Update app.py

app.py

@@ -1472,18 +1472,21 @@ KEY INSIGHTS:
         return f"Analysis error: {str(e)}", None
 
 def fake_detection_interface(reviews_text: str, file_upload):
-    """Fake detection interface"""
+    """Fixed fake detection interface"""
     try:
         analyzer = get_analyzer()
         reviews = []
         metadata = {}
         
+        # Process file upload first (priority over text input)
         if file_upload is not None:
             reviews, metadata = process_file_upload(file_upload)
             if 'error' in metadata:
                 return metadata['error'], None
         else:
-            reviews = [line.strip() for line in reviews_text.split('\n') if line.strip() and len(line.strip()) > 10]
+            # Only process text input if no file uploaded
+            reviews = [line.strip() for line in reviews_text.split('\n') 
+                      if line.strip() and len(line.strip()) > 10]
         
         if not reviews:
             return "Please enter review text or upload a file", None
@@ -1496,27 +1499,29 @@ def fake_detection_interface(reviews_text: str, file_upload):
         if 'error' in result:
             return result['error'], None
         
-        # Create risk distribution chart
-        lazy_import()
-        risk_scores = [item['risk_score'] for item in result['individual_analysis']]
-        
-        fig = plotly.go.Figure(data=[
-            plotly.go.Histogram(
-                x=risk_scores,
-                nbinsx=20,
-                marker_color='red',
-                opacity=0.7
+        # Create chart
+        try:
+            lazy_import()
+            risk_scores = [item['risk_score'] for item in result['individual_analysis']]
+            
+            fig = plotly.go.Figure(data=[
+                plotly.go.Histogram(
+                    x=risk_scores,
+                    nbinsx=20,
+                    marker_color='red',
+                    opacity=0.7
+                )
+            ])
+            fig.update_layout(
+                title="Fake Risk Distribution",
+                xaxis_title="Risk Score",
+                yaxis_title="Number of Reviews"
             )
-        ])
-        fig.update_layout(
-            title="Fake Risk Distribution",
-            xaxis_title="Risk Score",
-            yaxis_title="Number of Reviews"
-        )
+        except:
+            fig = None
         
-        # FORMATTED ENGLISH OUTPUT
-        formatted_result = f"""
-DETECTION SUMMARY:
+        # Format results
+        formatted_result = f"""DETECTION SUMMARY:
 Total Reviews: {result['summary']['total_reviews']}
 Suspicious Reviews: {result['summary']['suspicious_reviews']}
 Authenticity Rate: {result['summary']['authenticity_rate']:.1f}%
@@ -1530,13 +1535,13 @@ RECOMMENDATIONS:
 {chr(10).join(['• ' + rec for rec in result['recommendations']])}
 
 HIGH RISK SAMPLES:
-{chr(10).join([f'{i+1}. {item["text"][:50]}... | Risk: {item["risk_score"]:.2f} | Flags: {", ".join(item["flags"])}' for i, item in enumerate([r for r in result['individual_analysis'] if r['risk_score'] > 0.5][:3])])}
-"""
+{chr(10).join([f'{i+1}. {item["text"][:50]}... | Risk: {item["risk_score"]:.2f}' 
+               for i, item in enumerate([r for r in result['individual_analysis'] 
+               if r['risk_score'] > 0.5][:3]) if result['individual_analysis']])}"""
         
         return formatted_result, fig
         
     except Exception as e:
-        logger.error(f"Fake detection error: {str(e)}")
         return f"Analysis error: {str(e)}", None
 
 def quality_assessment_interface(reviews_text: str, file_upload, length_weight, detail_weight,