Create app.py

app.py

@@ -0,0 +1,27 @@
+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}')