orchestrator: 全专家失败时不调用 aggregator provider

src/llm/agents/orchestrator.py

@@ -259,7 +259,8 @@ async def predict_match_multi(
             "match %s: 所有 %d 位专家均无有效数据,跳过终裁,标记 degraded",
             match_id, len(reports),
         )
-        aggregator_provider = await _agent_provider("aggregator", tier="aggregator")
+        # 无有效专家时不调用 aggregator provider,避免多余开销
+        # model 使用 settings 默认值占位(无实际 LLM 调用)
         final = {
             "pred_home_goals": None,
             "pred_away_goals": None,
@@ -272,6 +273,7 @@ async def predict_match_multi(
         }
         agg_prompt_tokens = 0
         agg_completion_tokens = 0
+        aggregator_model = settings.LLM_MODEL  # 占位,无实际 LLM 调用
 
     latency_ms = int((time.perf_counter() - start) * 1000)
 
@@ -297,17 +299,19 @@ async def predict_match_multi(
                 raise RuntimeError(f"终裁输出校验失败: {e}")
             agent_weights = validate_agent_weights(final.get("agent_weights"))
             pred_status = "success"
+            model_name = aggregator_provider.model
         else:
             # 无有效报告:跳过严格校验,直接构造降级结果
             validated = None  # type: ignore
             agent_weights = {}
             pred_status = "degraded"
+            model_name = aggregator_model
 
         pred = await _upsert_prediction(
             session,
             match_id=match_id,
             provider_name=settings.LLM_PROVIDER,
-            model=aggregator_provider.model,
+            model=model_name,
             mode="multi",
             run_type="backtest" if backtest else "live",
             values={

tests/test_multi_agent_degraded.py

@@ -244,3 +244,57 @@ class TestPartialExpertsOk:
         assert captured_status.get("status") == "success", \
             f"期望 status=success,实际 {captured_status.get('status')}"
         print(f"PASS: 1 ok + 4 error → status={captured_status.get('status')}")
+
+
+class TestNoAggregatorCallOnDegraded:
+    """全专家失败时,aggregator provider 不应被调用。"""
+
+    @pytest.mark.asyncio
+    async def test_all_error_no_aggregator_call(self):
+        """5 个专家全 error → 不应调用 _agent_provider('aggregator')。"""
+        header = _make_header()
+        aggregator_called = []
+
+        async def mock_run_specialists(header, *, version, before):
+            return _all_error_reports()
+
+        async def mock_agent_provider(agent_id, *, tier):
+            aggregator_called.append((agent_id, tier))
+            return MagicMock(model="test-model")
+
+        async def mock_load_header(mid, db=None):
+            return header
+
+        captured_values = {}
+
+        async def mock_upsert(session, **kw):
+            captured_values.update(kw.get("values", {}))
+            mock_pred = MagicMock()
+            mock_pred.id = 1
+            mock_pred.provider = "test"
+            mock_pred.model = kw["values"].get("model")
+            return mock_pred
+
+        class FakeUow:
+            async def __aenter__(self):
+                return self
+            async def __aexit__(self, *a):
+                pass
+            async def get(self, cls, id):
+                return MagicMock()
+
+        with patch.object(orch_mod, "run_specialists", mock_run_specialists), \
+             patch.object(orch_mod, "_agent_provider", mock_agent_provider), \
+             patch.object(orch_mod, "load_match_header", mock_load_header), \
+             patch.object(orch_mod, "_upsert_prediction", mock_upsert), \
+             patch.object(orch_mod, "get_uow", FakeUow):
+
+            await orch_mod.predict_match_multi(999)
+
+        # 断言:aggregator provider 未被调用
+        assert len(aggregator_called) == 0, \
+            f"全失败时不应调用 aggregator provider,实际调用: {aggregator_called}"
+        # 断言:model 使用 settings 默认值
+        assert captured_values.get("model") is not None
+        assert captured_values.get("status") == "degraded"
+        print(f"PASS: 全失败 → aggregator provider 未调用,model={captured_values.get('model')}")