Chore: correct inconsistent logging and typo (#25945)

api/core/repositories/sqlalchemy_workflow_node_execution_repository.py

 
         if db_model is not None:
             offload_data = db_model.offload_data
-
         else:
             db_model = self._to_db_model(domain_model)
-            offload_data = []
+            offload_data = db_model.offload_data
 
-        offload_data = db_model.offload_data
         if domain_model.inputs is not None:
             result = self._truncate_and_upload(
                 domain_model.inputs,

api/core/workflow/graph_engine/layers/execution_limits.py

             self.logger.debug("Abort command sent to engine")
 
         except Exception:
-            self.logger.exception("Failed to send abort command: %s")
+            self.logger.exception("Failed to send abort command")

api/services/rag_pipeline/rag_pipeline.py

         """
         Retry error document
         """
-        document_pipeline_excution_log = (
+        document_pipeline_execution_log = (
             db.session.query(DocumentPipelineExecutionLog)
             .where(DocumentPipelineExecutionLog.document_id == document.id)
             .first()
         )
-        if not document_pipeline_excution_log:
+        if not document_pipeline_execution_log:
             raise ValueError("Document pipeline execution log not found")
-        pipeline = db.session.query(Pipeline).where(Pipeline.id == document_pipeline_excution_log.pipeline_id).first()
+        pipeline = db.session.query(Pipeline).where(Pipeline.id == document_pipeline_execution_log.pipeline_id).first()
         if not pipeline:
             raise ValueError("Pipeline not found")
         # convert to app config
             workflow=workflow,
             user=user,
             args={
-                "inputs": document_pipeline_excution_log.input_data,
-                "start_node_id": document_pipeline_excution_log.datasource_node_id,
-                "datasource_type": document_pipeline_excution_log.datasource_type,
-                "datasource_info_list": [json.loads(document_pipeline_excution_log.datasource_info)],
+                "inputs": document_pipeline_execution_log.input_data,
+                "start_node_id": document_pipeline_execution_log.datasource_node_id,
+                "datasource_type": document_pipeline_execution_log.datasource_type,
+                "datasource_info_list": [json.loads(document_pipeline_execution_log.datasource_info)],
                 "original_document_id": document.id,
             },
             invoke_from=InvokeFrom.PUBLISHED,

api/services/rag_pipeline/rag_pipeline_transform_service.py

         indexing_technique = dataset.indexing_technique
 
         if not datasource_type and not indexing_technique:
-            return self._transfrom_to_empty_pipeline(dataset)
+            return self._transform_to_empty_pipeline(dataset)
 
         doc_form = dataset.doc_form
         if not doc_form:
-            return self._transfrom_to_empty_pipeline(dataset)
+            return self._transform_to_empty_pipeline(dataset)
         retrieval_model = dataset.retrieval_model
         pipeline_yaml = self._get_transform_yaml(doc_form, datasource_type, indexing_technique)
         # deal dependencies
             logger.debug("Installing missing pipeline plugins %s", need_install_plugin_unique_identifiers)
             PluginService.install_from_marketplace_pkg(tenant_id, need_install_plugin_unique_identifiers)
 
-    def _transfrom_to_empty_pipeline(self, dataset: Dataset):
+    def _transform_to_empty_pipeline(self, dataset: Dataset):
         pipeline = Pipeline(
             tenant_id=dataset.tenant_id,
             name=dataset.name,