[V10.327] 補 OpenClaw 備援可觀測性

tests/test_caller_registry.py

@@ -28,6 +28,12 @@ def test_registry_contains_core_callers():
         'openclaw_daily', 'openclaw_weekly', 'openclaw_monthly',
         'openclaw_meta', 'openclaw_qa',
         'openclaw_qa_gemini_fallback', 'openclaw_qa_nim',
+        'openclaw_daily_gemini_fallback', 'openclaw_weekly_gemini_fallback',
+        'openclaw_monthly_gemini_fallback', 'openclaw_meta_gemini_fallback',
+        'openclaw_daily_insight_gemini_fallback',
+        'openclaw_daily_nim', 'openclaw_weekly_nim',
+        'openclaw_monthly_nim', 'openclaw_meta_nim',
+        'openclaw_daily_insight_nim',
         # MCP
         'mcp_l1_grounding', 'mcp_collector',
         # Code Review

tests/test_mcp_collector_ollama_first.py

@@ -0,0 +1,38 @@
+from types import SimpleNamespace
+
+
+def test_mcp_collector_uses_ollama_before_gemini(monkeypatch):
+    import services.mcp_collector_service as mcp_mod
+    import services.mcp_router as router_mod
+
+    service = mcp_mod.MCPCollectorService()
+    monkeypatch.setattr(service, "_read_cache", lambda _topic: None)
+    monkeypatch.setattr(router_mod, "is_mcp_router_enabled", lambda: False)
+    monkeypatch.setattr(mcp_mod, "_OLLAMA_AVAILABLE", True)
+
+    def fail_gemini_init():
+        raise AssertionError("Gemini must not initialize before Ollama fallback is tried")
+
+    calls = []
+
+    class FakeOllamaService:
+        def __init__(self, model=None):
+            self.model = model
+
+        def generate(self, **kwargs):
+            calls.append(kwargs)
+            return SimpleNamespace(
+                success=True,
+                content="(此為基於歷史趨勢的預測性洞察) 台灣電商促銷可先檢查母親節、618 與競品價差。",
+                error=None,
+            )
+
+    monkeypatch.setattr(service, "_ensure_init", fail_gemini_init)
+    monkeypatch.setattr(mcp_mod, "OllamaService", FakeOllamaService)
+
+    result = service._search_topic("market_trends", "台灣電商促銷趨勢")
+
+    assert "基於歷史趨勢" in result
+    assert calls
+    assert calls[0]["model"]
+    assert calls[0]["options"]["num_predict"] == 800