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Update app.py
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# Importing essential libraries
from flask import Flask, render_template, request
import pickle
# Load the Multinomial Naive Bayes model and CountVectorizer object from disk
filename = 'spam-sms-mnb-model.pkl'
classifier = pickle.load(open(filename, 'rb'))
cv = pickle.load(open('cv-transform.pkl','rb'))
app = Flask(__name__)
@app.route('/')
def home():
return render_template('home.html')
@app.route('/predict',methods=['POST'])
def predict():
if request.method == 'POST':
message = request.form['message']
data = [message]
vect = cv.transform(data).toarray()
my_prediction = classifier.predict(vect)
return render_template('result.html', prediction=my_prediction)
if __name__ == '__main__':
app.run(host="0.0.0.0", port=7860)