refactor(core): decouple actors and remove workflow templates (#67)

Removes the deprecated `workflow_template` concept entirely across both backend API routers, internal logic handling within the `supervisory_node` and `consciousness_node`, and front-end components. Enables `consciousness_node` to work autonomously.

Also refactors core package structure to enforce the "one python package, one Ray Actor" architectural rule. `GlobalWorkflowManager`, `WorkflowRunningEngine`, `PostgresDatabase`, and `WorkerCluster` have been moved to their own top-level decoupled package directories with properly exported `__init__.py` modules. Test suites have been relocated and import paths updated across the system.

Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

main.py

@@ -1,14 +1,14 @@
 import asyncio
 import ray
-from pretor.worker_individual.worker_cluster import WorkerCluster
+from pretor.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.global_state_machine.global_workflow_manager import GlobalWorkflowManager
-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.postgres_database import PostgresDatabase
+from pretor.core.global_state_machine import GlobalStateMachine
+from pretor.core.global_workflow_manager import GlobalWorkflowManager
+from pretor.core.individual.supervisory_node import SupervisoryNode
+from pretor.core.individual.consciousness_node import ConsciousnessNode
+from pretor.core.individual.control_node import ControlNode
+from pretor.core.workflow_running_engine import WorkflowRunningEngine
 from pretor.api import PretorGateway
 from ray import serve
 import os
@@ -18,7 +18,10 @@ _secret_key = os.getenv("SECRET_KEY")
 if not _secret_key or _secret_key in {"secret", "114514"}:
     _secret_key = secrets.token_urlsafe(32)
     os.environ["SECRET_KEY"] = _secret_key
-    print("⚠️ 警告: 未提供有效的 SECRET_KEY 或使用了不安全的默认值，已生成并设置随机密钥。")
+    print(
+        "⚠️ 警告: 未提供有效的 SECRET_KEY 或使用了不安全的默认值，已生成并设置随机密钥。"
+    )
+
 
 async def start_system():
     env_vars = {
@@ -30,21 +33,20 @@ async def start_system():
         "SECRET_KEY": os.getenv("SECRET_KEY"),
     }
 
-    ray.init(ignore_reinit_error=True,
-             namespace="pretor",
-             dashboard_host="0.0.0.0",
-             dashboard_port=8265,
-             runtime_env={"env_vars": env_vars})
-
+    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()
+    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'
+        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...")
@@ -58,29 +60,29 @@ async def start_system():
         return
 
     global_workflow_manager = GlobalWorkflowManager.options(
-        name='global_workflow_manager',
-        namespace='pretor',
-        lifetime='detached'
+        name="global_workflow_manager", namespace="pretor", lifetime="detached"
     ).remote()
 
     # 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()
+    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:
         WorkerCluster.options(
             name="worker_cluster",
-            lifetime="detached"  # 保证它在后台一直运行
+            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(
+    workflow_engine = WorkflowRunningEngine.options(
+        name="workflow_running_engine"
+    ).remote(
         consciousness_node=consciousness_node,
         control_node=control_node,
-        supervisory_node=supervisory_node
+        supervisory_node=supervisory_node,
     )
     # 异步拉起 runner 协程群
     workflow_engine.run.remote()
@@ -110,5 +112,5 @@ def main():
         print("系统已退出。")
 
 
-if __name__ == '__main__':
-    main()
+if __name__ == "__main__":
+    main()