app.py

from flask import flask,render,template, request
import joblib
sklearn.linear_model import LogisticRegression
app=flask(__name__)
model.joblib.load('iris_model.pkl')
pred=model.predict([[5,5,0,4.1,3]])
result=pred[0]

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

@app.route('/predict', methods=['POST'])
def predict():
    if request.method == 'POST':
        # Example: expecting 4 inputs from form (Sepal length, Sepal width, Petal length, Petal width)
        sl = float(request.form['sepal_length'])
        sw = float(request.form['sepal_width'])
        pl = float(request.form['petal_length'])
        pw = float(request.form['petal_width'])

        # Make prediction
        pred = model.predict([[sl, sw, pl, pw]])
        result = pred[0]  # Predicted class (0,1,2)

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

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