"""Temporal worker 启动入口。

可以把 worker 理解成 Temporal 的“执行器进程”：
它负责监听 task queue，然后真正执行 workflow / activity。
"""

import asyncio
from contextlib import AsyncExitStack

from temporalio.client import Client
from temporalio.worker import Worker

from app.infra.temporal.client import get_temporal_client
from app.infra.temporal.task_queues import (
    IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
    IMAGE_PIPELINE_EXPORT_TASK_QUEUE,
    IMAGE_PIPELINE_IMAGE_GEN_TASK_QUEUE,
    IMAGE_PIPELINE_POST_PROCESS_TASK_QUEUE,
    IMAGE_PIPELINE_QC_TASK_QUEUE,
)
from app.workers.activities.export_activities import run_export_activity
from app.workers.activities.face_activities import run_face_activity
from app.workers.activities.fusion_activities import run_fusion_activity
from app.workers.activities.qc_activities import run_qc_activity
from app.workers.activities.review_activities import (
    complete_review_wait_activity,
    mark_waiting_for_review_activity,
    mark_workflow_failed_activity,
)
from app.workers.activities.scene_activities import run_scene_activity
from app.workers.activities.texture_activities import run_texture_activity
from app.workers.activities.tryon_activities import prepare_model_activity, run_tryon_activity
from app.workers.workflows.low_end_pipeline import LowEndPipelineWorkflow
from app.workers.workflows.mid_end_pipeline import MidEndPipelineWorkflow


def build_workers(client: Client) -> list[Worker]:
    """创建本项目需要的 worker 集合。

    这里按 task queue 拆 worker，目的是把不同类型的任务分开：
    - control: 流程控制、review、失败收尾
    - image-gen: tryon / scene
    - post-process: texture / face / fusion
    - qc: 质检
    - export: 导出
    """

    return [
        # control 队列负责 workflow 本体，以及少量“流程状态管理型” activity。
        Worker(
            client,
            task_queue=IMAGE_PIPELINE_CONTROL_TASK_QUEUE,
            workflows=[LowEndPipelineWorkflow, MidEndPipelineWorkflow],
            activities=[
                prepare_model_activity,
                mark_waiting_for_review_activity,
                complete_review_wait_activity,
                mark_workflow_failed_activity,
            ],
        ),
        # image-gen 队列放生成类步骤，便于后续横向扩容。
        Worker(
            client,
            task_queue=IMAGE_PIPELINE_IMAGE_GEN_TASK_QUEUE,
            activities=[run_tryon_activity, run_scene_activity],
        ),
        # post-process 队列放增强/融合类步骤。
        Worker(
            client,
            task_queue=IMAGE_PIPELINE_POST_PROCESS_TASK_QUEUE,
            activities=[run_texture_activity, run_face_activity, run_fusion_activity],
        ),
        Worker(
            client,
            task_queue=IMAGE_PIPELINE_QC_TASK_QUEUE,
            activities=[run_qc_activity],
        ),
        Worker(
            client,
            task_queue=IMAGE_PIPELINE_EXPORT_TASK_QUEUE,
            activities=[run_export_activity],
        ),
    ]


async def run_workers() -> None:
    """启动全部 worker，并保持进程常驻。"""

    client = await get_temporal_client()
    workers = build_workers(client)
    async with AsyncExitStack() as stack:
        for worker in workers:
            # 逐个把 worker 注册到上下文里，退出时会自动优雅关闭。
            await stack.enter_async_context(worker)
        # 用一个永不触发的 Event 让进程保持存活。
        await asyncio.Event().wait()


if __name__ == "__main__":
    asyncio.run(run_workers())