Update app.py

app.py

@@ -605,8 +605,15 @@ def analyze_results(stats_df):
         'silhouette_score': 0.2
     }
     
+    # Convert relevant columns to numeric type
+    for metric in metric_weights.keys():
+        stats_df[metric] = pd.to_numeric(stats_df[metric], errors='coerce')
+    
     # Calculate weighted score for each configuration
-    stats_df['weighted_score'] = sum(stats_df[metric] * weight for metric, weight in metric_weights.items())
+    stats_df['weighted_score'] = sum(
+        stats_df[metric].fillna(0) * weight 
+        for metric, weight in metric_weights.items()
+    )
     
     # Get the best configuration
     best_config = stats_df.loc[stats_df['weighted_score'].idxmax()]
@@ -616,25 +623,25 @@ def analyze_results(stats_df):
         'best_model': f"{best_config['model_type']} - {best_config['model_name']}",
         'best_settings': {
             'split_strategy': best_config['split_strategy'],
-            'chunk_size': best_config['chunk_size'],
-            'overlap_size': best_config['overlap_size'],
+            'chunk_size': int(best_config['chunk_size']),
+            'overlap_size': int(best_config['overlap_size']),
             'vector_store_type': best_config['vector_store_type'],
             'search_type': best_config['search_type'],
-            'top_k': best_config['top_k'],
-            'optimize_vocab': best_config['optimize_vocab'],
-            'use_query_optimization': best_config['use_query_optimization'],
-            'use_reranking': best_config['use_reranking']
+            'top_k': int(best_config['top_k']),
+            'optimize_vocab': bool(best_config['optimize_vocab']),
+            'use_query_optimization': bool(best_config['use_query_optimization']),
+            'use_reranking': bool(best_config['use_reranking'])
         },
         'performance_summary': {
-            'search_time': best_config['search_time'],
-            'result_diversity': best_config['result_diversity'],
-            'rank_correlation': best_config['rank_correlation'],
-            'silhouette_score': best_config['silhouette_score']
+            'search_time': float(best_config['search_time']),
+            'result_diversity': float(best_config['result_diversity']),
+            'rank_correlation': float(best_config['rank_correlation']),
+            'silhouette_score': float(best_config['silhouette_score'])
         }
     }
     
     return recommendations
-####
+    ####
 
 # Gradio Interface
 def launch_interface(share=True):
@@ -696,7 +703,6 @@ def launch_interface(share=True):
             ],
             outputs=[results_output, stats_output, plot_output]
         )
-
         ####
         with gr.Tab("Automated"):
             auto_file_input = gr.File(label="Upload File (Optional)")