def process(self,
statement,
additional_response_selection_parameters=None):
_ = normalize
emotion = Emotion.neutral
self.normalized = normalize(str(statement))
if self.chatbot.globals["reversei"]["type"] is str:
ordinal_statement = str(statement).replace("9th", "ninth")
# FIXME PORT RO
if (cosine_similarity(_(ordinal_statement),
_(self.chatbot.globals["reversei"]["uid"])) >
0.8):
response = "Exactly, you got it right!"
emotion = Emotion.positive
reset_reverse(self)
else:
response = "Close! it was {}".format(
self.chatbot.globals["reversei"]["uid"])
emotion = Emotion.lol
reset_reverse(self)
confidence = 0.99
elif self.chatbot.globals["reversei"]["type"] is bool:
if self.chatbot.globals["reversei"]["uid"] == 30000000001:
"""
NameAdapter: token 30000000001
"""
if ("yes" in self.normalized) or ("yea" in self.normalized):
response = "Ok, will keep that in mind!"
self.chatbot.globals["USERNAME"] = self.chatbot.globals[
"nn"]
self.chatbot.globals["nn"] = None
reset_reverse(self)
else:
response = "Ok, I guess I am smart"
emotion = Emotion.wink
reset_reverse(self)
confidence = 1.0
else:
if ("yes" in self.normalized) or ("yea" in self.normalized):
if len(self.chatbot.globals["history"]["total"]) > 1:
if "joke" in _(
str(self.chatbot.globals["history"]["total"]
[-1])):
joke = pyjokes.get_joke("en", "all")
selected_statement = SugaroidStatement(
joke, chatbot=True)
selected_statement.emotion = Emotion.lol
selected_statement.confidence = 0.95
return selected_statement
else:
# TODO: Not Implemented yet
response = "Ok. (# Not Implemented yet. LOL)"
else:
response = "Ok then, probably next time"
reset_reverse(self)
confidence = 1.0
elif self.chatbot.globals["reversei"]["type"] is None and (
not self.chatbot.globals["reversei"]["uid"] == "CORONAVIRUS"):
fname = False
name = difference(self.normalized,
["my", "name", "is", "good", "be"])
tokenized = nltk.pos_tag(name)
for i in tokenized:
if i[1] == "NN":
fname = i[0]
break
if fname:
response = "Nice to meet you {}".format(fname)
emotion = Emotion.positive
reset_reverse(self)
else:
response = "I couldn't find your name. 🥦"
emotion = Emotion.non_expressive_left
reset_reverse(self)
confidence = 1
elif self.chatbot.globals["reversei"]["type"] is int:
confidence = (
2.0 # FIXME: Override Mathematical Evaluation when not necessary
)
if self.chatbot.globals["reversei"]["uid"] == 30000000002:
"""
WikiAdapter: token 30000000002
"""
if ("yes" in self.normalized) or ("yea" in self.normalized):
response = "I thought you would tell me a number to choose from :/"
emotion = Emotion.seriously
elif ("no" in self.normalized) or ("no" in self.normalized):
response = ("Oops! Sorry about that, seems like what "
"your'e searching for is not on Wikipedia yet")
emotion = Emotion.dead
reset_reverse(self)
else:
chatbot_temporary_data = self.chatbot.globals["temp_data"]
tokenized = nltk.pos_tag(tokenize(str(statement)))
for i in tokenized:
if i[1] == "CD":
try:
num = int(i[0])
except ValueError:
num = text2int(i[0].lower())
index = num - 1
if index < len(chatbot_temporary_data):
response, confidence, stat = wikipedia_search(
self, chatbot_temporary_data[index])
logging.info("REVERSEI: {}".format(response))
confidence = (
1 + confidence
