app.py

from flask import Flask, request, render_template
from src.pipelines.Prediction_Pipeline import CustomData, PredictPipeline
 
app=Flask(__name__)

# app=application

@app.route('/',methods=['GET','POST'])
def predict_datapoint():
    if request.method=='GET':
        return render_template('index.html')
    else:
        data=CustomData(
            gender=request.form.get('gender'),
            race_ethnicity=request.form.get('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=float(request.form.get('writing_score')),
            writing_score=float(request.form.get('reading_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])
    

if __name__=="__main__":
    app.run(host="0.0.0.0",port=8080, debug=True)