minor change

app.py

@@ -86,28 +86,45 @@ def process_file(file):
         processed_rows = []
         
         for _, row in df.iterrows():
-            text = row['Выдержки из текста']
-            entity = row['Объект']
+            text = str(row.get('Выдержки из текста', ''))
+            entity = str(row.get('Объект', ''))
             
             event_type, event_summary = detector.detect_events(text, entity)
             sentiment = detector.analyze_sentiment(text)
             
-            processed_row = {
+            processed_rows.append({
                 'Объект': entity,
-                'Заголовок': row['Заголовок'],
+                'Заголовок': str(row.get('Заголовок', '')),
                 'Sentiment': sentiment,
                 'Event_Type': event_type,
                 'Event_Summary': event_summary,
                 'Текст': text
-            }
-            processed_rows.append(processed_row)
+            })
             
         return pd.DataFrame(processed_rows)
         
     except Exception as e:
-        return f"Error processing file: {str(e)}"
+        # Return empty DataFrame instead of string
+        return pd.DataFrame(columns=['Объект', 'Заголовок', 'Sentiment', 'Event_Type', 'Event_Summary', 'Текст'])
+
+def analyze(file):
+    if file is None:
+        return None, None, None
+        
+    df = process_file(file)
+    if df.empty:
+        return df, None, None
+        
+    try:
+        fig_sentiment, fig_events = create_visualizations(df)
+        return df, fig_sentiment, fig_events
+    except Exception as e:
+        return df, None, None
 
 def create_visualizations(df):
+    if df is None or df.empty:
+        return None, None
+        
     # Create sentiment distribution plot
     sentiments = df['Sentiment'].value_counts()
     fig_sentiment = go.Figure(data=[go.Pie(
@@ -116,7 +133,7 @@ def create_visualizations(df):
         marker_colors=['#FF6B6B', '#4ECDC4', '#95A5A6']
     )])
     
-    # Create events distribution plot
+    # Create events distribution plot  
     events = df['Event_Type'].value_counts()
     fig_events = go.Figure(data=[go.Bar(
         x=events.index,