zhaoxi
d84212f780
正式发布 Pretor 平台的首个 alpha 版本。本项目旨在构建一个基于分布式架构的多智能体协同工作流水线。 核心功能实现： 1. 建立基于 BaseIndividual 的动态插件加载机制。 2. 实现三类核心 worker_individual 子个体。 3. 集成 Ray 框架支持分布式集群调度。 4. 基于 PostgreSQL 的全量持久化存储方案。 5. 提供完整的 FastAPI 后端与 React 前端交互界面。
38 lines
1.3 KiB
Python
38 lines
1.3 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
|
|
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
|
|
|