diff --git a/api/tasks/clean_dataset_task.py b/api/tasks/clean_dataset_task.py
index 69e5df025..9a45115b0 100644
--- a/api/tasks/clean_dataset_task.py
+++ b/api/tasks/clean_dataset_task.py
@@ -56,19 +56,29 @@ def clean_dataset_task(
         documents = db.session.query(Document).where(Document.dataset_id == dataset_id).all()
         segments = db.session.query(DocumentSegment).where(DocumentSegment.dataset_id == dataset_id).all()
 
-        # Fix: Always clean vector database resources regardless of document existence
-        # This ensures all 33 vector databases properly drop tables/collections/indices
-        if doc_form is None:
-            # Use default paragraph index type for empty datasets to enable vector database cleanup
+        # Enhanced validation: Check if doc_form is None, empty string, or contains only whitespace
+        # This ensures all invalid doc_form values are properly handled
+        if doc_form is None or (isinstance(doc_form, str) and not doc_form.strip()):
+            # Use default paragraph index type for empty/invalid datasets to enable vector database cleanup
             from core.rag.index_processor.constant.index_type import IndexType
 
             doc_form = IndexType.PARAGRAPH_INDEX
             logging.info(
-                click.style(f"No documents found, using default index type for cleanup: {doc_form}", fg="yellow")
+                click.style(f"Invalid doc_form detected, using default index type for cleanup: {doc_form}", fg="yellow")
             )
 
-        index_processor = IndexProcessorFactory(doc_form).init_index_processor()
-        index_processor.clean(dataset, None, with_keywords=True, delete_child_chunks=True)
+        # Add exception handling around IndexProcessorFactory.clean() to prevent single point of failure
+        # This ensures Document/Segment deletion can continue even if vector database cleanup fails
+        try:
+            index_processor = IndexProcessorFactory(doc_form).init_index_processor()
+            index_processor.clean(dataset, None, with_keywords=True, delete_child_chunks=True)
+            logging.info(click.style(f"Successfully cleaned vector database for dataset: {dataset_id}", fg="green"))
+        except Exception as index_cleanup_error:
+            logging.exception(click.style(f"Failed to clean vector database for dataset {dataset_id}", fg="red"))
+            # Continue with document and segment deletion even if vector cleanup fails
+            logging.info(
+                click.style(f"Continuing with document and segment deletion for dataset: {dataset_id}", fg="yellow")
+            )
 
         if documents is None or len(documents) == 0:
             logging.info(click.style(f"No documents found for dataset: {dataset_id}", fg="green"))
@@ -128,6 +138,14 @@ def clean_dataset_task(
             click.style(f"Cleaned dataset when dataset deleted: {dataset_id} latency: {end_at - start_at}", fg="green")
         )
     except Exception:
+        # Add rollback to prevent dirty session state in case of exceptions
+        # This ensures the database session is properly cleaned up
+        try:
+            db.session.rollback()
+            logging.info(click.style(f"Rolled back database session for dataset: {dataset_id}", fg="yellow"))
+        except Exception as rollback_error:
+            logging.exception("Failed to rollback database session")
+
         logging.exception("Cleaned dataset when dataset deleted failed")
     finally:
         db.session.close()