) # FIXME override math evaluation adapter
if not stat:
response = (
"I have some trouble connecting"
"to Wikipedia. Something's not right")
confidence = 1.1
emotion = Emotion.rich
reset_reverse(self)
break
else:
response = "Sorry, I couldn't find the item you were choosing. "
confidence = 1.1
emotion = Emotion.cry_overflow
reset_reverse(self)
break
else:
response = (
"I thought you wanted to know something from wikipedia. "
"Ok, I will try something else")
emotion = Emotion.seriously
reset_reverse(self)
confidence = 1.2
else:
if self.chatbot.globals["reversei"]["uid"] == "CORONAVIRUS":
confidence = 1
NUM = self.chatbot.globals["reversei"]["data"][0]
score = self.chatbot.globals["reversei"]["data"][1]
if NUM == 6:
self.chatbot.globals["reversei"]["enabled"] = False
if score > 3:
response = "You have a high risk of COVID-19"
else:
response = "As per my approximation, you do not have a high risk of COVID-19"
response += (
"\n My approximations might not be correct. "
"You might confirm my results by a legal test")
else:
sia = SentimentIntensityAnalyzer()
_scores = sia.polarity_scores(str(statement))
true_responses = ["yes", "yea", "y", "yup", "true"]
if (any_in(
true_responses +
[x.capitalize() for x in true_responses],
self.normalized,
) or (_scores["pos"] > _scores["neg"])):
score += COVID_QUESTIONS[NUM - 1][2]
response = COVID_QUESTIONS[NUM][1]
self.chatbot.globals["reversei"]["data"] = [NUM + 1, score]
else:
response = "ok"
confidence = 0
selected_statement = SugaroidStatement(response, chatbot=True)
selected_statement.confidence = confidence
selected_statement.emotion = emotion
return selected_statement
def process(self, statement, additional_response_selection_parameters=None):
response = "ok"
confidence = 0
emotion = Emotion.neutral
if raw_in("I", self.tokenized):
logging.info(
str(["{} {} {}".format(k, k.tag_, k.pos_) for k in self.tokenized])
)
# check if the pronoun has been reached yet, otherwise may detect some other nouns
start_scanning = False
for i in self.tokenized:
if i.pos_ == "PRON" and not i.tag_.startswith("W"):
start_scanning = True
if start_scanning:
pass
elif (
(i.pos_ != "PRON")
or (not start_scanning)
or (i.tag_.startswith("W"))
):
logging.info("MeAdapter: Skipping {} {}".format(i.lower_, i.tag_))
continue
logging.info("MeAdapter: Scanning :: {} : {}".format(i.text, i.pos_))
if (i.pos_ == "PROPN") or (i.tag_ == "NN"):
nn = i.text
if self.chatbot.globals["USERNAME"]:
response = (
"Are you sure you are {n}? I thought you were {u}".format(
n=nn, u=self.chatbot.globals["USERNAME"]
)
)
emotion = Emotion.wink
if i.pos_ == "PROPN":
confidence = 0.95
else:
confidence = 0.8
self.chatbot.globals["nn"] = nn
self.chatbot.globals["reversei"]["uid"] = 30000000001
self.chatbot.globals["reversei"]["type"] = bool
self.chatbot.globals["reversei"]["enabled"] = True
emotion = Emotion.non_expressive_left
break
else:
if not ("not" in str(statement)):
if i.lower_ == "sugaroid":
response = random_response(I_AM)
emotion = Emotion.lol
confidence = 0.95
else:
response = random_response(GREET).format(
str(nn).capitalize()
)
confidence = 0.9
self.chatbot.globals["USERNAME"] = nn
emotion = Emotion.positive
break
else:
response = "Ok!"
