class TestAnalyticsEngineEnglish(TestCase):
def setUp(self):
self.ae = AnalyticsEngine(lang=LANG.EN)
def test_analyze_utterance_1(self):
utterance = u'Peter is the father of Tom.'
result = self.ae.analyze_utterance(utterance, persist=True)
assert result == [('peter', 'father-of', 'tom')]
def test_analyze_utterance_2(self):
utterance = u'My daughter Lisa is moving to London next month.'
result = self.ae.analyze_utterance(utterance)
assert result == [('lisa', 'daughter-of', 'USER')]
# TODO fix
def test_analyze_utterance_3(self):
utterance = u'''Tom's sister Lisa lives in London now.'''
result = self.ae.analyze_utterance(utterance)
assert result == [('lisa', 'sister-of', 'tom')]
def test_analyze_utterance_4(self):
utterance = u'''Peter, Tom's father, will pick us up.'''
result = self.ae.analyze_utterance(utterance)
assert result == [('peter', 'father-of', 'tom')]
def test_analyze_utterance_5(self):
utterance = u'''my sister , madonna , does too .'''
result = self.ae.analyze_utterance(utterance)
assert result == [('madonna', 'sister-of', 'USER')]
def run(self, dispatcher, tracker, domain):
utterance = tracker.latest_message()
ae = AnalyticsEngine(lang=LANG.DE)
result, response_mesage = ae.analyze_utterance(utterance, persist=True)
if response_mesage:
dispatcher.utter_message(response_mesage)
def validate(in_file, out_file):
"""
Experimental evaluation on 1000 utterances of 'Persona-Chat corpus' and 'Friends TV Corpus'
"""
ae = AnalyticsEngine(LANG.EN)
with open(
in_file,
'r', encoding='utf-8') as f:
for line in f.readlines():
ae.analyze_utterance(line, persist=False, validate=True, out_val_file=out_file)
class TestAnalyticsEngineGerman(TestCase):
def setUp(self):
self.ae = AnalyticsEngine(lang=LANG.DE)
def test_analyze_utterance_1(self):
result = self.ae.analyze_utterance(u'Hans und sein Sohn Hubert.')
assert result == [('hubert', 'son-of', 'hans')]
class SocialRelationExtractor(Component):
name = "relationextractor"
provides = ["entities"]
#requires = [""]
defaults = {}
language_list = ["de_core_news_sm"]
def __init__(self, component_config=None):
super(SocialRelationExtractor, self).__init__(component_config)
self.re = RelationExtractor(LANG.DE)
self.ae = AnalyticsEngine(LANG.DE)
self.rt = RelationTypes()
def process(self, message, **kwargs):
print(f'Processing Message {message.text}')
extracted_relations, response_message = self.ae.analyze_utterance(
message.text, persist=True)
print(f'Extracted relations: {extracted_relations}')
if extracted_relations:
if len(extracted_relations[0]) == 3:
entity_value = extracted_relations[0][2]
else:
entity_value = self.rt.get_relation_from_relation_type_DE(
extracted_relations[0][1])
entities = [{
"value": entity_value,
"confidence": 1,
"entity": "relativename",
"extractor": "relationextractor"
}, {
"value": True,
"confidence": 1,
"entity": "relationextracted",
"extractor": "relationextractor"
}]
message.set("entities", entities, add_to_output=True)
def run(self, dispatcher, tracker, domain):
kg = NetworkGraph()
contact_name = tracker.get_slot('firstname')
relation_ship = tracker.get_slot('relationship')
me_name = tracker.get_slot('me_name')
utterance = tracker.latest_message()
ae = AnalyticsEngine(lang=LANG.DE)
# search relationship by contact name
if me_name and contact_name:
relationship = kg.search_relationship_by_contactname(
me_name, contact_name)
if relationship:
SlotSet("relationship", relationship)
dispatcher.utter_message("Deine(n) " + relationship + " " +
str(contact_name).title() + "?")
else:
ae.analyze_utterance(utterance, persist=True)
# search contact name by given relationship
elif me_name and relation_ship:
contact = kg.search_contactname_by_relationship(
me_name, relation_ship)
if contact: # contact already exists in network
SlotSet("contactname", contact)
dispatcher.utter_message("Meinst du " + contact + "?")
else:
ae.analyze_utterance(utterance, persist=True)
elif me_name:
dispatcher.utter_message(
"Leider hab ich dich nicht ganz verstanden. Wen willst du mitnehmen?"
)
else:
dispatcher.utter_message("Leider kenne ich dich noch nicht. "
"Willst du mir sagen wie du heißt?")
def __init__(self, component_config=None):
super(SocialRelationExtractor, self).__init__(component_config)
self.re = RelationExtractor(LANG.DE)
self.ae = AnalyticsEngine(LANG.DE)
self.rt = RelationTypes()
def setUp(self):
self.ae = AnalyticsEngine(lang=LANG.DE)