app.py

import streamlit as st
import numpy as np
import pickle
import streamlit.components.v1 as components

# Load the pickled model
def load_model():
    return pickle.load(open('china_gdp_estimate_rr.pkl', 'rb'))

# Function for model prediction
def model_prediction(model, features):
    predicted = str(model.predict(features))
    return predicted

def app_design():
    # Add input fields for High, Open, and Low values
    image = '8.png'
    st.image(image, use_column_width=True)
    
    st.subheader("Enter the following values:")
    
    Y_2000 = st.number_input("Year_2000",max_value=9999999999999999999.00)
    Y_2001 = st.number_input("Year_2001",max_value=9999999999999999999.00)
    Y_2002 = st.number_input("Year_2002",max_value=9999999999999999999.00)
    Y_2003 = st.number_input("Year_2003",max_value=9999999999999999999.00)
    Y_2004 = st.number_input("Year_2004",max_value=9999999999999999999.00)
    Y_2005 = st.number_input("Year_2005",max_value=9999999999999999999.00)
    Y_2006 = st.number_input("Year_2006",max_value=9999999999999999999.00)
    Y_2007 = st.number_input("Year_2007",max_value=9999999999999999999.00)
    Y_2008 = st.number_input("Year_2008",max_value=9999999999999999999.00)
    Y_2009 = st.number_input("Year_2009",max_value=9999999999999999999.00)
    Y_2010 = st.number_input("Year_2010",max_value=9999999999999999999.00)
    Y_2011 = st.number_input("Year_2011",max_value=9999999999999999999.00)
    Y_2012 = st.number_input("Year_2012",max_value=9999999999999999999.00)
    Y_2013 = st.number_input("Year_2013",max_value=9999999999999999999.00)
    Y_2014 = st.number_input("Year_2014",max_value=9999999999999999999.00)
    Y_2015 = st.number_input("Year_2015",max_value=9999999999999999999.00)
    Y_2016 = st.number_input("Year_2016",max_value=9999999999999999999.00)
    Y_2017 = st.number_input("Year_2017",max_value=9999999999999999999.00)
    Y_2018 = st.number_input("Year_2018",max_value=9999999999999999999.00)
    Y_2019 = st.number_input("Year_2019",max_value=9999999999999999999.00)
    Y_2020 = st.number_input("Year_2020",max_value=9999999999999999999.00)
    
    # Create a feature list from the user inputs
    features = [[Y_2000, Y_2001, Y_2002, Y_2003, Y_2004, Y_2005, Y_2006, Y_2007, Y_2008, Y_2009,Y_2010,Y_2011,Y_2012,Y_2013,Y_2014,Y_2015,Y_2016,Y_2017,Y_2018,Y_2019,Y_2020]]
    
    # Load the model
    model = load_model()
    
    # Make a prediction when the user clicks the "Predict" button
    if st.button('Predict GDP'):
        predicted_value = model_prediction(model, features)
        st.success(f"The calculated GDP is: {predicted_value}")  


def about_hidevs():

        components.html("""
        <div>
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      </div>
        """,
                    height=600)

def main():

        # Set the app title and add your website name and logo
        st.set_page_config(
        page_title="China GDP Estimation",
        page_icon=":chart_with_upwards_trend:",
        )
    
        st.title("Welcome to our China GDP Estimation App!")
    
        app_design()    
        st.header("About HiDevs Community")
        about_hidevs()

if __name__ == '__main__':
        main()