import pandas as pd
import gradio as gr
import joblib





le=joblib.load('le_col.pkl')
std=joblib.load('std_col.pkl')
lr=joblib.load('model.pkl')



le_col=['Gender', 'Parental Education Level', 'Lunch Type','Test Preparation Course']
std_col=['Study Time','Absences', 'Math Score','Reading Score', 'Writing Score']









def Prediction_model_C(G,PL,LT,TPC,ST,A,MS,RS,WC):
    try:
        input_data=pd.DataFrame({
            'Gender':[G],
            'Parental Education Level':[PL],
            'Lunch Type':[LT],
            'Test Preparation Course':[TPC],
            'Study Time':[ST],
            'Absences':[A],
            'Math Score':[MS],
            'Reading Score':[RS],
            'Writing Score':[WC],
            
        })
        for col in le_col:
            input_data[col]=le[col].transform(input_data[col])
        input_data[std_col]=std.transform(input_data[std_col])
        prediction=lr.predict(input_data)
        return prediction[0]
    except Exception as e:
        return str(e)
gr.Interface(
    inputs=[
        gr.Dropdown(['Male','Female'],label='Gender'),
        gr.Dropdown(['High School','Bachelor','Associate','Master','Some College'],label='Parental Education Level'),
        gr.Dropdown(['Free/Reduced','Standard'],label='Lunch Type'),
        gr.Dropdown(['Completed','NO_Completed'],label='Test Preparation Course'),
        gr.Number(label='Study Time'),
        gr.Number(label='Absences'),
        gr.Number(label='Math Score'),
        gr.Number(label='Reading Score'),
        gr.Number(label='Writing Score'),
        
    ],
    fn=Prediction_model_C,
    outputs=gr.Textbox(label='Prediction')
).launch()