from flask import Flask, request, render_template
from flask_cors import CORS
import numpy as np
import pandas as pd
import pickle

app = Flask(__name__)
CORS(app)



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


@app.route('/report')
def report():
    return render_template('report.html')
 
@app.route('/code')
def code():
    return render_template('code.html')

def analysis2(missedprior,totalmissed,reminded,age,hyper,diabetes):

    column = ['missed_appointment_before', 'sum_missed', 'Age', 'SMS_received',
       'Hypertension', 'Diabetes']
    
    serInput = [missedprior,totalmissed,age,reminded,hyper,diabetes]
    
    data = pd.DataFrame([serInput], columns=column)
    
    filename = './models/xgbnoshow.sav'
    model = pickle.load(open(filename, 'rb'))

    data = np.ascontiguousarray(data, dtype=np.float32)

    r =  model.predict(data)
    for i in r:
        if r == 0:
            result = str("Might Miss")
        else: 
            result = str("Might Show")
    proba = np.max(model.predict_proba(data)*100, axis=1)
    pred = str( (result) + ' With A Probability of: ' +'%.2f' % (proba) +'%')
     
    return pred

@app.route('/predictnoshow', methods=['GET', 'POST'])
def uploadsnoshow():
    if request.method == 'GET':
        # Get the file from post request

        missedprior = int(request.args['MissedPrior'])
        totalmissed = int(request.args['TotalMissed'])
        reminded = int(request.args['Reminded'])
        age = int(request.args['Age'])
        hyper = int(request.args['Hypertension'])
        diabetes = int(request.args['Diabetes'])

        serInput = [missedprior,totalmissed,reminded,age,hyper,diabetes]

        result =  analysis2(missedprior,totalmissed,reminded,age,hyper,diabetes)
           
        return render_template('index.html', predictions=result)
    return None

if __name__ == "__main__":
    print("🚀 Starting Flask app...")
    app.run(debug=True, host="0.0.0.0", port=7860)