confidence = 0.5
emotion = Emotion.seriously
break
elif i.lower_ == "sugaroid":
response = random_response(I_AM)
emotion = Emotion.lol
confidence = 0.95
else:
sia = SentimentIntensityAnalyzer()
ps = sia.polarity_scores(str(i.sent))
confidence = 0.35
if ps["neu"] == 1:
response = "Ok! Thats great to hear from you"
emotion = Emotion.lol
elif ps["pos"] > ps["neg"]:
response = "Yay! I agree to you"
emotion = Emotion.positive
else:
confidence = 0.2
response = "Think again"
emotion = Emotion.non_expressive_left
elif raw_lower_in("you", self.tokenized):
logging.info(
str(["{} {} {}".format(k, k.tag_, k.pos_) for k in self.tokenized])
)
nn = ""
start_scanning = False
for i in self.tokenized:
if i.pos_ == "PRON" and not i.tag_.startswith("W"):
start_scanning = True
if start_scanning:
pass
elif (
(i.pos_ != "PRON")
or (not start_scanning)
or (i.tag_.startswith("W"))
):
logging.info(
"MeAdapter: Skipping {} {} ss={} {}".format(
i.lower_, i.tag_, not start_scanning, i.pos_
)
)
continue
logging.info("MeAdapter: Scanning :: {} : {}".format(i.text, i.pos_))
if i.pos_ == "ADJ":
try:
cos = cosine_similarity([str(i.lower_)], ["sugaroid"])
except ZeroDivisionError:
cos = 0.0
if i.lower_ == "sugaroid":
nn = i.text
response = "Yup, that's my name. I am sugaroid"
emotion = Emotion.lol
confidence = 0.9
break
elif cos > 0.9:
response = "Yes, you were close! My name is sugaroid"
emotion = Emotion.positive
confidence = 0.9
break
else:
if i.lower_ in ["human", "animal", "bird"]:
response = "No, I am not a {adj}. I am a robot".format(
adj=i.lower_
)
emotion = Emotion.angry_non_expressive
confidence = 0.9
else:
response = "seriously?"
emotion = Emotion.angry
confidence = 0.09
elif i.pos_ == "PROPN":
cos = cosine_similarity([str(i.lower_)], ["sugaroid"])
if i.lower_ == "sugaroid":
nn = i.text
response = "Yup, that's my name. I am sugaroid"
emotion = Emotion.lol
confidence = 0.9
break
elif cos > 0.9:
response = "Yes, you were close! My name is sugaroid"
emotion = Emotion.positive
confidence = 0.9
break
elif i.lower_ in WHAT_I_AM_GOING_TO_DO:
confidence = 0.4
response = "Perhaps, I will sit simply, and smile."
emotion = Emotion.lol
else:
nn = i.text
response = "Nope, I am not {n}, I am sugaroid".format(n=nn)
emotion = Emotion.angry
confidence = 0.9
elif i.tag_ == "NN":
if i.lower_ in ["bot", "robot", "computer", "silicon", "infant"]:
response = "You are right! I am a {}".format(i.lower_)
confidence = 0.9
emotion = Emotion.positive
elif i.lower_ in [
"human",
"bird",
"animal",
"tree",
"politician",
"player",
"liar",
"priest",
]:
response = "No way! I can't imagine myself to be a {}".format(
i.lower_
)
confidence = 0.9
emotion = Emotion.vomit
else:
logging.info(
"MeAdapter: Couldn't classify type of noun {}".format(
i.lower_
)
)
confidence = 0.9
sia = SentimentIntensityAnalyzer()
ps = sia.polarity_scores(str(i.sent))
if ps["neu"] == 1.0:
# try presence adapter pieces
presence_statement = process_what_ami_doing(statement)
if presence_statement.confidence == 0:
response = (
"I will need more time to learn if that actually makes sense with respect to "
"myself. "
)
emotion = Emotion.cry
else:
return presence_statement
elif ps["pos"] > ps["neg"]:
response = "I guess I am {}. Thanks!".format(i.text)
emotion = Emotion.wink
else:
response = "I am not {}! I am Sugaroid.".format(i.lower_)
emotion = Emotion.angry
elif i.tag_.startswith("VB"):
root_verb = i.lemma_
if root_verb in [
"say",
"tell",
"speak",
"murmur",
"blabber",
"flirt",
]:
response = random_response(BURN_IDK)
emotion = Emotion.lol
confidence = 0.8
else:
