and call the handler method from the skill
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getattr(skill, handler_method_name)(data=data)
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def train_padatious():
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print("Training PADATIOUS intents models, can take a few minutes (first time) or a few seconds (startup)")
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padatious_intents_container.train(timeout=120)
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def recognise(sentence, client_ip=None, client_port=None):
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sentence = sentence.lower()
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print(sentence)
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data = dict()
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data['client_ip'] = client_ip
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data['client_port'] = client_port
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data['utterance'] = sentence
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best_intent_adapt = get_best_intent_adapt(sentence)
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best_intent_padatious = get_best_intent_padatious(sentence)
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confidence_adapt = get_confidence(best_intent_adapt)
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confidence_padatious = get_confidence(best_intent_padatious)
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if confidence_adapt < 0.2 and confidence_padatious < 0.2:
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return "I didn't understand..."
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else:
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return handle_intent(data,
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best_intent_adapt if confidence_adapt > confidence_padatious else best_intent_padatious)
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def get_confidence(intent):
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if intent is None:
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return 0
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if 'confidence' in intent:
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return intent['confidence']
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elif hasattr(intent, 'conf'):
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return intent.conf
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else:
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return 0
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def get_best_intent_adapt(sentence):
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if len(intents_handlers_adapt) > 0:
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try:
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best_intents = adapt_engine.determine_intent(sentence, 100)
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best_intent = next(best_intents)
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return best_intent
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except StopIteration:
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pass
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return None # No match (Adapt)
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def get_best_intent_padatious(sentence):
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if len(intents_handlers_padatious) > 0:
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result = padatious_intents_container.calc_intent(sentence)
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return result
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else:
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return None # No match (Padatious)
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def handle_intent(data, intent):
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if 'intent_type' in intent:
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return handle_adapt_intent(data, intent)
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elif hasattr(intent, 'name'):
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return handle_padatious_intent(data, intent)
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def handle_adapt_intent(data, best_intent):
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for key, val in best_intent.items():
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if key != 'intent_type' and key != 'target' and key != 'confidence':
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data[key] = val
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handle(best_intent['intent_type'], data=data)
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return best_intent
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def handle_padatious_intent(data, result):
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data.update(result.matches) # adding the matches from padatious to the data
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handle(result.name, data)
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return json.dumps(str(result))
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