增加未来5分钟pm2.5的预测功能

config/config.yaml

@@ -41,8 +41,8 @@ remote:
     isSuper: 'true'
     token: 'b4d751b5ffff882b2e410c5901c80dc0705bb96f1bc4e8b47e918ad49085f90e'
   base_url:
+    bme-algorithm-prediction: http://10.10.10.17:43002  # 算法预测服务
     bme-screen-service: https://vis.bmetech.com/vis
-#    bme-screen-service: http://localhost:9070/screen
     bme-reduce-cost-screen-service: https://vis.bmetech.com/reducecostscreen
 #    bme-screen-service: http://192.168.138.158:4050/vis  # 常州中天
 #    bme-reduce-cost-screen-service: http://192.168.138.158:4070/reducecostscreen  # 常州中天

server/server.py

@@ -20,6 +20,8 @@ bme_screen_service = base_url["bme-screen-service"]
 
 bme_reduce_cost_screen_service = base_url["bme-reduce-cost-screen-service"]
 
+bme_algorithm_prediction = base_url["bme-algorithm-prediction"]
+
 
 def deal_request_exception(response):
     """
@@ -46,6 +48,56 @@ def get_size_limit(size: int, max_size=20, min_size=0) -> int:
     size = min_size if size < min_size else size
     return size
 
+@mcp.tool()
+def get_air_pm_25_prediction(customer_id: int, device_name: str, start_time: str, end_time: str) -> Any:
+    """
+    根据客户id和设备名称获取PM2.5未来节点（5分钟后）预测值
+    start_time如果没有指定，默认值是当前时间的一天前，如：2025-04-29 16:00:00;
+    end_time如果没有指定，默认值是当前时间，如：2025-04-30 16:00:00;
+
+    :param customer_id: 客户id
+    :param device_name: 设备名称
+    :param start_time: 开始时间，格式为yyyy-MM-dd HH:mm:ss
+    :param end_time: 结束时间，格式为yyyy-MM-dd HH:mm:ss
+    :return: 返回结构中的字段名解释：
+        flag：标记, True代表预测成功，data就是预测的值，False代表预测失败，data就是错误信息
+        data：预测结果，当Flag为True时才说明预测成功
+    """
+    response = requests.get(bme_screen_service + "/monitor/getMonitorList", {
+        "customerId": customer_id,
+        "order": 1,
+        "type": "1",
+        "pageNo": "1",
+        "pageSize": "1",
+        "index": 2,
+        "typeId": "",
+        "deviceName": device_name
+    }, headers=headers)
+    device_records = deal_request_exception(response).get("data", {}).get("page", {}).get("records", [])
+    if not device_records:
+        return {"flag": False, "data": "设备不存在"}
+    device_no = device_records[0].get("deviceNo")
+    response = requests.get(bme_screen_service + "/monitor/getMonitorDetailNew_new", {
+        "customerId": customer_id,
+        "deviceNo": device_no,
+        "startTime": start_time,
+        "endTime": end_time
+    }, headers=headers)
+    assemble_data = deal_request_exception(response).get("data", {}).get("assembleData", [])
+    result = next((item for item in assemble_data if item.get("name") == "PM2.5"), None)
+    if not result:
+        return {"flag": False, "data": "无历史数据"}
+    history_data = result.get("list", [])
+    if not history_data:
+        return {"flag": False, "data": "无历史数据"}
+    signal_no = result.get("signalNo")
+    response = requests.post(bme_algorithm_prediction + "/predict/pm2p5", json={
+        "deviceNo": device_no,
+        "signalNo": signal_no,
+        "historyList": history_data[-15:],
+    })
+    predicted_result = next(iter(deal_request_exception(response).get("predicted", [{}])), {})
+    return {"flag": True, "data": predicted_result.get("value")}
 
 @mcp.tool()
 def get_air_pm_10_month_focus(customer_id: int) -> Any: