def run(self, key, ctx: Context):
from sagas.nlu.rasa_procs import invoke_nlu
lang = ctx.meta['lang']
if lang not in default_projects:
return False
# proj=default_projects[lang]
proj = lang
def proc(cnt: Text) -> bool:
succ = False
logger.debug('query with rasa-nlu: %s', cnt)
# print(('query with rasa-nlu: %s'%cnt))
resp = invoke_nlu(self.endpoint, proj, "current", cnt)
if resp is not None:
intent = resp["intent"]
entities = resp['entities']
ent_names = {ent['entity'] for ent in entities}
intent_name = intent['name']
intent_confidence = float(intent['confidence'])
self._result = intent_confidence
logger.info('%s(%s) -> %f, with entities %s' %
(cnt, intent_name, intent_confidence,
', '.join(ent_names)))
# print(f'{self.intent}, {self.confidence}')
if self.intent == intent_name and intent_confidence > self.confidence:
# print('... matched intent and confidence')
ctx.add_result(self.name(), 'default', key, {
'intent': intent_name,
'confidence': intent_confidence
})
if self.contains_entity is None:
succ = True
elif self.contains_entity is not None and ent_names.issubset(
self.contains_entity):
succ = True
return succ
if self.entire:
# print('proc -> %s'%key)
return proc(key)
else:
for cnt in ctx.stem_pieces(key):
result = proc(cnt)
if result:
return True
return False
def check_interr(key: Text, ctx: Context, check_fn, lang='pt') -> bool:
for stem in ctx.stem_pieces(key):
interr = get_interrogative(stem, lang)
if interr and check_fn(interr):
return True
return False