feat: add workflow action runtime policies

backend/services/brains/workflow_brain.py

@@ -724,19 +724,29 @@ class WorkflowBrain(BaseBrain):
         self._state.enter(node_id, WorkflowStatus.RUNNING_ACTION)
         await self._emit_node_active(node_id)
         data = self._engine.data(node_id)
+        runtime = self._require_runtime()
+        block_user_input = data.get("userInputPolicy") == "block"
+        if block_user_input and runtime.set_input_enabled:
+            # Blocking only suppresses new audio/text input while the Action
+            # runs.  It deliberately does not cancel the tool.  The default
+            # queue policy leaves input enabled; the turn lock serializes any
+            # completed user turn until this automatic path has finished.
+            runtime.set_input_enabled(False)
         tool_id = str(data.get("toolId") or "")
         tool = self._tool_by_id.get(tool_id)
-        if not tool:
-            self._store.values["system__last_action_status"] = "error"
-            self._store.values["system__last_action_error"] = f"工具不存在:{tool_id}"
-            return
         try:
+            if not tool:
+                raise ToolExecutionError(f"工具不存在:{tool_id}")
             arguments = self._store.render_data(data.get("arguments") or {})
             result = await self._tools.execute(
                 tool,
                 arguments,
-                result_assignments=data.get("resultAssignments") or {},
+                result_assignments=self._action_result_assignments(data),
             )
+            if result.get("status") != "ok":
+                raise ToolExecutionError(
+                    str(result.get("message") or "工具返回执行失败状态")
+                )
             updated_variables = list(result.get("updated_variables") or [])
             if updated_variables:
                 await self._emit_variables(
@@ -749,6 +759,26 @@ class WorkflowBrain(BaseBrain):
         except (ToolExecutionError, ValueError) as exc:
             self._store.values["system__last_action_status"] = "error"
             self._store.values["system__last_action_error"] = str(exc)[:2048]
+        finally:
+            if block_user_input and runtime.set_input_enabled:
+                runtime.set_input_enabled(True)
+
+    @staticmethod
+    def _action_result_assignments(
+        data: dict[str, Any],
+    ) -> dict[str, str] | None:
+        """Resolve node mapping semantics for ToolExecutor.
+
+        ``None`` means inherit the reusable tool's mapping, while an empty
+        dictionary explicitly disables all result assignments.
+        """
+        mode = str(data.get("resultAssignmentMode") or "none")
+        if mode == "inherit":
+            return None
+        if mode == "override":
+            assignments = data.get("resultAssignments")
+            return dict(assignments) if isinstance(assignments, dict) else {}
+        return {}
 
     async def _enter_handoff(self, node_id: str) -> None:
         self._state.enter(node_id, WorkflowStatus.HANDOFF)