Add progress tracking and caching checks for model downloads

- Introduced methods to check if models are cached locally in MLX and PyTorch backends.
- Enhanced progress tracking during model loading to filter out non-download progress when models are cached.
- Updated HFProgressTracker to conditionally report progress based on download status.
- Added test scripts for monitoring SSE events during model downloads and verifying progress tracking functionality.
- Improved overall error handling and logging for better debugging during model download processes.

backend/tests/test_check_progress_state.py

@@ -0,0 +1,48 @@
+"""
+Check the internal state of ProgressManager.
+"""
+import sys
+import time
+
+# Add backend to path
+sys.path.insert(0, '.')
+
+from utils.progress import get_progress_manager
+from utils.tasks import get_task_manager
+
+def main():
+    pm = get_progress_manager()
+    tm = get_task_manager()
+
+    print("=" * 60)
+    print("ProgressManager State Inspector")
+    print("=" * 60)
+
+    # Check all progress
+    print("\nAll progress entries:")
+    print(f"  _progress dict: {pm._progress}")
+
+    # Check listeners
+    print("\nActive listeners:")
+    print(f"  _listeners dict: {pm._listeners}")
+
+    # Check main loop
+    print(f"\nMain loop set: {pm._main_loop is not None}")
+    if pm._main_loop:
+        print(f"  Loop running: {pm._main_loop.is_running()}")
+
+    # Check task manager
+    print("\nTaskManager state:")
+    print(f"  Active downloads: {tm.get_active_downloads()}")
+    print(f"  Active generations: {tm.get_active_generations()}")
+
+    # Check for specific model
+    print("\nChecking whisper-base specifically:")
+    progress = pm.get_progress("whisper-base")
+    if progress:
+        print(f"  Progress: {progress}")
+    else:
+        print("  No progress data found")
+
+if __name__ == "__main__":
+    main()