Source code for chatterbot.logic.time_adapter
from datetime import datetime
from chatterbot import constants, languages
from chatterbot.logic import LogicAdapter
from chatterbot.conversation import Statement
import spacy
[docs]
class TimeLogicAdapter(LogicAdapter):
"""
The TimeLogicAdapter returns the current time.
:kwargs:
* *positive* (``list``) --
The time-related questions used to identify time questions about the current time.
Defaults to a list of English sentences.
* *language* (``str``) --
The language for the spacy model. Defaults to English.
"""
def __init__(self, chatbot, **kwargs):
super().__init__(chatbot, **kwargs)
# TODO / FUTURE: Switch `positive` to `patterns` for more accurate naming
phrases = kwargs.get('positive', [
'What time is it?',
'Hey, what time is it?',
'Do you have the time?',
'Do you know the time?',
'Do you know what time it is?',
'What is the time?',
'What time is it now?',
'Can you tell me the time?',
'Could you tell me the time?',
'What is the current time?',
])
language = kwargs.get('language', languages.ENG)
try:
model = constants.DEFAULT_LANGUAGE_TO_SPACY_MODEL_MAP[language]
except KeyError as e:
raise KeyError(
f'Spacy model is not available for language {language}'
) from e
self.nlp = spacy.load(model)
# Set up rules for spacy's rule-based matching
# https://spacy.io/usage/rule-based-matching
self.matcher = spacy.matcher.PhraseMatcher(self.nlp.vocab)
patterns = [self.nlp.make_doc(text) for text in phrases]
# Add the patterns to the matcher
self.matcher.add('TimeQuestionList', patterns)
def process(self, statement, additional_response_selection_parameters=None):
now = datetime.now()
# Check if the input statement contains a time-related question
doc = self.nlp(statement.text)
matches = self.matcher(doc)
self.chatbot.logger.info('TimeLogicAdapter detected {} matches'.format(len(matches)))
confidence = 1 if matches else 0
response = Statement(text='The current time is ' + now.strftime('%I:%M %p'))
response.confidence = confidence
return response