presence_statement = process_what_ami_doing(statement)
if presence_statement.confidence == 0:
# FIXME : Add more logic here
response = "Ok"
confidence = 0.05
emotion = Emotion.non_expressive_left
else:
return presence_statement
selected_statement = SugaroidStatement(response, chatbot=True)
selected_statement.confidence = confidence
selected_statement.emotion = emotion
return selected_statement
def process(self,
statement,
additional_response_selection_parameters=None):
response = 'ok'
confidence = 0
emotion = Emotion.neutral
if raw_in('I', self.tokenized):
logging.info(
str([
"{} {} {}".format(k, k.tag_, k.pos_)
for k in self.tokenized
]))
# check if the pronoun has been reached yet, otherwise may detect some other nouns
start_scanning = False
for i in self.tokenized:
if i.pos_ == 'PRON' and not i.tag_.startswith("W"):
start_scanning = True
if start_scanning:
pass
elif (i.pos_ != 'PRON') or (not start_scanning) or (
i.tag_.startswith('W')):
logging.info("MeAdapter: Skipping {} {}".format(
i.lower_, i.tag_))
continue
logging.info("MeAdapter: Scanning :: {} : {}".format(
i.text, i.pos_))
if (i.pos_ == 'PROPN') or (i.tag_ == 'NN'):
nn = i.text
if self.chatbot.globals['USERNAME']:
response = "Are you sure you are {n}? I thought you were {u}".format(
n=nn, u=self.chatbot.globals['USERNAME'])
emotion = Emotion.wink
if i.pos_ == 'PROPN':
confidence = 0.95
else:
confidence = 0.8
self.chatbot.globals['nn'] = nn
self.chatbot.globals['reversei']['uid'] = 30000000001
self.chatbot.globals['reversei']['type'] = bool
self.chatbot.globals['reversei']['enabled'] = True
emotion = Emotion.non_expressive_left
break
else:
if not ('not' in str(statement)):
if i.lower_ == 'sugaroid':
response = random_response(I_AM)
emotion = Emotion.lol
confidence = 0.95
else:
response = random_response(GREET).format(
str(nn).capitalize())
confidence = 0.9
self.chatbot.globals['USERNAME'] = nn
emotion = Emotion.positive
break
else:
response = 'Ok!'
confidence = 0.5
emotion = Emotion.seriously
break
elif i.lower_ == 'sugaroid':
response = random_response(I_AM)
emotion = Emotion.lol
confidence = 0.95
else:
sia = SentimentIntensityAnalyzer()
ps = sia.polarity_scores(str(i.sent))
confidence = 0.35
if ps['neu'] == 1:
response = 'Ok! Thats great to hear from you'
emotion = Emotion.lol
elif ps['pos'] > ps['neg']:
response = 'Yay! I agree to you'
emotion = Emotion.positive
else:
confidence = 0.2
response = 'Think again'
emotion = Emotion.non_expressive_left
elif raw_lower_in('you', self.tokenized):
logging.info(
str([
"{} {} {}".format(k, k.tag_, k.pos_)
for k in self.tokenized
]))
nn = ''
start_scanning = False
for i in self.tokenized:
if i.pos_ == 'PRON' and not i.tag_.startswith("W"):
start_scanning = True
if start_scanning:
pass
elif (i.pos_ != 'PRON') or (not start_scanning) or (
i.tag_.startswith('W')):
logging.info("MeAdapter: Skipping {} {} ss={} {}".format(
i.lower_, i.tag_, not start_scanning, i.pos_))
continue
logging.info("MeAdapter: Scanning :: {} : {}".format(
i.text, i.pos_))
if i.pos_ == 'ADJ':
try:
cos = cosine_similarity([str(i.lower_)], ['sugaroid'])
except ZeroDivisionError:
cos = 0.0
if i.lower_ == 'sugaroid':
nn = i.text
response = "Yup, that's my name. I am sugaroid"
emotion = Emotion.lol
confidence = 0.9
break
elif cos > 0.9:
response = "Yes, you were close! My name is sugaroid"
emotion = Emotion.positive
confidence = 0.9
break
else:
if i.lower_ in ['human', 'animal', 'bird']:
response = 'No, I am not a {adj}. I am a robot'.format(
adj=i.lower_)
emotion = Emotion.angry_non_expressive
confidence = 0.9
else:
response = 'seriously?'
