import numpy as np
import joblib
import gradio as gr
import pandas as pd


loaded_model = joblib.load('./saved_model(2).joblib')

def predict_rank(NATIONAL,Institution_name, Academic_Reputation_score, Academic_Reputation_rank, Employer_Reputation_score, Employer_Reputation_rank, Faculty_Student_score, Faculty_Student_rank, Citations_per_Faculty_score, Citations_per_Faculty_rank, International_Faculty_score, International_Students_score, International_Students_rank):
    input_data = np.array([NATIONAL, Institute_name, Academic_Reputation_score, Academic_Reputation_rank, Employer_Reputation_score, Employer_Reputation_rank, Faculty_Student_score, Faculty_Student_rank, Citations_per_Faculty_score, Citations_per_Faculty_rank, International_Faculty_score, International_Students_score,International_Students_rank]).reshape(1, -1)
    predict_score = loaded_model.predict(input_data)
    return f"Predicted Rank: {np.round(predict_score[0], 2)}"

C11 = gr.components.Slider(minimum=1, maximum=1401, label='NATIONAL')
C22 = gr.components.Slider(minimum=0, maximum=1700, label='Institution name')
C23 = gr.components.Slider(minimum=1, maximum=100, label='Academic Reputation Score')
C33 = gr.components.Slider(minimum=1, maximum=601, label='Academic Reputation Rank')
C44 = gr.components.Slider(minimum=1, maximum=100, label='Employer Reputation score')
C55 = gr.components.Slider(minimum=1, maximum=601, label='Employer Reputation rank')
C66 = gr.components.Slider(minimum=1, maximum=100, label='Faculty Student score')
C77 = gr.components.Slider(minimum=1, maximum=701, label='Faculty Student rank')
C88 = gr.components.Slider(minimum=1, maximum=100, label='Citations per Faculty score')
C99 = gr.components.Slider(minimum=1, maximum=701, label='Citations per Faculty rank')
C100 = gr.components.Slider(minimum=1, maximum=100, label='International Faculty score')
C101 = gr.components.Slider(minimum=1, maximum=100, label='International Students score')
C102 = gr.components.Slider(minimum=1, maximum=701,label='International Students rank')





op = gr.components.Textbox(label="Overall_score")
iface = gr.Interface(fn=predict_rank, inputs=[C11, C22,C23, C33, C44, C55, C66, C77, C88, C99, C100, C101, C102], theme='HaleyCH/HaleyCH_Theme', outputs=op)
iface.launch()