zhaoxi
a53ffebe0e
1. 新增工具插件(edit_file, python_executor, search_file, shell_executor, write_file) 2. 新增系统事件日志模块和API 3. 新增workflow配置文件和详情API 4. 前端增加SSE、错误边界、设置引导等组件 5. 优化认证加密、速率限制、配置加载等工具模块 6. 删除废弃的cluster和health API 7. 补充单元测试和集成测试 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
105 lines
3.8 KiB
Python
105 lines
3.8 KiB
Python
# Copyright 2026 zhaoxi826
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import time
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import ray
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from functools import lru_cache
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class ActorList:
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"""属性式访问的简易容器，用 ``a.actor_name`` 取代 ``d["actor_name"]``。"""
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def __init__(self):
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super().__setattr__("dict", {})
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def __setattr__(self, key, value):
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self.dict[key] = value
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def __getattr__(self, key):
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if key in self.dict:
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return self.dict[key]
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raise AttributeError(f"ActorList 对象没有属性 '{key}'")
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def __delattr__(self, key):
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if key in self.dict:
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del self.dict[key]
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else:
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raise AttributeError(f"ActorList对象没有属性 '{key}'")
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@lru_cache(maxsize=128)
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def _get_cached_actor_handle(actor_name: str):
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"""缓存接口"""
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return ray.get_actor(actor_name, namespace="kilostar")
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def clear_actor_cache():
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"""清理接口"""
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_get_cached_actor_handle.cache_clear()
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def wait_for_actor(
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actor_name: str, *, timeout: float = 10.0, interval: float = 0.5
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):
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"""阻塞等待某个 actor 就绪，返回其句柄。
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用于"启动期 / ray task 入口刚拉起"这类场景——被依赖的 actor 可能还没注册。
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在 ``timeout`` 内按 ``interval`` 轮询 ``ray.get_actor``；拿到就立即返回，
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超时则抛带清晰上下文的 ``TimeoutError``（而不是裸 ``ValueError``）。
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Args:
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actor_name: actor 注册名
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timeout: 最长等待秒数；``<=0`` 表示只试一次（等价于直接取句柄）
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interval: 轮询间隔秒数
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Raises:
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TimeoutError: 超时仍未就绪。原始异常通过 ``raise ... from`` 链保留。
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"""
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deadline = time.monotonic() + max(timeout, 0.0)
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last_err: Exception | None = None
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while True:
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try:
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return _get_cached_actor_handle(actor_name)
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except Exception as e: # ray.get_actor 失败一般是 ValueError
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last_err = e
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# 失败不能让 lru_cache 留下脏数据（异常本身不会被缓存，
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# 但若底层换实现，这里清一次更稳妥）
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if time.monotonic() >= deadline:
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raise TimeoutError(
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f"等待 actor {actor_name!r} 就绪超时（{timeout}s）：{last_err}"
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) from last_err
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time.sleep(interval)
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def ray_actor_hook(*actor_names: str, timeout: float = 0.0, interval: float = 0.5):
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"""按名字批量取出 Ray Actor 句柄，组装成一个 ``ActorList`` 返回。
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例：``actors = ray_actor_hook("postgres_database", "global_state_machine")``，
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随后即可用 ``actors.postgres_database`` 拿到对应句柄。
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Args:
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timeout: ``>0`` 时对每个 actor 走 ``wait_for_actor`` 等待就绪（启动期用）；
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缺省 ``0`` 保持原"快速失败"语义——actor 不在立即抛异常。
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interval: 等待轮询间隔，仅在 ``timeout>0`` 时生效。
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"""
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actor_list = ActorList()
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for actor_name in actor_names:
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if timeout > 0:
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handle = wait_for_actor(
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actor_name, timeout=timeout, interval=interval
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)
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else:
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handle = _get_cached_actor_handle(actor_name)
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setattr(actor_list, actor_name, handle)
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return actor_list
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