Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import pandas as pd
 from pycaret.classification import setup as classification_setup, compare_models as compare_classification_models, evaluate_model as evaluate_classification_model, save_model as save_classification_model, plot_model as plot_classification_model
 from pycaret.regression import setup as regression_setup, compare_models as compare_regression_models, evaluate_model as evaluate_regression_model, save_model as save_regression_model, plot_model as plot_regression_model
-from pycaret.clustering import setup as clustering_setup, compare_models as compare_clustering_models, evaluate_model as evaluate_clustering_model, save_model as save_clustering_model, plot_model as plot_clustering_model
+from pycaret.clustering import setup as clustering_setup, evaluate_model as evaluate_clustering_model, save_model as save_clustering_model, plot_model as plot_clustering_model
 from ydata_profiling import ProfileReport
 from streamlit_pandas_profiling import st_profile_report
 import os
@@ -81,11 +81,15 @@ elif app_mode == "Model Training":
                 elif st.session_state['problem_type'] == "Regression":
                     best_model = compare_regression_models()
                 elif st.session_state['problem_type'] == "Clustering":
-                    best_model = compare_clustering_models()
-                st.session_state['best_model'] = best_model
-                st.success(f"Best Model: {best_model}")
+                    st.info("Model comparison is not available for clustering. Please proceed with evaluation or create a model manually.")
+                    best_model = None
+                else:
+                    best_model = None
+                if best_model is not None:
+                    st.session_state['best_model'] = best_model
+                    st.success(f"Best Model: {best_model}")
 
-        if 'best_model' in st.session_state:
+        if 'best_model' in st.session_state and st.session_state['best_model'] is not None:
             st.subheader("Model Evaluation")
             if st.button("Evaluate Model"):
                 with st.spinner("Evaluating model..."):
@@ -110,8 +114,8 @@ elif app_mode == "Model Training":
 
 elif app_mode == "Validation & Exploration":
     st.title("🔍 Validation & Exploration")
-    if 'best_model' not in st.session_state:
-        st.warning("Please train a model first.")
+    if 'best_model' not in st.session_state or st.session_state['best_model'] is None:
+        st.warning("Please train a model first. Note: Clustering does not support automatic model comparison.")
         st.stop()
 
     st.subheader("Model Performance")