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ml.py
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ml.py
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from textblob import TextBlob
import random
from sklearn.feature_extraction.text import TfidfVectorizer
from PyDictionary import PyDictionary
class mls:
def __init__(self, text):
self.text = text
self.blob = TextBlob(text)
self.dictionary = PyDictionary()
self.sentences = self.text.split(".")
self.getTags()
def getTags(self):
self.noun = {}
self.properNoun = {}
self.adjectives = {}
for i in self.blob.tags:
if i[1] == 'NNP':
if i[0] in self.properNoun.keys():
self.properNoun[i[0]] += 1
else:
self.properNoun[i[0]] = 1
if i[1] == 'NN':
if i[0] in self.noun.keys():
self.noun[i[0]] += 1
else:
self.noun[i[0]] = 1
if i[1] == 'JJ':
if i[0] in self.adjectives.keys():
self.adjectives[i[0]] += 1
else:
self.adjectives[i[0]] = 1
self.properNoun = dict(sorted(self.properNoun.items(), key=lambda item: item[1], reverse=True))
self.noun = dict(sorted(self.noun.items(), key=lambda item: item[1], reverse=True))
self.adjectives = dict(sorted(self.adjectives.items(), key=lambda item: item[1], reverse=True))
def getBlanks(self):
tempSentense = set()
tempBlanks = []
for i in list(self.properNoun.keys()) + list(self.noun.keys()):
for j in self.sentences:
if i in j and j not in tempSentense:
tempSentense.add(j)
r1 = {}
r1["blank"] = j.replace(i, "_____")
r1["answer"] = i
tempArr = list(self.properNoun.keys()) + list(self.noun.keys())
tempArr.remove(i)
r1["option1"] = random.choice(tempArr)
tempArr.remove(r1["option1"])
r1["option2"] = random.choice(list(self.noun.keys()))
r1["option3"] = "None of the above"
tempBlanks.append(r1)
self.blanks = tempBlanks[0]
return self.blanks
def getBool(self):
tempOppo = []
for i in self.adjectives.keys():
if len(tempOppo) == 2:
break
val = self.dictionary.antonym(i)
if val is not None:
tempOppo.append([i, val[0]])
self.bool = []
for i in tempOppo:
for j in self.sentences:
if i[0] in j:
ch = random.choice([0, 1])
if ch == 0:
self.bool.append({"bool": j, "answer": True})
else:
self.bool.append({"bool": j.replace(i[0], i[1]), "answer": False})
return random.choice(self.bool)
def getResponse(self):
resp = {"blank": self.getBlanks(), "bool": self.getBool()}
return resp