incorrect_answer_generation.py

''' This module contains the class
for generating incorrect alternative
answers for a given answer
'''
import gensim
import gensim.downloader as api
from gensim.models import Word2Vec
from nltk.tokenize import sent_tokenize, word_tokenize
import random
import numpy as np


class IncorrectAnswerGenerator:
    ''' This class contains the methods
    for generating the incorrect answers
    given an answer
    '''

    def __init__(self, document):
        # model required to fetch similar words
        self.model = api.load("glove-wiki-gigaword-100")
        self.all_words = []
        for sent in sent_tokenize(document):
            self.all_words.extend(word_tokenize(sent))
        self.all_words = list(set(self.all_words))

    def get_all_options_dict(self, answer, num_options):
        ''' This method returns a dict
        of 'num_options' options out of
        which one is correct and is the answer
        '''
        options_dict = dict()
        try:
            similar_words = self.model.similar_by_word(answer, topn=15)[::-1]

            for i in range(1, num_options + 1):
                options_dict[i] = similar_words[i - 1][0]

        except BaseException:
            self.all_sim = []
            for word in self.all_words:
                if word not in answer:
                    try:
                        self.all_sim.append(
                            (self.model.similarity(answer, word), word))
                    except BaseException:
                        self.all_sim.append(
                            (0.0, word))
                else:
                    self.all_sim.append((-1.0, word))

            self.all_sim.sort(reverse=True)

            for i in range(1, num_options + 1):
                options_dict[i] = self.all_sim[i - 1][1]

        replacement_idx = random.randint(1, num_options)

        options_dict[replacement_idx] = answer

        return options_dict