feat: 交互Agent + VLM优化 + 企微演示模式

- 新增交互Agent调度器（意图识别 + 工单/查询/报表/闲聊4个Handler）
- 新增工单服务、Excel报表生成器、企微消息加解密模块
- VLM提示词优化（角色设定、≤25字描述、布尔值优先输出）
- VLM降级策略（入侵默认放行、离岗默认拦截）
- 企微演示模式（WECHAT_TEST_UIDS兜底 + SERVICE_BASE_URL修复）
- 新增Agent回调路由和测试接口

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

app/services/notify_dispatch.py

@@ -69,6 +69,14 @@ async def process_alarm_notification(alarm_data: Dict):
         description = vlm_result.get("description", "")
         area_name, persons = _get_notify_persons(device_id, alarm_level)
 
+        # 演示模式：数据库无人员时，使用配置的测试 userid
+        if not persons and settings.wechat.test_uids:
+            test_uids = [uid.strip() for uid in settings.wechat.test_uids.split(",") if uid.strip()]
+            if test_uids:
+                persons = [{"person_name": "测试用户", "wechat_uid": uid, "role": "TEST"} for uid in test_uids]
+                area_name = "演示区域"
+                logger.info(f"演示模式: 使用测试用户 {test_uids}")
+
         if not persons:
             logger.warning(f"未找到通知人员: camera={device_id}, 跳过企微推送")
             return
@@ -95,7 +103,7 @@ async def process_alarm_notification(alarm_data: Dict):
             snapshot_url=snapshot_url,
             event_time=event_time_str,
             alarm_level=alarm_level,
-            service_base_url=f"http://{settings.app.host}:{settings.app.port}",
+            service_base_url=settings.wechat.service_base_url or f"http://{settings.app.host}:{settings.app.port}",
         )
 
         logger.info(f"告警通知完成: {alarm_id} → {len(persons)} 人")
@@ -110,12 +118,12 @@ def _save_vlm_result(alarm_id: str, vlm_result: Dict):
     try:
         analysis = AlarmLlmAnalysis(
             alarm_id=alarm_id,
-            llm_model=vlm_result.get("model", "qwen3-vl-flash"),
+            llm_model="qwen3-vl-flash",
             analysis_type="REVIEW",
             summary=vlm_result.get("description", ""),
             is_false_alarm=not vlm_result.get("confirmed", True),
-            confidence_score=0.0 if vlm_result.get("skipped") else 0.9,
-            suggestion=None,
+            confidence_score=None if vlm_result.get("skipped") else 0.9,
+            suggestion="VLM跳过" if vlm_result.get("skipped") else None,
         )
         db.add(analysis)
         db.commit()