app.py

from flask import Flask,render_template,request
import joblib
from sklearn.linear_model import LogisticRegression
app=Flask(__name__)

#predicting using saved model
model=joblib.load('iris_model.pkl')

@app.route('/')
def home():
    return render_template('index.html')

@app.route('/predict', methods=['POST'])
def predict():

        # Get form values and convert them to float
        sepal_length = float(request.form['sl'])
        sepal_width = float(request.form['sw'])
        petal_length = float(request.form['pl'])
        petal_width = float(request.form['pw'])

        # Make prediction
        prediction = model.predict([[sepal_length, sepal_width, petal_length, petal_width]])
        result = prediction[0]

        return render_template('index.html', result=result)

if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0')