Update app.py

app.py

@@ -1,21 +1,24 @@
 import streamlit as st
 import joblib
 import numpy as np
+import pickle
 
 # --- 1. Load Model and Define Feature Information ---
 
 @st.cache_resource
 def load_model():
     """
-    Loads the saved model. Using st.cache_resource to load the model only once.
+    Loads the saved model using pickle.
+    Using st.cache_resource to load the model only once.
     """
     try:
-        # Load the pre-trained Voting Classifier model
-        model = joblib.load('voting_classifier_model.joblib')
+        # Load the pre-trained model from a pickle file
+        with open('voting_classifier_model.pkl', 'rb') as f:
+            model = pickle.load(f)
         return model
     except FileNotFoundError:
-        st.error("The model file 'voting_classifier_model.joblib' was not found.")
-        st.info("Please ensure the model file is in the same directory as this script.")
+        st.error("The model file 'voting_classifier_model.pkl' was not found.")
+        st.info("Please ensure you have saved your model using pickle and the file is in the same directory.")
         st.stop()
     except Exception as e:
         st.error(f"An error occurred while loading the model: {e}")
@@ -23,6 +26,7 @@ def load_model():
 
 model = load_model()
 
+
 # --- Hardcoded Feature Information ---
 # We define the feature names and their typical ranges (min, mean, max)
 # This removes the need to load the original dataset file.