Embeding a ML model into a Web Application

import pickle
import re
import os
from movieclassifier.vectorizer import vect

clf = pickle.load(open(os.path.join('movieclassifier/pkl_objects', 'classifier.pkl'), 'rb'))

import numpy as np
label = {0:'negative', 1:'positive'}

example = ["I love this movie. It's amazing."]
X = vect.transform(example)
print('Prediction: %s\nProbability: %.2f%%' %\
      (label[clf.predict(X)[0]], 
       np.max(clf.predict_proba(X))*100))

X = vect.transform(["The work that they did with the move is really not up to the standards I expect"])
print('Prediction: %s\nProbability: %.2f%%' %\
      (label[clf.predict(X)[0]], 
       np.max(clf.predict_proba(X))*100))

X = vect.transform(["they called that a movie!"])
print('Prediction: %s\nProbability: %.2f%%' %\
      (label[clf.predict(X)[0]], 
       np.max(clf.predict_proba(X))*100))