zhaoxi
209ba45477
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>
43 lines
1.7 KiB
Python
43 lines
1.7 KiB
Python
# Copyright 2026 zhaoxi826
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
from typing import Type, TypeVar
|
|
from pydantic import BaseModel
|
|
|
|
T = TypeVar("T", bound=Type[BaseModel])
|
|
|
|
|
|
def pickle(cls: T) -> T:
|
|
"""
|
|
类装饰器pickle
|
|
通过装饰继承了BaseModel的类，用pydantic的高效序列化替代python原生__reduce__魔术方法,实现ray在通讯时的高效序列化
|
|
Args:
|
|
cls: 继承了BaseModel类的类，需要被装饰的对象
|
|
|
|
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。"""
|
|
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
|