from flask import Flask,request,render_template
import numpy as np
import sys

from sklearn.preprocessing import StandardScaler
from src.exception import CustomException

from src.pipeline.predict_pipeline import CustomData,PredictPipeline

application = Flask(__name__)

app = application

## route for home page

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

@app.route('/predictdata',methods=['GET','POST'])
def predict_datapoint():
    try:
        if request.method == 'GET':
            return render_template('index.html')
        else:
            
            data=CustomData(
                gender=request.form.get('gender'),
                race_ethnicity=request.form.get('race_ethnicity'),
                parental_level_of_education=request.form.get('parental_level_of_education'),
                lunch=request.form.get('lunch'),
                test_preparation_course=request.form.get('test_preparation_course'),
                reading_score=request.form.get('reading_score'),
                writing_score=request.form.get('writing_Score')
                )
            pred_df = data.get_data_as_data_frame()

            predict_pipeline = PredictPipeline()

            results = predict_pipeline.predict(pred_df)
            return render_template('index.html',results=results[0])
    except Exception as e:
        raise CustomException(e,sys)
    
if __name__ == '__main__':
    app.run(host='0.0.0.0',port=7860)