cbot.py

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
import warnings
import string
import random
import nltk
nltk.download('punkt')
warnings.filterwarnings('ignore')

f = open('./data.txt', 'r', errors='ignore')

raw = f.read()
raw = raw.lower()

sent_tokens = nltk.sent_tokenize(raw)  # converts to list of sentences
word_tokens = nltk.word_tokenize(raw)
# preprocessing
lemmer = nltk.stem.WordNetLemmatizer()


def LemTokens(tokens):
    return [lemmer.lemmatize(token) for token in tokens]


remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation)


def LemNormalize(text):
    return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))


# Greetings
GREETING_INPUTS = ("hello", "hi", "greetings", "sup", "what's up", "hey")
GREETING_RESPONSES = ["hi", "hey", "nods", "hi there",
                      "hello", "I am glad! you are talking to me"]

# =============== GREETING ===============


def greeting(scentence):

    for word in scentence.split():
        if word.lower() in GREETING_INPUTS:
            return random.choice(GREETING_RESPONSES)

# Vectorizer


# =============== RESPONSE ===============


def response(user_response):
    chatbot_response = ''
    sent_tokens.append(user_response)
    TfidfVec = TfidfVectorizer(tokenizer=LemNormalize, stop_words="english")
    tfidf = TfidfVec.fit_transform(sent_tokens)
    vals = cosine_similarity(tfidf[-1], tfidf)
    idx = vals.argsort()[0][-2]
    flat = vals.flatten()
    flat.sort()
    req_tfidf = flat[-2]
    if(req_tfidf == 0):
        chatbot_response = chatbot_response + "I am sorry! I don't understand you"
        return chatbot_response

    else:
        chatbot_response = chatbot_response+sent_tokens[idx]
        return chatbot_response


if __name__ == "__main__":
    flag = True
    print("Hey there! I'm Perry. I'm here to answer your queries regarding COVID 19. If you want to exit, type Bye! :)")
    while(flag == True):
        user_response = input()
        user_response = user_response.lower()
        if(user_response != 'bye'):
            if user_response == 'thanks' or user_response == 'thank you':
                flag = False
                print("Perry: You're welcome!")
            else:
                if(greeting(user_response) != None):
                    print("Perry:" + greeting(user_response))
                else:
                    print("Perry:", end='')
                    print(response(user_response))
                    sent_tokens.remove(user_response)
        else:
            flag = False
            print("Perry: Bye! Have a great time!")