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>

pretor/utils/pickle.py

@@ -17,6 +17,7 @@ from pydantic import BaseModel
 
 T = TypeVar("T", bound=Type[BaseModel])
 
+
 def pickle(cls: T) -> T:
     """
     类装饰器pickle
@@ -27,14 +28,15 @@ def pickle(cls: T) -> T:
     Returns:
         返回被重写了__reduce__魔术方法的cls类
     """
+
     def __reduce__(self):
         # 1. 序列化：触发 Pydantic-core (Rust) 的极速序列化
         """执行与   reduce   相关的核心业务流转操作。
         该方法封装了具体的算法策略或状态控制逻辑，确保操作能够在事务上下文中被原子且一致地执行。
-        Returns:        : 经由当前业务模型加工处理后所输出的具体数据实例或领域模型对象。    """
+        Returns:        : 经由当前业务模型加工处理后所输出的具体数据实例或领域模型对象。"""
         data = self.model_dump_json()
         # 2. 反序列化：告诉 Pickle 重建时调用 cls.model_validate_json
         return cls.model_validate_json, (data,)
+
     cls.__reduce__ = __reduce__
     return cls
-