chore: initial commit for Pretor v0.1.0-alpha

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。

pretor/utils/pickle.py

@@ -0,0 +1,37 @@
+#  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
+