feat: 统一治理配置与通知责任人映射

tests/test_agent_core.py

@@ -2,6 +2,7 @@ from agent_core.orchestrator import build_messages, run_agent
 from agent_core.rag.ingest import _split_text, ingest_document
 from agent_core.rag.retriever import retrieve
 from agent_core.schemas.outputs import SUPPORTED_OUTPUT_TYPES
+from django.test import override_settings
 
 
 def test_run_agent_returns_structured_result_from_llm_output():
@@ -352,3 +353,110 @@ def test_registration_risk_report_builds_eight_business_nodes():
     assert result.node_results[5]["status"] == "已阻断"
     assert result.node_results[6]["status"] == "待处理"
     assert result.node_results[7]["status"] == "待处理"
+
+
+@override_settings(GOVERNANCE_CONFIG_PATH="")
+def test_registration_risk_payload_falls_back_to_governance_owner_mappings(tmp_path):
+    config_path = tmp_path / "governance.yaml"
+    config_path.write_text(
+        """
+owner_mappings:
+  - owner_role: 法规负责人
+    owner_name: 赵六
+    department: 法规事务部
+    chapter_scope: CH1
+    risk_scope: 高风险缺失
+    feishu_user_id: ou_governance_1
+    feishu_open_id: on_governance_1
+    feishu_name: 赵六
+    notify_enabled: 是
+""".strip(),
+        encoding="utf-8",
+    )
+    scenario = {
+        "id": "document_review",
+        "name": "注册审核智能体",
+        "agent": {
+            "role": "注册审核助手",
+            "goal": "输出风险结果",
+            "instructions": ["输出结构化风险结果"],
+        },
+        "rag": {"enabled": False},
+        "tools": [],
+        "output": {"type": "registration_risk_report"},
+    }
+    provider_response = """
+    {
+      "summary": "存在高风险项，需人工复核。",
+      "highest_risk_level": "high",
+      "pass_status": "blocked",
+      "owner_roles": [],
+      "notify_reason": "task_completed"
+    }
+    """
+
+    class FakeProvider:
+        def generate(self, messages, response_format=None):
+            from agent_core.llm_provider import LLMResponse
+
+            return LLMResponse(content=provider_response, model_name="demo-model", success=True)
+
+    with override_settings(GOVERNANCE_CONFIG_PATH=config_path):
+        result = run_agent(scenario, "请输出风险结果", options={"llm_provider": FakeProvider()})
+
+    owner = result.notification_payload["owners"][0]
+    assert owner["owner_role"] == "法规负责人"
+    assert owner["feishu_user_id"] == "ou_governance_1"
+    assert result.notification_payload["notify_reason"] == "task_completed"
+
+
+@override_settings(GOVERNANCE_CONFIG_PATH="")
+def test_failed_agent_result_uses_governance_owner_mappings_for_failed_notification(tmp_path):
+    config_path = tmp_path / "governance.yaml"
+    config_path.write_text(
+        """
+owner_mappings:
+  - owner_role: 注册资料负责人
+    owner_name: 孙七
+    department: 注册事务部
+    chapter_scope: CH2
+    risk_scope: 执行异常
+    feishu_user_id: ou_failed_1
+    feishu_open_id: on_failed_1
+    feishu_name: 孙七
+    notify_enabled: 是
+""".strip(),
+        encoding="utf-8",
+    )
+    scenario = {
+        "id": "document_review",
+        "name": "注册审核智能体",
+        "agent": {
+            "role": "注册审核助手",
+            "goal": "输出风险结果",
+            "instructions": ["输出结构化风险结果"],
+        },
+        "rag": {"enabled": False},
+        "tools": [],
+        "output": {"type": "registration_risk_report"},
+    }
+
+    class FailedProvider:
+        def generate(self, messages, response_format=None):
+            from agent_core.llm_provider import LLMResponse
+
+            return LLMResponse(
+                content="",
+                model_name="demo-model",
+                success=False,
+                error="provider down",
+            )
+
+    with override_settings(GOVERNANCE_CONFIG_PATH=config_path):
+        result = run_agent(scenario, "请输出风险结果", options={"llm_provider": FailedProvider()})
+
+    owner = result.notification_payload["owners"][0]
+    assert result.status == "failed"
+    assert result.notification_payload["notify_reason"] == "task_failed"
+    assert owner["owner_name"] == "孙七"
+    assert owner["feishu_open_id"] == "on_failed_1"