import asyncio
import ray
from pretor.worker_individual.worker_cluster import WorkerCluster
from pretor.utils.banner import print_banner
from pretor.core.database.postgres import PostgresDatabase
from pretor.core.global_state_machine.global_state_machine import GlobalStateMachine
from pretor.core.individual.supervisory_node.supervisory_node import SupervisoryNode
from pretor.core.individual.consciousness_node.consciousness_node import ConsciousnessNode
from pretor.core.individual.control_node.control_node import ControlNode
from pretor.core.workflow.workflow_runner import WorkflowRunningEngine
from pretor.core.api import PretorGateway
from ray import serve
import os



async def start_system():
    env_vars = {
        "POSTGRES_USER": os.getenv("POSTGRES_USER", "postgres"),
        "POSTGRES_PASSWORD": os.getenv("POSTGRES_PASSWORD", ""),
        "POSTGRES_HOST": os.getenv("POSTGRES_HOST", "db"),
        "POSTGRES_PORT": os.getenv("POSTGRES_PORT", "5432"),
        "POSTGRES_DB": os.getenv("POSTGRES_DB", "postgres"),
        "SECRET_KEY": os.getenv("SECRET_KEY", "secret"),
    }

    ray.init(ignore_reinit_error=True,
             namespace="pretor",
             dashboard_host="0.0.0.0",
             dashboard_port=8265,
             runtime_env={"env_vars": env_vars})


    # 2. 启动数据库组件
    postgres_database = PostgresDatabase.options(name='postgres_database').remote()
    await postgres_database.init_db.remote()

    global_state_machine = GlobalStateMachine.options(
        name='global_state_machine',
        namespace='pretor',
        lifetime='detached'
    ).remote(postgres_database)

    print("正在等待 GlobalStateMachine 初始化并加载注册表...")
    try:
        # 强制执行初始化方法并阻塞等待结果。
        # 如果 __init__ 或 init_state_machine 中有任何报错，会立刻在这里抛出！
        await global_state_machine.init_state_machine.remote()
        print("GlobalStateMachine 初始化成功！")
    except Exception as e:
        print(f"\n[致命错误] GlobalStateMachine 启动失败！真实报错如下：\n{e}\n")
        return

    # 4. 启动核心节点
    supervisory_node = SupervisoryNode.options(name='supervisory_node').remote()
    consciousness_node = ConsciousnessNode.options(name='consciousness_node').remote()
    control_node = ControlNode.options(name='control_node').remote()

    try:
        worker_cluster_actor = WorkerCluster.options(
            name="worker_cluster",
            lifetime="detached"  # 保证它在后台一直运行
        ).remote()
        print("✅ WorkerCluster 已成功启动并注册！")
    except ValueError:
        print("WorkerCluster 已经存在。")
    # 5. 启动工作流运行引擎
    workflow_engine = WorkflowRunningEngine.options(name='workflow_running_engine').remote(
        consciousness_node=consciousness_node,
        control_node=control_node,
        supervisory_node=supervisory_node
    )
    # 异步拉起 runner 协程群
    workflow_engine.run.remote()

    # 6. 启动 FastAPI 网关 (使用 Ray Serve)
    serve.start(http_options={"host": "0.0.0.0", "port": 8000})
    serve.run(PretorGateway.bind())

    # 挂起主线程以保持系统运行
    while True:
        await asyncio.sleep(3600)


def main():
    print_banner()
    try:
        asyncio.run(start_system())
    except KeyboardInterrupt:
        print("系统已退出。")


if __name__ == '__main__':
    main()