#!pip install --quiet gradio

import gradio as gr
input_long=gr.inputs.Slider(-124.35, -114.34, step=0.1,label="longitude")
input_lati=gr.inputs.Slider(32, 41, step=0.5,label="latitude")
input_hmg=gr.inputs.Slider(1, 55, step=1,label="Housing_median_age (Year)")
input_tr=gr.inputs.Slider(1, 40000, step=12,label="Total_rooms")
input_tb=gr.inputs.Slider(1, 6500, step=5,label="Total_Bedrooms")
input_p=gr.inputs.Slider(3, 35678, step=5,label="Population")
input_hh=gr.inputs.Slider(1, 6081, step=5,label="Households")
input_mi=gr.inputs.Slider(0, 15, step=1,label="Median_income")
output_mhv = gr.outputs.Textbox(label = "Predicted housing price")  
output_mhv1 = gr.outputs.Image(label = "Median house value")





def house_price(input_long, input_lati, input_hmg, input_tr, input_tb, input_p, input_hh, input_mi ):
    import numpy as np
    import pandas as pd
    ## processing inputs

    ## return outputs
    output1 = 111253
    output2 = np.random.rand(5,5)
    return output1,output2

gr.Interface( title="house Prediction",description="This model gives the estimated price of a house." ,fn=house_price,inputs=[input_long, input_lati, input_hmg, input_tr, input_tb, input_p, input_hh, input_mi], outputs=[output_mhv, output_mhv1] ).launch()