Update app.py

app.py

@@ -27,7 +27,7 @@ from bs4 import BeautifulSoup
 from markdown import markdown
 import chardet
 from transformers import pipeline, MarianTokenizer, AutoModelForSeq2SeqLM
-from huggingface_hub import login
+from huggingface_hub import login, upload_file
 
 # ================================
 # Configuration & Constants
@@ -133,7 +133,8 @@ class ModelManager:
             logger.info(f"Loading translation model: {config.model_name}")
             
             # Authenticate with Hugging Face if token provided
-            if hf_token := os.getenv("hffff"):
+            hf_token = os.getenv("hffff")
+            if hf_token:
                 login(token=hf_token)
             
             model = AutoModelForSeq2SeqLM.from_pretrained(
@@ -513,17 +514,16 @@ class TranslationApp:
                     writer.writeheader()
                 writer.writerow(row)
             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
-    
+            hf_token = os.getenv("hffff")
+            space_id = os.getenv("SPACE_ID")  # e.g., "yourusername/your-space-name"
+            if hf_token and space_id:
                 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"
+                        repo_id=space_id,
                         token=hf_token,
                         repo_type="space",
                         commit_message=f"Add/update feedback: {filename}"
@@ -608,15 +608,14 @@ class TranslationApp:
             # --- FEEDBACK SECTION ---
             gr.Markdown("### 📝 Provide Feedback on Translation")
 
-            with gr.Row():
-                notation = gr.Slider(
-                    minimum=1,
-                    maximum=5,
-                    step=1,
-                    label="Rate translation quality (1-5 stars)",
-                    value=None,
-                    interactive=True
-                )
+            notation = gr.Slider(
+                minimum=1,
+                maximum=5,
+                step=1,
+                label="Rate translation quality (1-5 stars)",
+                value=None,
+                interactive=True
+            )
 
             correct_translation = gr.Textbox(
                 label="Correct Translation (if incorrect)",
@@ -718,57 +717,57 @@ class TranslationApp:
                     )
                     # Return values to reset UI components
                     return (
-                        "✅ Thank you for your feedback!",  # feedback_status
-                        None,                               # notation (reset slider)
-                        ""                                  # correct_translation (clear textbox)
+                        "✅ Thank you for your feedback!",
+                        None,   # reset slider
+                        ""      # clear correction box
                     )
                 except Exception as e:
                     logger.error(f"Feedback submission failed: {e}")
                     return (
                         f"❌ Failed to save feedback: {str(e)}",
-                        gr保留(notation_val),               # keep value on error
-                        correct_trans                      # keep text on error
+                        notation_val,   # keep value
+                        correct_trans   # keep text
                     )
+
+            # Connect events
+            input_mode.change(
+                fn=update_visibility,
+                inputs=input_mode,
+                outputs=[input_text, audio_input, file_input, extracted_text, output_text]
+            )
             
-                    # 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
-                        )
+            # Chain: Process → Translate → Store context
+            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, notation, correct_translation]
+            )
                     
-                    return interface
+        return interface
 
 # ================================
 # Application Entry Point