Add progress tracking to batch classification process

src/interface/file_upload_interface.py

@@ -362,7 +362,7 @@ class FileUploadInterfaceController(ProgressTrackingMixin):
         
         return classification
 
-    def run_batch_classification(self) -> Tuple[bool, str, Dict[str, Any]]:
+    def run_batch_classification(self, progress: Optional[gr.Progress] = None) -> Tuple[bool, str, Dict[str, Any]]:
         """Run classification for the whole uploaded dataset and persist results.
 
         File Upload Mode is already labeled (ground truth provided in the file), so we
@@ -389,6 +389,11 @@ class FileUploadInterfaceController(ProgressTrackingMixin):
             self.setup_progress_tracking(total)
 
             for idx, test_message in enumerate(self.current_file_result.parsed_test_cases):
+                if progress is not None:
+                    progress(
+                        (idx) / total,
+                        desc=f"Processing {idx + 1}/{total}"
+                    )
                 self.batch_processing_start_time = datetime.now()
 
                 user_prompt = (
@@ -438,6 +443,9 @@ class FileUploadInterfaceController(ProgressTrackingMixin):
             self.current_session.is_complete = True
             self.current_session.completed_at = datetime.now()
 
+            if progress is not None:
+                progress(1.0, desc=f"Completed {total}/{total}")
+
             self.store.save_session(self.current_session)
 
             accuracy = (
@@ -805,6 +813,9 @@ def create_file_upload_interface() -> gr.Blocks:
                     "Ready to start batch processing",
                     label="Progress"
                 )
+
+                # Visual progress bar (updates during batch classification)
+                batch_progress_bar = gr.Progress()
         
         # Message processing section (initially hidden)
         message_processing_section = gr.Row(visible=False)
@@ -961,7 +972,7 @@ def create_file_upload_interface() -> gr.Blocks:
             if success:
                 # Simplified behavior: dataset is already labeled, so run full batch
                 # classification immediately and generate results for export.
-                run_ok, run_msg, stats = controller.run_batch_classification()
+                run_ok, run_msg, stats = controller.run_batch_classification(progress=batch_progress_bar)
                 if run_ok:
                     progress_text = f"✅ Completed: {stats.get('processed', 0)}/{stats.get('total', 0)} messages"
                     return (