Update app.py

app.py

@@ -477,22 +477,13 @@ class TranslationApp:
         correct_translation: Optional[str] = None
     ):
         """
-        Log user feedback to a CSV file named '{source}_{target}.csv'.
-        
-        Args:
-            source_lang: Source language enum
-            target_lang: Target language enum
-            user_input: Original input text
-            model_output: Model-generated translation
-            notation: User rating (optional)
-            correct_translation: Corrected version (optional)
+        Log user feedback to a CSV file and push to Hugging Face repo if running in Space.
         """
         # Define filename
         src = source_lang.value.lower()
         tgt = target_lang.value.lower()
         filename = f"{src}_{tgt}.csv"
-        
-        # Define headers and row
+    
         headers = [
             "timestamp",
             "source_language",
@@ -511,17 +502,35 @@ class TranslationApp:
             "notation": notation,
             "correct_translation": correct_translation.strip() if correct_translation else ""
         }
-        
-        # Check if file exists to determine whether to write headers
+    
         file_exists = Path(filename).exists()
-
+    
         try:
+            # Write to local CSV
             with open(filename, mode="a", encoding="utf-8", newline="") as f:
                 writer = csv.DictWriter(f, fieldnames=headers)
                 if not file_exists:
-                    writer.writeheader()  # Write header only once
+                    writer.writeheader()
                 writer.writerow(row)
-            logger.info(f"Feedback saved to {filename}")
+            logger.info(f"Feedback saved locally to {filename}")
+    
+            # Try to push to HF repo if HF_TOKEN exists
+            if hf_token := os.getenv("hffff"):
+                from huggingface_hub import Repository, upload_file, get_repo_info
+    
+                try:
+                    # Upload directly using upload_file (recommended for single files)
+                    upload_file(
+                        path_or_fileobj=filename,
+                        path_in_repo=filename,
+                        repo_id=os.getenv("LocaleNLP/LocaleNLP_Translator"),  # e.g., "yourusername/your-space-name"
+                        token=hf_token,
+                        repo_type="space",
+                        commit_message=f"Add/update feedback: {filename}"
+                    )
+                    logger.info(f"Successfully pushed {filename} to Hugging Face Space repo.")
+                except Exception as e:
+                    logger.warning(f"Failed to push feedback to HF Hub: {e}")
         except Exception as e:
             logger.error(f"Failed to save feedback to {filename}: {e}")
 
@@ -694,7 +703,7 @@ class TranslationApp:
                 notation_val: float,
                 correct_trans: str
             ):
-                """Save feedback to CSV."""
+                """Save feedback to CSV and clear form."""
                 try:
                     source_lang = Language(source_lang_str)
                     target_lang = Language(target_lang_str)
@@ -707,50 +716,59 @@ class TranslationApp:
                         notation=notation_val,
                         correct_translation=correct_trans or None
                     )
-                    return "✅ Thank you for your feedback!"
+                    # Return values to reset UI components
+                    return (
+                        "✅ Thank you for your feedback!",  # feedback_status
+                        None,                               # notation (reset slider)
+                        ""                                  # correct_translation (clear textbox)
+                    )
                 except Exception as e:
                     logger.error(f"Feedback submission failed: {e}")
-                    return f"❌ Failed to save feedback: {str(e)}"
-
-            # Connect events
-            input_mode.change(
-                fn=update_visibility,
-                inputs=input_mode,
-                outputs=[input_text, audio_input, file_input, extracted_text, output_text]
-            )
+                    return (
+                        f"❌ Failed to save feedback: {str(e)}",
+                        gr保留(notation_val),               # keep value on error
+                        correct_trans                      # keep text on error
+                    )
             
-            # Chain: Process → Translate → Store context → Wait for feedback
-            process_event = translate_btn.click(
-                fn=handle_process,
-                inputs=[input_mode, input_lang, input_text, audio_input, file_input],
-                outputs=[extracted_text, output_text]
-            )
-
-            process_event.success(
-                fn=handle_translate_with_input,
-                inputs=[extracted_text, input_lang, output_lang],
-                outputs=[output_text, gr.State(), gr.State()]
-            ).success(
-                fn=set_states_for_feedback,
-                inputs=[output_text, extracted_text, input_lang, output_lang],
-                outputs=[user_input_state, model_output_state, source_lang_state, target_lang_state]
-            )
-
-            # Feedback submission
-            submit_feedback.click(
-                fn=save_feedback,
-                inputs=[
-                    user_input_state,
-                    model_output_state,
-                    source_lang_state,
-                    target_lang_state,
-                    notation,
-                    correct_translation
-                ],
-                outputs=feedback_status
-            )
-        
-        return interface
+                        # Connect events
+                        input_mode.change(
+                            fn=update_visibility,
+                            inputs=input_mode,
+                            outputs=[input_text, audio_input, file_input, extracted_text, output_text]
+                        )
+                        
+                        # Chain: Process → Translate → Store context → Wait for feedback
+                        process_event = translate_btn.click(
+                            fn=handle_process,
+                            inputs=[input_mode, input_lang, input_text, audio_input, file_input],
+                            outputs=[extracted_text, output_text]
+                        )
+            
+                        process_event.success(
+                            fn=handle_translate_with_input,
+                            inputs=[extracted_text, input_lang, output_lang],
+                            outputs=[output_text, gr.State(), gr.State()]
+                        ).success(
+                            fn=set_states_for_feedback,
+                            inputs=[output_text, extracted_text, input_lang, output_lang],
+                            outputs=[user_input_state, model_output_state, source_lang_state, target_lang_state]
+                        )
+            
+                        # Feedback submission
+                        submit_feedback.click(
+                            fn=save_feedback,
+                            inputs=[
+                                user_input_state,
+                                model_output_state,
+                                source_lang_state,
+                                target_lang_state,
+                                notation,
+                                correct_translation
+                            ],
+                            outputs=feedback_status
+                        )
+                    
+                    return interface
 
 # ================================
 # Application Entry Point