Update app.py

app.py

@@ -101,10 +101,18 @@ def calculate_linguistic_metrics(text):
         'unique_words': len(unique_words)
     }
 
+def create_empty_metrics_table():
+    """Create an empty metrics table for error cases"""
+    return pd.DataFrame({
+        'Metric': ['Words', 'Characters', 'Sentences', 'Unique Words', 'Avg Word Length', 'Lexical Diversity'],
+        'Source Text': [0, 0, 0, 0, '0.0', '0.000'],
+        'Target Text': [0, 0, 0, 0, '0.0', '0.000']
+    })
+
 def translate_text(text, direction):
     """Main translation function with linguistic analysis"""
     if not text.strip():
-        return "Please enter text to translate.", "", ""
+        return "Please enter text to translate.", "No analysis available.", create_empty_metrics_table()
     
     start_time = time.time()
     
@@ -115,7 +123,7 @@ def translate_text(text, direction):
         # Perform translation
         if direction == "English → Siswati":
             if en_ss_translator is None:
-                return "Translation model not loaded. Please try again.", "", ""
+                return "Translation model not loaded. Please try again.", "Model loading failed.", create_empty_metrics_table()
             
             result = en_ss_translator(text, max_length=512)
             translated_text = result[0]['translation_text']
@@ -127,7 +135,7 @@ def translate_text(text, direction):
             
         else:  # Siswati → English
             if ss_en_translator is None:
-                return "Translation model not loaded. Please try again.", "", ""
+                return "Translation model not loaded. Please try again.", "Model loading failed.", create_empty_metrics_table()
             
             result = ss_en_translator(text, max_length=512)
             translated_text = result[0]['translation_text']
@@ -151,7 +159,7 @@ def translate_text(text, direction):
         return translated_text, analysis_report, metrics_table
         
     except Exception as e:
-        return f"Translation error: {str(e)}", "", ""
+        return f"Translation error: {str(e)}", f"Analysis failed: {str(e)}", create_empty_metrics_table()
 
 def create_analysis_report(source_metrics, target_metrics, siswati_features, processing_time, direction):
     """Create a comprehensive linguistic analysis report"""
@@ -209,7 +217,7 @@ def create_metrics_table(source_metrics, target_metrics, processing_time):
 def secure_file_processing(file_obj, direction):
     """Securely process uploaded files with proper cleanup"""
     if file_obj is None:
-        return "Please upload a file.", ""
+        return "Please upload a file.", pd.DataFrame()
     
     # Create a unique temporary directory for this processing session
     session_id = str(uuid.uuid4())
@@ -222,7 +230,7 @@ def secure_file_processing(file_obj, direction):
         # Get file extension and validate
         file_ext = os.path.splitext(file_obj.name)[1].lower()
         if file_ext not in ['.txt', '.csv']:
-            return "Only .txt and .csv files are supported.", ""
+            return "Only .txt and .csv files are supported.", pd.DataFrame()
         
         # Create secure temporary file path
         temp_file_path = os.path.join(temp_dir, f"upload_{session_id}{file_ext}")
@@ -237,21 +245,21 @@ def secure_file_processing(file_obj, direction):
             try:
                 df = pd.read_csv(temp_file_path)
                 if df.empty:
-                    return "The uploaded CSV file is empty.", ""
+                    return "The uploaded CSV file is empty.", pd.DataFrame()
                 # Assume first column contains text to translate
                 texts = df.iloc[:, 0].dropna().astype(str).tolist()
             except Exception as e:
-                return f"Error reading CSV file: {str(e)}", ""
+                return f"Error reading CSV file: {str(e)}", pd.DataFrame()
         else:  # .txt file
             try:
                 with open(temp_file_path, 'r', encoding='utf-8') as f:
                     content = f.read()
                 texts = [line.strip() for line in content.split('\n') if line.strip()]
             except Exception as e:
-                return f"Error reading text file: {str(e)}", ""
+                return f"Error reading text file: {str(e)}", pd.DataFrame()
         
         if not texts:
-            return "No text found in the uploaded file.", ""
+            return "No text found in the uploaded file.", pd.DataFrame()
         
         # Limit batch size for performance and security
         max_batch_size = 10
@@ -298,7 +306,7 @@ def secure_file_processing(file_obj, direction):
             })
         
         if not results:
-            return "No valid text entries found to translate.", ""
+            return "No valid text entries found to translate.", pd.DataFrame()
         
         results_df = pd.DataFrame(results)
         summary = f"Successfully processed {len(results)} text entries."
@@ -308,12 +316,13 @@ def secure_file_processing(file_obj, direction):
         return summary, results_df
         
     except Exception as e:
-        return f"Error processing file: {str(e)}", ""
+        return f"Error processing file: {str(e)}", pd.DataFrame()
     
     finally:
         # Clean up temporary files and directory
         if temp_dir and os.path.exists(temp_dir):
             try:
+                import shutil
                 shutil.rmtree(temp_dir)
             except Exception as e:
                 print(f"Warning: Could not clean up temporary directory: {e}")
@@ -389,14 +398,6 @@ def create_gradio_interface():
                             lines=4,
                             interactive=False
                         )
-                        
-                        # Quick metrics display
-                        with gr.Row():
-                            processing_info = gr.Textbox(
-                                label="Processing Info",
-                                lines=1,
-                                interactive=False
-                            )
                 
                 # Examples Section
                 gr.Markdown("### 📚 Example Translations")