import gradio as gr
import pandas as pd
import numpy as np
from sklearn.linear_model import LinearRegression
import pickle
filename = 'finalized_model.sav'


# load the model from disk
lineareg = pickle.load(open(filename, 'rb'))


#function to predict the input hours
def predict_score(hours):
    hours = np.array(hours)
    pred_score = lineareg.predict(hours.reshape(-1,1))
    return np.round(pred_score[0], 2)

input = gr.inputs.Number(label='Number of Hours studied')
output = gr.outputs.Textbox(label='Predicted Score')
gr.Interface( fn=predict_score,
              inputs=input,
              outputs=output).launch();