app.py

import streamlit as st
import joblib
import pandas as pd

# Load the trained model
model = joblib.load('sugar_cane_model.joblib')

st.title('Sugar Cane Properties Prediction')

# Input fields
farm = st.text_input('Farm Name')
variety = st.text_input('Variety')
age = st.text_input('Age')

if st.button('Predict'):
    # Create a DataFrame with the input data
    input_data = pd.DataFrame({'Farm': [farm], 'Variety': [variety], 'Age': [age]})
    
    # Make prediction
    prediction = model.predict(input_data)
    
    # Display results
    st.write('Predicted Properties:')
    st.write(f'Brix: {prediction[0][0]:.2f}')
    st.write(f'Purity: {prediction[0][1]:.2f}')
    st.write(f'Pol: {prediction[0][2]:.2f}')
    st.write(f'RS: {prediction[0][3]:.2f}')