完善牧安云哨-后端

bbit_ai/app/service/RabbitMQ.py

@@ -0,0 +1,98 @@
+# consumer.py
+import asyncio
+import json
+
+import aio_pika
+
+from config.rabbitMQ import *
+from models.AnalysisRequest import AnalysisRequest
+from models.SentinelRecordRequest import SentinelRecordRequest
+from service.vision import process_vehicle_animal_image
+
+
+async def mq_new_analysis_test(req: dict):
+    """将分析请求发送到 RabbitMQ 队列（异步版）"""
+    connection = await aio_pika.connect_robust(
+        f"amqp://{RABBIT_USER}:{RABBIT_PASSWORD}@{RABBIT_HOST}/{RABBIT_VHOST}"
+    )
+
+    async with connection:
+        channel = await connection.channel()
+        # 声明队列，确保队列存在
+        queue = await channel.declare_queue(QUEUE_NAME, durable=True)
+
+        message_body = json.dumps(req)
+        message = aio_pika.Message(
+            body=message_body.encode(),
+            delivery_mode=aio_pika.DeliveryMode.PERSISTENT,  # 持久化
+        )
+
+        await channel.default_exchange.publish(message, routing_key=QUEUE_NAME)
+
+
+async def mq_pull_analysis_async_test():
+    """
+    从队列拉取分析任务并处理
+    process_func: 一个函数，接收 AnalysisRequest 对象处理分析逻辑
+    """
+    connection = await aio_pika.connect_robust(
+        f"amqp://{RABBIT_USER}:{RABBIT_PASSWORD}@{RABBIT_HOST}/{RABBIT_VHOST}"
+    )
+    async with connection:
+        queue_name = QUEUE_NAME
+        channel = await connection.channel()
+        await channel.set_qos(prefetch_count=1)
+        queue = await channel.declare_queue(queue_name, durable=True)
+
+        async with queue.iterator() as queue_iter:
+            async for message in queue_iter:
+                async with message.process():
+                    data = json.loads(message.body)
+                    req = AnalysisRequest(**data)
+                    print(f"收到任务: {req}")
+                    await asyncio.sleep(5)  # 模拟处理
+                    print(f"完成任务: {req}")
+
+
+async def sentinel_new_analysis(req: SentinelRecordRequest):
+    """将分析请求发送到 RabbitMQ 队列（异步版）"""
+    connection = await aio_pika.connect_robust(
+        f"amqp://{RABBIT_USER}:{RABBIT_PASSWORD}@{RABBIT_HOST}/{SENTINEL_VHOST}"
+    )
+
+    async with connection:
+        channel = await connection.channel()
+        # 声明队列，确保队列存在
+        queue = await channel.declare_queue(QUEUE_NAME, durable=True)
+
+        message_body = json.dumps(req.model_dump())
+        message = aio_pika.Message(
+            body=message_body.encode(),
+            delivery_mode=aio_pika.DeliveryMode.PERSISTENT,  # 持久化
+        )
+
+        await channel.default_exchange.publish(message, routing_key=QUEUE_NAME)
+
+
+async def sentinel_pull_analysis_async():
+    """
+    从队列拉取分析任务并处理
+    process_func: 一个函数，接收 AnalysisRequest 对象处理分析逻辑
+    """
+    connection = await aio_pika.connect_robust(
+        f"amqp://{RABBIT_USER}:{RABBIT_PASSWORD}@{RABBIT_HOST}/{SENTINEL_VHOST}"
+    )
+    async with connection:
+        queue_name = QUEUE_NAME
+        channel = await connection.channel()
+        await channel.set_qos(prefetch_count=1)
+        queue = await channel.declare_queue(queue_name, durable=True)
+
+        async with queue.iterator() as queue_iter:
+            async for message in queue_iter:
+                async with message.process():
+                    data = json.loads(message.body)
+                    req = SentinelRecordRequest(**data)
+                    print(f"收到任务: {req}")
+                    await process_vehicle_animal_image(req)  # 处理
+                    print(f"完成任务: {req}")

bbit_ai/app/service/vision.py

@@ -4,10 +4,15 @@ from uuid import UUID
 import config.minIO as minIO
 import db.postgres as pg
 from agent.licenseImageAgent import get_license_response
+from agent.vehicleImageAgent import get_vehicle_response
 from config.minIO import minio_client
 from config.yolo import YOLOSingleton
+from db.postgres import get_dept_id_by_iot_user_name, get_dept_ids_by_dept_id
+from db.postgres.sentinel import update_sentinel_record
 from llm.ticketLLM import *
 from llm.ticketLLMv2 import get_ticket_response_v2
+from models.SentinelRecordRequest import SentinelRecordRequest
+from routers.WS import ws_manager
 
 
 def process_ticket_image(
@@ -178,3 +183,27 @@ def process_silkworm_cocoon_image(
         "postprocess_time_ms": speed_json.get("postprocess"),
         "details": results_json.get("class_counts"),
     }
+
+
+async def process_vehicle_animal_image(
+    data: SentinelRecordRequest,
+):
+    # 通过设备id获得组织id
+    dept_id = get_dept_id_by_iot_user_name(data.DeviceId)
+    # 得到动物类型
+    oss_url = minIO.get_temp_url("sentinel", "vehicle_image/" + data.VehicleImage)
+    analysis_result = await get_vehicle_response(oss_url)
+    livestock_type = analysis_result.get("livestock_type", "")
+    remark = analysis_result.get("remark", "")
+
+    available_departments = get_dept_ids_by_dept_id(dept_id)
+
+    await ws_manager.noticeSentinel(
+        {
+            "content": f"载有{livestock_type}的车辆即将进入关卡，请准备检查",
+            "type": "vehicle_alert",
+        },
+        available_departments,
+    )
+    # 保存到数据库
+    return update_sentinel_record(data.Id, livestock_type, remark, dept_id)