Update app.py

app.py

@@ -656,7 +656,7 @@ class AdvancedAnalysisEngine:
     
     @handle_errors(default_return=("Analysis failed", None, None))
     def analyze_with_lime(self, text: str, language: str = 'auto', num_samples: int = 100) -> Tuple[str, go.Figure, Dict]:
-        """FIXED LIME analysis implementation"""
+        """FIXED LIME analysis implementation - Bug Fix for mode parameter"""
         if not text.strip():
             return "Please enter text for analysis", None, {}
         
@@ -684,11 +684,8 @@ class AdvancedAnalysisEngine:
             else:
                 class_names = ['Negative', 'Positive']
             
-            # Initialize LIME explainer
-            explainer = LimeTextExplainer(
-                class_names=class_names,
-                mode='classification'
-            )
+            # Initialize LIME explainer - FIXED: Remove 'mode' parameter
+            explainer = LimeTextExplainer(class_names=class_names)
             
             # Get LIME explanation
             exp = explainer.explain_instance(
@@ -742,7 +739,7 @@ class AdvancedAnalysisEngine:
             }
             
             summary_text = f"""
-**LIME Analysis Results (FIXED):**
+**LIME Analysis Results (BUG FIXED):**
 - **Language:** {detected_lang.upper()}
 - **Features Analyzed:** {analysis_data['features_analyzed']}
 - **Classes:** {', '.join(class_names)}
@@ -750,7 +747,7 @@ class AdvancedAnalysisEngine:
 - **Positive Features:** {analysis_data['positive_features']}
 - **Negative Features:** {analysis_data['negative_features']}
 - **Top Features:** {', '.join([f"{word}({score:.3f})" for word, score in lime_data[:5]])}
-- **Status:** ✅ LIME analysis completed successfully
+- **Status:** ✅ LIME analysis completed successfully (mode parameter bug fixed)
             """
             
             return summary_text, fig, analysis_data
@@ -763,6 +760,10 @@ class AdvancedAnalysisEngine:
 - **Language:** {detected_lang.upper()}
 - **Suggestion:** Try with a shorter text or reduce number of samples
 
+**Bug Fix Applied:**
+- ✅ Removed 'mode' parameter from LimeTextExplainer initialization
+- ✅ This should resolve the "unexpected keyword argument 'mode'" error
+
 **Common fixes:**
 - Reduce sample size to 50-100
 - Use shorter input text (< 200 words)