emotion = Emotion.angry
confidence = 0.09
elif i.pos_ == 'PROPN':
cos = cosine_similarity([str(i.lower_)], ['sugaroid'])
if i.lower_ == 'sugaroid':
nn = i.text
response = "Yup, that's my name. I am sugaroid"
emotion = Emotion.lol
confidence = 0.9
break
elif cos > 0.9:
response = "Yes, you were close! My name is sugaroid"
emotion = Emotion.positive
confidence = 0.9
break
else:
nn = i.text
response = "Nope, I am not {n}, I am sugaroid".format(
n=nn)
emotion = Emotion.angry
confidence = 0.9
elif i.tag_ == 'NN':
if i.lower_ in [
'bot', 'robot', 'computer', 'silicon', 'infant'
]:
response = 'You are right! I am a {}'.format(i.lower_)
confidence = 0.9
emotion = Emotion.positive
elif i.lower_ in [
'human', 'bird', 'animal', 'tree', 'politician',
'player', 'liar', 'priest'
]:
response = 'No way! I can\'t imagine myself to be a {}'.format(
i.lower_)
confidence = 0.9
emotion = Emotion.vomit
else:
logging.info(
"MeAdapter: Couldn't classify type of noun {}".
format(i.lower_))
confidence = 0.9
sia = SentimentIntensityAnalyzer()
ps = sia.polarity_scores(str(i.sent))
if ps['neu'] == 1.0:
# try presence adapter pieces
presence_statement = process_what_ami_doing(
statement)
if presence_statement.confidence == 0:
response = 'I will need more time to learn if that actually makes sense with respect to ' \
'myself. '
emotion = Emotion.cry
else:
return presence_statement
elif ps['pos'] > ps['neg']:
response = 'I guess I am {}. Thanks!'.format(
i.text)
emotion = Emotion.wink
else:
response = 'I am not {}! I am Sugaroid.'.format(
i.lower_)
emotion = Emotion.angry
elif i.tag_.startswith('VB'):
root_verb = i.lemma_
if root_verb in [
'say', 'tell', 'speak', 'murmur', 'blabber',
'flirt'
]:
response = random_response(BURN_IDK)
emotion = Emotion.lol
confidence = 0.8
else:
presence_statement = process_what_ami_doing(statement)
if presence_statement.confidence == 0:
# FIXME : Add more logic here
response = 'Ok'
confidence = 0.05
emotion = Emotion.non_expressive_left
else:
return presence_statement
selected_statement = SugaroidStatement(response, chatbot=True)
selected_statement.confidence = confidence
selected_statement.emotion = emotion
return selected_statement
def process(self,
statement,
additional_response_selection_parameters=None):
_ = normalize
emotion = Emotion.neutral
self.normalized = normalize(str(statement))
if self.chatbot.globals['reversei']['type'] is str:
ordinal_statement = str(statement).replace('9th', 'ninth')
# FIXME PORT RO
if cosine_similarity(
_(ordinal_statement),
_(self.chatbot.globals['reversei']['uid'])) > 0.8:
response = 'Exactly, you got it right!'
emotion = Emotion.positive
reset_reverse(self)
else:
response = 'Close! it was {}'.format(
self.chatbot.globals['reversei']['uid'])
emotion = Emotion.lol
reset_reverse(self)
confidence = 0.99
elif self.chatbot.globals['reversei']['type'] is bool:
if self.chatbot.globals['reversei']['uid'] == 30000000001:
"""
NameAdapter: token 30000000001
"""
if ('yes' in self.normalized) or ('yea' in self.normalized):
response = "Ok, will keep that in mind!"
