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fix: Variable Aggregator Node supports parallel branching #8677

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fix: Variable Aggregator Node supports parallel branching #8677

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fdcd4bc
fix: Variable Aggregator Node supports parallel branching
wangiii Sep 23, 2024
4f12a0a
Merge branch 'langgenius_main' into fix_VariableAggregatorNode
wangiii Sep 23, 2024
2bde923
fix: Variable Aggregator Node supports parallel branching
wangiii Sep 23, 2024
971db3b
Merge branch 'langgenius_main' into fix_VariableAggregatorNode
wangiii Sep 23, 2024
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12 changes: 7 additions & 5 deletions api/core/workflow/nodes/variable_aggregator/variable_aggregator_node.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,10 +21,13 @@ def _run(self) -> NodeRunResult:
for selector in node_data.variables:
variable = self.graph_runtime_state.variable_pool.get_any(selector)
if variable is not None:
outputs = {"output": variable}

inputs = {".".join(selector[1:]): variable}
break
if "output" not in outputs:
outputs["output"] = []
if isinstance(variable, list):
outputs["output"].extend(variable)
elif isinstance(variable, str):
outputs["output"].append(variable)
inputs[".".join(selector[1:])] = variable
Comment on lines +24 to +30
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Would you pls explain the purpose of this codes?

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When the parallel branch calls the knowledge recall and then aggregates, the variable is a list, and the parameter aggregation variable after the ordinary if else node is a str.

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When the parallel branch calls the knowledge recall and then aggregates, the variable is a list, and the parameter aggregation variable after the ordinary if else node is a str.

Could you explain the problem you’re encountering? I'd like to understand the context and intent.
If possible, pls create an issue and link it to this PR.

else:
for group in node_data.advanced_settings.groups:
for selector in group.variables:
Expand All @@ -33,7 +36,6 @@ def _run(self) -> NodeRunResult:
if variable is not None:
outputs[group.group_name] = {"output": variable}
inputs[".".join(selector[1:])] = variable
break

return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED, outputs=outputs, inputs=inputs)

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