# 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}")