Fix minor comment missing (#21517)

api/core/workflow/utils/variable_utils.py

 ):
     """
     Append variables recursively
+    :param pool: variable pool to append variables to
     :param node_id: node id
     :param variable_key_list: variable key list
     :param variable_value: variable value

api/core/workflow/workflow_entry.py

             return node_instance, generator
         except Exception as e:
             logger.exception(
-                "error while running node_instance, workflow_id=%s, node_id=%s, type=%s, version=%s",
+                "error while running node_instance, node_id=%s, type=%s, version=%s",
                 node_instance.id,
                 node_instance.node_type,
                 node_instance.version(),

api/factories/file_factory.py

 
 class StorageKeyLoader:
     """FileKeyLoader load the storage key from database for a list of files.
-    This loader is batched, the
+    This loader is batched, the database query count is constant regardless of the input size.
     """
 
     def __init__(self, session: Session, tenant_id: str) -> None:
             if file.transfer_method in (FileTransferMethod.LOCAL_FILE, FileTransferMethod.REMOTE_URL):
                 upload_file_row = upload_files.get(model_id)
                 if upload_file_row is None:
-                    raise ValueError(...)
+                    raise ValueError(f"Upload file not found for id: {model_id}")
                 file._storage_key = upload_file_row.key
             elif file.transfer_method == FileTransferMethod.TOOL_FILE:
                 tool_file_row = tool_files.get(model_id)
                 if tool_file_row is None:
-                    raise ValueError(...)
+                    raise ValueError(f"Tool file not found for id: {model_id}")
                 file._storage_key = tool_file_row.file_key

api/services/dataset_service.py

             )
         except ProviderTokenNotInitError:
             # If we can't get the embedding model, preserve existing settings
+            logging.warning(
+                f"Failed to initialize embedding model {data['embedding_model_provider']}/{data['embedding_model']}, "
+                f"preserving existing settings"
+            )
             if dataset.embedding_model_provider and dataset.embedding_model:
                 filtered_data["embedding_model_provider"] = dataset.embedding_model_provider
                 filtered_data["embedding_model"] = dataset.embedding_model