app.py

from flask import Flask, request, jsonify, render_template
import pickle 
import numpy as np

#Load trained model
model_path = 'Air_Quality_checking_model.pkl'
with open(model_path, 'rb') as file:
    model = pickle.load(file)

app = Flask(__name__)

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

@app.route('/predict', methods=['POST'])
def predict():
    int_features = [int(x) for x in request.form.values()]
    final_features = [np.array(int_features)]
    
    prediction = model.predict(final_features)
    output = 'The Data for the quality of air can be trusted.' if prediction[0] ==1 else 'The Data for the quality of air cannot be trusted'
    
    return render_template('index.html', prediction_text='prediction: {}'.format(output))

if __name__ == "__main__":
    app.run(debug=True)