feat: 持久化会话节点结果与失败通知留痕

tests/test_chat.py

@@ -172,6 +172,106 @@ def test_chat_execution_creates_notification_record_from_agent_result(client, db
     assert record.batch_id == batch.batch_id
 
 
+def test_chat_execution_creates_failed_notification_record_and_updates_conversation(client, db, monkeypatch):
+    batch, conversation = _create_conversation_with_batch()
+    UploadedDocument.objects.create(
+        batch=batch,
+        scenario_id="document_review",
+        original_name="说明书.md",
+        file_type="md",
+        size=1,
+        status=UploadedDocument.STATUS_INDEXED,
+    )
+
+    monkeypatch.setattr(
+        "apps.chat.views.run_agent",
+        lambda *args, **kwargs: AgentResult(
+            answer="执行失败",
+            status="failed",
+            error="规则执行失败",
+            node_results=[
+                {"code": "package_import", "label": "资料包导入", "status": "已完成"},
+                {"code": "overview", "label": "目录汇总", "status": "已完成"},
+                {"code": "risk", "label": "风险预警", "status": "已阻断"},
+                {"code": "feishu_notify", "label": "飞书通知", "status": "失败"},
+            ],
+            notification_payload={
+                "batch_id": batch.batch_id,
+                "conversation_id": conversation.conversation_id,
+                "product_name": batch.product_name,
+                "notify_reason": "task_failed",
+                "owners": [
+                    {
+                        "owner_role": "注册申报负责人",
+                        "feishu_user_id": "ou_demo_2",
+                    }
+                ],
+            },
+        ),
+    )
+
+    response = client.post(
+        reverse("chat:detail", args=[conversation.conversation_id]),
+        {"message": "执行失败任务"},
+    )
+
+    assert response.status_code == 200
+    record = NotificationRecord.objects.get()
+    conversation.refresh_from_db()
+    assert record.notify_reason == "task_failed"
+    assert record.message_status == "failed"
+    assert conversation.task_status == "failed"
+    assert conversation.node_results[-1]["label"] == "飞书通知"
+
+
+def test_chat_execution_persists_agent_node_results_to_conversation(client, db, monkeypatch):
+    batch, conversation = _create_conversation_with_batch()
+    UploadedDocument.objects.create(
+        batch=batch,
+        scenario_id="document_review",
+        original_name="说明书.md",
+        file_type="md",
+        size=1,
+        status=UploadedDocument.STATUS_INDEXED,
+    )
+
+    monkeypatch.setattr(
+        "apps.chat.views.run_agent",
+        lambda *args, **kwargs: AgentResult(
+            answer="已生成风险结论",
+            status="success",
+            node_results=[
+                {"code": "package_import", "label": "资料包导入", "status": "已完成"},
+                {"code": "overview", "label": "目录汇总", "status": "已完成"},
+                {"code": "completeness", "label": "法规完整性检查", "status": "已完成"},
+                {"code": "field_extraction", "label": "字段抽取", "status": "已完成"},
+                {"code": "consistency", "label": "一致性核查", "status": "待复核"},
+                {"code": "risk", "label": "风险预警", "status": "已阻断", "summary": "存在高风险"},
+                {"code": "word_export", "label": "Word 回填导出", "status": "待处理"},
+                {"code": "feishu_notify", "label": "飞书通知", "status": "待处理"},
+            ],
+            notification_payload={
+                "batch_id": batch.batch_id,
+                "conversation_id": conversation.conversation_id,
+                "product_name": batch.product_name,
+                "notify_reason": "task_completed",
+                "owners": [],
+            },
+        ),
+    )
+
+    response = client.post(
+        reverse("chat:detail", args=[conversation.conversation_id]),
+        {"message": "执行节点任务"},
+    )
+
+    assert response.status_code == 200
+    conversation.refresh_from_db()
+    assert len(conversation.node_results) == 8
+    assert conversation.task_status == "success"
+    assert conversation.latest_summary["answer"] == "已生成风险结论"
+
+
 def test_create_conversation_for_batch_initializes_eight_workflow_nodes(db):
     conversation = create_conversation_for_batch(
         "SUB-20260604-001",