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fix(workflow): rectify error handling and bolster execution logging

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- Rectify exception propagation during node execution failures to ensure errors are correctly raised.
- Bolster workflow logging to support failed status records and persist node execution data, including loop nodes.
This commit is contained in:
wwq
2026-04-24 11:39:33 +08:00
parent 5c89acced6
commit 0f7a7263eb
3 changed files with 117 additions and 46 deletions
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29
api/app/core/workflow/nodes/base_node.py
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@@ -228,19 +228,21 @@ class BaseNode(ABC):
logger.error(
f"Node {self.node_id} execution timed out ({timeout} seconds)."
)
return self._wrap_error(
self._wrap_error(
f"Node execution timed out ({timeout} seconds).",
elapsed_time,
state,
variable_pool,
)
raise
except Exception as e:
elapsed_time = (time.time() - start_time) * 1000
logger.error(
f"Node {self.node_id} execution failed: {e}",
exc_info=True,
)
return self._wrap_error(str(e), elapsed_time, state, variable_pool)
self._wrap_error(str(e), elapsed_time, state, variable_pool)
raise
async def run_stream(
self, state: WorkflowState,
@@ -351,11 +353,13 @@ class BaseNode(ABC):
variable_pool
)
yield error_output
raise
except Exception as e:
elapsed_time = (time.time() - start_time) * 1000
logger.error(f"Node {self.node_id} execution failed: {e}", exc_info=True)
error_output = self._wrap_error(str(e), elapsed_time, state, variable_pool)
yield error_output
raise
def _wrap_output(
self,
@@ -447,26 +451,19 @@ class BaseNode(ABC):
"error": error_message
}
# if error_edge:
# # If an error edge exists, log a warning and continue to error node
# logger.warning(
# f"Node {self.node_id} execution failed, redirecting to error node: {error_edge['target']}"
# )
# return {
# "node_outputs": {
# self.node_id: node_output
# },
# "error": error_message,
# "error_node": self.node_id
# }
# else:
writer = get_stream_writer()
writer({
"type": "node_error",
**node_output
})
logger.error(f"Node {self.node_id} execution failed, stopping workflow: {error_message}")
raise Exception(f"Node {self.node_id} execution failed: {error_message}")
return {
"node_outputs": {
self.node_id: node_output
},
"error": error_message,
"error_node": self.node_id
}
def _extract_input(self, state: WorkflowState, variable_pool: VariablePool) -> dict[str, Any]:
"""Extracts the input data for this node (used for logging or audit).