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bot.py
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import pandas as pd
import numpy as np
import random
from matplotlib import pyplot as plt
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.metrics.pairwise import cosine_similarity
dataset = "./data/covid_qA.csv"
data = pd.read_csv(dataset)
vectorizer = TfidfVectorizer()
count_vec = vectorizer.fit_transform(data['Question']).toarray()
def COVIDbot(user_response):
text = vectorizer.transform([user_response]).toarray()
data['similarity'] = cosine_similarity(count_vec, text)
return data.sort_values(['similarity'], ascending=False).iloc[0]['Answer']
welcome_input = ("hello", "hi", "greetings", "sup", "what's up","hey",)
welcome_response = ["hi", "hey", "*nods*", "hi there", "hello", "I am glad! You are talking to me"]
def welcome(user_response):
for word in user_response.split():
if word.lower() in welcome_input:
return random.choice(welcome_response)
def generate_response(user_response):
user_response = user_response.lower()
if(user_response not in ['bye','shutdown','exit', 'quit']):
if(user_response=='thanks' or user_response=='thank you'):
flag=False
return "You are welcome.."
else:
if(welcome(user_response)!=None):
response = welcome(user_response)
return response
else:
return COVIDbot(user_response)
def main():
flag=True
print("Greetings! I am a chatbot and I will try to answer your questions about COVID-19. If you want to exit, type Bye!")
while(flag==True):
user_response = input()
user_response = user_response.lower()
if(user_response not in ['bye','shutdown','exit', 'quit']):
if(user_response=='thanks' or user_response=='thank you'):
flag=False
print("Chatbot : You are welcome..")
else:
if(welcome(user_response)!=None):
print("Chatbot : "+welcome(user_response))
else:
print("Chatbot : ",end="")
print(COVIDbot(user_response))
else:
flag=False
print("Chatbot : Bye!!! ")
main()