self.chatbot.globals['USERNAME'] = self.chatbot.globals[
'nn']
self.chatbot.globals['nn'] = None
reset_reverse(self)
else:
response = "Ok, I guess I am smart"
emotion = Emotion.wink
reset_reverse(self)
confidence = 1.0
else:
if ('yes' in self.normalized) or ('yea' in self.normalized):
if len(self.chatbot.globals['history']['total']) > 1:
if 'joke' in _(
str(self.chatbot.globals['history']['total']
[-1])):
joke = pyjokes.get_joke('en', 'all')
selected_statement = SugaroidStatement(
joke, chatbot=True)
selected_statement.emotion = Emotion.lol
selected_statement.confidence = 0.95
return selected_statement
else:
# TODO: Not Implemented yet
response = 'Ok. (# Not Implemented yet. LOL)'
else:
response = 'Ok then, probably next time'
reset_reverse(self)
confidence = 1.0
elif self.chatbot.globals['reversei']['type'] is None and \
(not self.chatbot.globals['reversei']['uid'] == 'CORONAVIRUS'):
fname = False
name = difference(self.normalized,
['my', 'name', 'is', 'good', 'be'])
tokenized = nltk.pos_tag(name)
for i in tokenized:
if i[1] == 'NN':
fname = i[0]
break
if fname:
response = "Nice to meet you {}".format(fname)
emotion = Emotion.positive
reset_reverse(self)
else:
response = "I couldn't find your name. 🥦"
emotion = Emotion.non_expressive_left
reset_reverse(self)
confidence = 1
elif self.chatbot.globals['reversei']['type'] is int:
confidence = 2.0 # FIXME: Override Mathematical Evaluation when not necessary
if self.chatbot.globals['reversei']['uid'] == 30000000002:
"""
WikiAdapter: token 30000000002
"""
if ('yes' in self.normalized) or ('yea' in self.normalized):
response = "I thought you would tell me a number to choose from :/"
emotion = Emotion.seriously
elif ('no' in self.normalized) or ('no' in self.normalized):
response = 'Oops! Sorry about that, seems like what you\'re searching for is not on Wikipedia yet'
emotion = Emotion.dead
reset_reverse(self)
else:
chatbot_temporary_data = self.chatbot.globals['temp_data']
tokenized = nltk.pos_tag(tokenize(str(statement)))
for i in tokenized:
if i[1] == 'CD':
try:
num = int(i[0])
except ValueError:
num = text2int(i[0].lower())
index = num - 1
if index < len(chatbot_temporary_data):
response, confidence, stat = wikipedia_search(
self, chatbot_temporary_data[index])
logging.info('REVERSEI: {}'.format(response))
confidence = 1 + confidence # FIXME override math evaluation adapter
if not stat:
response = "I have some trouble connecting to Wikipedia. Something's not right"
confidence = 1.1
emotion = Emotion.rich
reset_reverse(self)
break
else:
response = "Sorry, I couldn't find the item you were choosing. "
confidence = 1.1
emotion = Emotion.cry_overflow
reset_reverse(self)
break
else:
response = 'I thought you wanted to know something from wikipedia. ' \
'Ok, I will try something else'
emotion = Emotion.seriously
reset_reverse(self)
confidence = 1.2
else:
if self.chatbot.globals['reversei']['uid'] == 'CORONAVIRUS':
confidence = 1
NUM = self.chatbot.globals['reversei']['data'][0]
score = self.chatbot.globals['reversei']['data'][1]
if NUM == 6:
self.chatbot.globals['reversei']['enabled'] = False
if score > 3:
response = 'You have a high risk of COVID-19'
else:
response = 'As per my approximation, you do not have a high risk of COVID-19'
response += "\n My approximations might not be correct. " \
"You might confirm my results by a legal test"
else:
sia = SentimentIntensityAnalyzer()
_scores = sia.polarity_scores(str(statement))
true_responses = ['yes', 'yea', 'y', 'yup', 'true']
if any_in(
true_responses +
[x.capitalize()
for x in true_responses], self.normalized) or (
_scores['pos'] > _scores['neg']):
score += COVID_QUESTIONS[NUM - 1][2]
response = COVID_QUESTIONS[NUM][1]
self.chatbot.globals['reversei']['data'] = [NUM + 1, score]
else:
response = 'ok'
confidence = 0
selected_statement = SugaroidStatement(response, chatbot=True)
selected_statement.confidence = confidence
selected_statement.emotion = emotion
return selected_statement