Method _update_memory

runtime/node/executor/agent_executor.py:1253–1286

Update the memory store with the latest conversation.

(self, node: Node, input_data: str, inputs: List[Message], result: Message | str)

            )
    
    def _update_memory(self, node: Node, input_data: str, inputs: List[Message], result: Message | str) -> None:
        """Update the memory store with the latest conversation."""
        memory_manager = self.context.get_memory_manager(node.id)
        if not memory_manager:
            return
        
        stage = AgentExecFlowStage.FINISHED_STAGE
        
        input_snapshot = MemoryContentSnapshot.from_messages(inputs)
        output_snapshot = MemoryContentSnapshot.from_message(result)
        payload = MemoryWritePayload(
            agent_role=node.role if node.role else "",
            inputs_text=input_data,
            input_snapshot=input_snapshot,
            output_snapshot=output_snapshot,
        )

        with self.log_manager.memory_timer(node.id, "UPDATE", stage.value):
            memory_manager.update(payload)
        
        # Record the memory update
        normalized_result = result.text_content() if isinstance(result, Message) else str(result)
        self.log_manager.record_memory_operation(
            node.id,
            "UPDATE",
            stage.value,
            normalized_result,
            {
                "stage": stage.value,
                "input_size": len(str(input_data)),
                "output_size": len(normalized_result),
                "attachment_count": len(output_snapshot.attachment_overview()) if output_snapshot else 0,
            }
        )

    def _build_thinking_payload_from_inputs(self, inputs: List[Message], input_text: str) -> ThinkingPayload:
        blocks: List[MessageBlock] = []