Update app.py

app.py

@@ -204,12 +204,15 @@ def analyze_file(file, label_col, n_clusters):
 
     try:
         f_scores, _ = f_classif(X_processed, clusters_kmeans)
+        # Handle potential division by zero or NaN values
+        f_scores = np.nan_to_num(f_scores, nan=0.0, posinf=0.0)
         f_series = pd.Series(f_scores, index=X_processed.columns).sort_values(ascending=False).head(MAX_FEATURES_TO_SHOW)
         plt.figure(figsize=(10, 6))
-        sns.barplot(x=f_series.values, y=f_series.index, palette="mako")
+        sns.barplot(data=f_series.reset_index(), x="index", y=0, hue="index", legend=False)  # Fix palette warning
         plt.title("Top 10 Differentiating Features (ANOVA F-scores)")
         plt.xlabel("F-score")
         plt.ylabel("Feature")
+        plt.xticks(rotation=45)
         buf = io.BytesIO()
         plt.savefig(buf, format="png", bbox_inches="tight")
         plt.close()
@@ -220,11 +223,18 @@ def analyze_file(file, label_col, n_clusters):
 
     return results_text, model_img, fi_img, kmeans_img, agg_img, diff_img
 
-def predict_interactive(**kwargs):
+def predict_interactive(*args):
     if global_data['model'] is None:
         return "Please analyze a file first to train the model."
     
     try:
+        # Convert args to kwargs based on column names
+        kwargs = {}
+        if len(args) > 0 and global_data['X_columns'] is not None:
+            for i, col in enumerate(global_data['X_columns']):
+                if i < len(args):
+                    kwargs[col] = args[i]
+        
         # Create DataFrame from user inputs
         input_data = pd.DataFrame([kwargs])
         
@@ -349,7 +359,7 @@ with gr.Blocks() as demo:
             def update_inputs(file, label_col):
                 print(f"Updating inputs with file: {file}, label_col: {label_col}")  # Debug logging
                 components = create_interactive_inputs(file, label_col)
-                return components, gr.Column.update(components=components, visible=True)
+                return components, gr.update(components=components, visible=True)  # Use gr.update() instead of gr.Column.update()
 
             file_input.change(
                 fn=update_inputs,