fix: preserve empty workflow filter outputs

app/chain/workflow.py

@@ -661,19 +661,40 @@ class WorkflowExecutor:
         declared_outputs = self.get_action_output_declarations(action)
         if isinstance(declared_outputs, list):
             normalized_outputs = {}
+            missing = object()
             for item in declared_outputs:
                 key = item.get("name") if isinstance(item, dict) else item
-                if key and outputs.get(key) not in (None, "", [], {}):
+                if not key:
-                    normalized_outputs[key] = outputs.get(key)
+                    continue
+                value = outputs.get(key, missing)
+                if value is missing and key in result_context.__class__.model_fields:
+                    value = getattr(result_context, key, missing)
+                if value is not missing and self.should_keep_output_value(action, key, value):
+                    normalized_outputs[key] = value
             return normalized_outputs or outputs
         if isinstance(declared_outputs, dict):
-            return {
+            normalized_outputs = {}
-                key: outputs.get(key)
+            missing = object()
-                for key in declared_outputs
+            for key in declared_outputs:
-                if outputs.get(key) not in (None, "", [], {})
+                value = outputs.get(key, missing)
-            } or outputs
+                if value is missing and key in result_context.__class__.model_fields:
+                    value = getattr(result_context, key, missing)
+                if value is not missing and self.should_keep_output_value(action, key, value):
+                    normalized_outputs[key] = value
+            return normalized_outputs or outputs
         return outputs
 
+    def should_keep_output_value(self, action: Action, key: str, value: Any) -> bool:
+        """
+        判断输出值是否应参与后续合并。
+        """
+        if value not in (None, "", [], {}):
+            return True
+        output_config = self.get_action_output_config(action, key)
+        target_key = output_config.get("target") or key
+        merge_policy = output_config.get("merge") or self.get_default_merge_policy(action, target_key, value)
+        return merge_policy == "replace"
+
     def record_node_outputs(self, action_id: str, outputs: dict) -> None:
         """
         记录当前节点输出，供后续条件表达式读取。
@@ -699,11 +720,11 @@ class WorkflowExecutor:
         按声明式合并策略写入全局上下文和 artifacts 分区。
         """
         for key, value in outputs.items():
-            if value in (None, "", [], {}):
-                continue
             output_config = self.get_action_output_config(action, key)
             target_key = output_config.get("target") or key
             merge_policy = output_config.get("merge") or self.get_default_merge_policy(action, target_key, value)
+            if value in (None, "", [], {}) and merge_policy != "replace":
+                continue
             identity = output_config.get("identity")
             self.merge_output_value(target_key, value, merge_policy, identity)
 

tests/test_workflow_execution.py

@@ -679,6 +679,58 @@ def test_workflow_executor_filter_action_replaces_artifact_outputs(monkeypatch):
     assert executor.context.artifacts["torrents"] == ["keep"]
 
 
+def test_workflow_executor_filter_action_replaces_with_empty_outputs(monkeypatch):
+    """过滤节点结果为空时也应清空上游资源，避免后续继续下载。"""
+    calls = []
+    stale_torrents = ["old", "drop"]
+    filtered_torrents = []
+
+    def run_fetch(action, context):
+        """模拟上游搜索节点产出资源池。"""
+        context.torrents = stale_torrents.copy()
+        return ActionResult(
+            success=True,
+            message=f"{action.name}完成",
+            context=context,
+            outputs={"torrents": stale_torrents.copy()}
+        )
+
+    def run_filter(action, context):
+        """模拟过滤节点把资源全部过滤掉。"""
+        context.torrents = filtered_torrents.copy()
+        return ActionResult(
+            success=True,
+            message=f"{action.name}完成",
+            context=context,
+            outputs={"torrents": filtered_torrents.copy()}
+        )
+
+    fake_manager = _FakeWorkflowManager(
+        calls,
+        results={
+            "A": run_fetch,
+            "B": run_filter,
+        }
+    )
+    workflow = _build_workflow(
+        actions=[
+            {"id": "A", "type": "FetchTorrentsAction", "name": "搜索站点资源", "data": {}},
+            {"id": "B", "type": "FilterTorrentsAction", "name": "过滤资源", "data": {}},
+        ],
+    )
+
+    monkeypatch.setattr(workflow_module, "WorkFlowManager", lambda: fake_manager)
+    monkeypatch.setattr(workflow_module.global_vars, "workflow_resume", lambda workflow_id: None)
+    monkeypatch.setattr(workflow_module.global_vars, "is_workflow_stopped", lambda workflow_id: False)
+
+    executor = workflow_module.WorkflowExecutor(workflow)
+    executor.execute()
+
+    assert executor.context.torrents == filtered_torrents
+    assert executor.context.artifacts["torrents"] == filtered_torrents
+    assert executor.context.node_outputs["B"]["torrents"] == filtered_torrents
+
+
 def test_workflow_executor_stop_is_not_success(monkeypatch):
     """停止信号不应被执行器汇报为成功完成。"""
     calls = []