def __init__(self, name, **kwargs):
ChatBot.__init__(self, name=name, **kwargs)
self.lp = LanguageProcessor()
self.spell_checker = False # FIXME
self.discord = False
self.authors = []
self.interrupt = 0
self.report = False
self.globals = {
"emotion": Emotion.neutral,
"history": {"total": [0], "user": [0], "types": [0]},
"reversei": {
"enabled": False,
"uid": None,
"type": None,
},
"akinator": {"enabled": False, "class": None},
"hangman": {"enabled": False, "class": None},
"adapters": [],
"fun": True,
"update": False,
"last_news": None,
"USERNAME": None,
"learn": False,
"trivia_answer": None,
"learn_last_conversation": [],
"DEBUG": {},
}
def __init__(self, name, **kwargs):
ChatBot.__init__(self, name=name, **kwargs)
self.lp = LanguageProcessor()
self.spell_checker = False # FIXME
self.discord = False
self.authors = []
self.interrupt = 0
self.report = False
self.globals = {
'emotion': Emotion.neutral,
'history': {
'total': [0],
'user': [0],
'types': [0]
},
'reversei': {
'enabled': False,
'uid': None,
'type': None,
},
'akinator': {
'enabled': False,
'class': None
},
'hangman': {
'enabled': False,
'class': None
},
'adapters': [],
'fun': True,
'update': False,
'last_news': None,
'USERNAME': None,
'learn': False,
'trivia_answer': None,
'learn_last_conversation': [],
'DEBUG': {}
}
def reverse(token):
"""
Reverses the first person pronouns to second person pronouns and vice versa
:param token: a nltk.word_tokenize type list
:return: a list similar to nltk.word_tokenize
"""
processed = []
has_am = "am" in token
has_is = "are" in token
logging.info("Reverse: Received {}".format(token))
interrogation = False
for i in token:
lps = LanguageProcessor().tokenize(i)[0]
if lps.tag_ == "." and lps.lower_ == "?":
interrogation = True
elif str(lps.tag_).startswith("W"):
interrogation = True
for i in token:
tagged = nltk.pos_tag([i])
if tagged[0][1] == "PRP":
if i == "you":
if interrogation:
processed.append("I")
else:
processed = processed[:-1] + ["I"] + processed[-1:]
elif i.lower() == "i":
processed.append("you")
elif tagged[0][1] == "VBP":
if i == "are":
if "I" in processed:
processed.append("am")
else:
processed.append("are")
elif i == "am":
if "I" in processed:
processed.append("am")
else:
processed.append("are")
else:
processed.append("are")
else:
processed.append(i)
for j in range(0, len(processed) - 2):
if processed[j] == "I" and processed[j + 1] == "are":
processed[j + 1] = "am"
elif processed[j] == "you" and processed[j + 1] == "am":
processed[j + 1] = "are"
else:
continue
for j in range(0, len(processed) - 2):
if processed[j] == "I" and processed[j + 1] == "are":
processed[j] = "you"
elif processed[j] == "you" and processed[j + 1] == "am":
processed[j] = "I"
else:
continue
for j in range(0, len(processed) - 2):
if processed[j] == "are" and processed[j + 1] == "I":
processed[j] = "am"
elif processed[j] == "am" and processed[j + 1] == "you":
processed[j] = "are"
else:
continue
logging.info("Reverse: Pushing {}".format(processed))
return processed
if os.getenv('SUGAROID_DEBUG') in ('true', 'True'):
# set the verbosity
verbosity = logging.INFO
logging.basicConfig(level=verbosity)
try:
from PyQt5 import QtCore, QtWidgets # noqa:
from PyQt5.QtWidgets import QApplication # noqa:
GUI_DEPS = True
except (ModuleNotFoundError, ImportError) as e:
print("warn: Could not import PyQt5", e)
GUI_DEPS = False
SPACY_LANG_PROCESSOR = LanguageProcessor()
class SugaroidStatement(Statement):
"""
A modified chatterbot Statement with the additional parameters
The Chatterbot Statement did not preserve the capabilities to hold
fundamental data such as name of the adapter and emotion of the statemnt passed
The emotion was either a <class 'Emotion'> type or NoneType
The Adapter was the generic name of the adapter in string type determined
by the __gtype__ variable
"""
def __init__(self, text, in_response_to=None, **kwargs):
Statement.__init__(self, text, in_response_to, **kwargs)
self.emotion = kwargs.get('emotion', Emotion.neutral)
self.adapter = kwargs.get('type_', '')
def reverse(token):
"""
Reverses the first person pronouns to second person pronouns and vice versa
:param token: a nltk.word_tokenize type list
:return: a list similar to nltk.word_tokenize
"""
processed = []
has_am = 'am' in token
has_is = 'are' in token
logging.info("Reverse: Received {}".format(token))
interrogation = False
for i in token:
lps = LanguageProcessor().tokenize(i)[0]
if lps.tag_ == '.' and lps.lower_ == '?':
interrogation = True
elif str(lps.tag_).startswith('W'):
interrogation = True
for i in token:
tagged = nltk.pos_tag([i])
if tagged[0][1] == 'PRP':
if i == 'you':
if interrogation:
processed.append('I')
else:
processed = processed[:-1] + ['I'] + processed[-1:]
elif i.lower() == 'i':
processed.append('you')
elif tagged[0][1] == 'VBP':
if i == 'are':
if 'I' in processed:
processed.append('am')
else:
processed.append('are')
elif i == 'am':
if 'I' in processed:
processed.append('am')
else:
processed.append('are')
else:
processed.append('are')
else:
processed.append(i)
for j in range(0, len(processed) - 2):
if processed[j] == 'I' and processed[j + 1] == 'are':
processed[j + 1] = 'am'
elif processed[j] == 'you' and processed[j + 1] == 'am':
processed[j + 1] = 'are'
else:
continue
for j in range(0, len(processed) - 2):
if processed[j] == 'I' and processed[j + 1] == 'are':
processed[j] = 'you'
elif processed[j] == 'you' and processed[j + 1] == 'am':
processed[j] = 'I'
else:
continue
for j in range(0, len(processed) - 2):
if processed[j] == 'are' and processed[j + 1] == 'I':
processed[j] = 'am'
elif processed[j] == 'am' and processed[j + 1] == 'you':
processed[j] = 'are'
else:
continue
logging.info("Reverse: Pushing {}".format(processed))
return processed
from typing import List, Generator
from chatterbot.conversation import Statement
from spacy.tokens.doc import Doc
from sugaroid.brain.postprocessor import random_response
from sugaroid.brain.preprocessors import tokenize
from sugaroid.brain.utils import LanguageProcessor
lang_processor = LanguageProcessor()
class SugaroidStatement(Statement):
"""
A modified chatterbot Statement with the additional parameters
The Chatterbot Statement did not preserve the capabilities to hold
fundamental data such as name of the adapter and emotion of the statement passed
The emotion was either a <class 'Emotion'> type or NoneType
The Adapter was the generic name of the adapter in string type determined
by the __gtype__ variable
"""
def __init__(self, text: str, in_response_to=None, emotion: int = None, **kwargs):
super(SugaroidStatement, self).__init__(text, in_response_to, **kwargs)
self._doc = None
self._simple = None
self._words = None
self._emotion = emotion
self._text = text