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* ♻️ refactor(core): 重构 AI 能力与定时任务调度系统 - 【AI 能力与工具】重构 Capability 注册与管理机制,引入 CapabilityManager 统一管理 - 移除全局能力注册表,改用声明式装饰器 `@capability` 进行解耦注册 - 重构工具解析器链,使用统一的 BaseToolResolver 代替原有的多个特定解析器 - 增强工具查询过滤,支持通配符匹配、工具箱过滤和排除标签 - 【定时任务调度】重构定时任务管理器,引入 SchedulerRegistry 统一管理任务元数据 - 引入 JobConfig 聚合定时任务配置,支持用户维度的定时任务调度 - 重构执行分发器,支持并发限制、串行间隔和随机延迟打散 - 【运行上下文】引入 ScheduledDeps 以支持后台和定时任务环境下的依赖注入 - 优化 RunContext,支持从定时任务上下文快速构造,并提供 emit 辅助方法 - 【日志与监控】引入 AILoggerProxy,实现 AI 各模块的专属日志输出 - 将各模块的全局 logger 替换为对应的模块专属日志代理 - 【其他优化】修复 Pydantic V1 兼容层中 model_validator 的装饰器兼容性问题 - 在非交互式环境(如定时任务)中自动隐藏 HITL 交互工具以节省 Token * ♻️ refactor(core): 优化内部导入路径并提升 Pydantic 兼容性 - 【重构】将 `services/ai` 模块内的绝对导入重构为相对导入,优化包结构 - 【重构】移除不必要的 `if TYPE_CHECKING` 保护,通过 `from __future__ import annotations` 直接导入类型 - 【清理】清理 `core/messages/types.py` 中未使用的 `AssistantContentUnion` 等联合类型定义 - 【优化】在 `utils/pydantic_compat.py` 中新增 `model_rebuild` 兼容函数,统一 Pydantic V1/V2 的模型重建逻辑 - 【优化】将部分函数内部的延迟导入提升至模块顶部,规范代码结构 * ♻️ refactor(imports): 优化导入路径为相对导入并清理冗余导入 - 【重构】将 AI 服务相关模块中的绝对导入路径修改为相对导入,提升模块内聚性与可移植性 - 【清理】移除多处函数内部或类方法中未使用的冗余导入,避免循环引用和资源浪费 - 【格式化】微调部分工具装饰器和返回语句的格式与尾随逗号 * 🚨 auto fix by pre-commit hooks --------- Co-authored-by: webjoin111 <455457521@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
190 lines
5.2 KiB
Python
190 lines
5.2 KiB
Python
from abc import ABC, abstractmethod
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from collections.abc import Awaitable, Callable
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from contextlib import AbstractAsyncContextManager
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any, Protocol, runtime_checkable
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from .models import SandboxExecutionResult
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class InteractiveTerminalSession(Protocol):
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@abstractmethod
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async def start(self, cmd: str, env: dict[str, str] | None = None) -> None:
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"""启动并挂载终端会话"""
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...
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@abstractmethod
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async def send_input(self, text: str) -> None:
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"""向终端发送标准输入"""
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...
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@abstractmethod
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async def read_output(self, timeout: int = 5) -> str:
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"""读取当前终端屏幕输出画面"""
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...
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@abstractmethod
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async def interrupt(self) -> None:
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"""发送强制中断信号(Ctrl+C)"""
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...
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@abstractmethod
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async def close(self) -> None:
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"""释放并关闭终端资源"""
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...
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@runtime_checkable
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class SupportsCommandExecution(Protocol):
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async def run_process(
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self,
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command: str | list[str],
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cwd: str | None = None,
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timeout: float | None = None,
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env: dict[str, str] | None = None,
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on_output: Callable[[str, bytes], Awaitable[None]] | None = None,
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) -> SandboxExecutionResult:
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"""在沙箱内单次执行短命令并获取结果"""
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...
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@runtime_checkable
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class SandboxProcessStream(Protocol):
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@abstractmethod
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async def read(self) -> "ProcessStreamMessage | None":
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"""异步读取下一块输出流数据"""
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...
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@abstractmethod
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async def write(self, data: bytes) -> None:
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"""异步写入数据到进程标准输入"""
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...
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@abstractmethod
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async def close(self) -> None:
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"""关闭并终止输入输出流"""
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...
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@runtime_checkable
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class SupportsStreamExecution(Protocol):
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@abstractmethod
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def create_stream_process(
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self,
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command: str | list[str],
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cwd: str | None = None,
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env: dict[str, str] | None = None,
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) -> AbstractAsyncContextManager[SandboxProcessStream]:
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"""创建持久流式后台进程,供长连接通信"""
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...
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@runtime_checkable
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class SupportsInteractivePTY(Protocol):
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async def create_pty_session(self) -> InteractiveTerminalSession:
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"""创建分配一个真实的伪终端(PTY)交互会话"""
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...
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@runtime_checkable
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class SupportsFileSystem(Protocol):
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async def write_raw_file(self, path: str | Path, content: str) -> bool:
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"""使用字符串极速覆写文件"""
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...
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async def read_raw_file(self, path: str | Path) -> str:
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"""直接读取文件内容为文本字符串"""
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...
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async def delete_raw_file(self, path: str | Path) -> bool:
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"""直接删除指定物理文件"""
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...
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async def upload_raw_dir(
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self, local_dir_path: str | Path, sandbox_target_path: str | Path
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) -> bool:
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"""将宿主机本地目录完整打包上传至沙箱"""
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...
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async def write(self, path: str | Path, data: bytes) -> bool:
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"""底层二进制安全写入文件"""
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...
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async def read(self, path: str | Path) -> bytes:
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"""底层二进制安全读取文件"""
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...
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async def rm(self, path: str | Path, recursive: bool = False) -> bool:
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"""执行标准的 rm 删除操作"""
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...
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async def mkdir(self, path: str | Path, parents: bool = False) -> bool:
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"""执行标准的 mkdir 创建目录操作"""
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...
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@runtime_checkable
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class SupportsPortMapping(Protocol):
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def get_meta(self, key: str, default: Any = None) -> Any:
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"""获取沙箱驱动映射的底层元数据(如分配的随机端口)"""
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...
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class SandboxChannel(ABC):
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@abstractmethod
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def get_meta(self, key: str, default: Any = None) -> Any:
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"""获取沙箱会话的底层元数据字典"""
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...
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class StatefulCodeClient(Protocol):
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"""有状态代码执行客户端通信协议"""
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@abstractmethod
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async def execute(
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self,
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code: str,
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timeout: int = 30,
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on_output: Callable[[str, bytes], Awaitable[None]] | None = None,
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) -> SandboxExecutionResult:
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"""执行指定代码并获取结果"""
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...
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@abstractmethod
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async def interrupt(self) -> None:
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"""发送强制中断信号(模拟Ctrl+C)"""
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...
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@abstractmethod
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async def close(self) -> None:
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"""关闭底层网络及进程连接"""
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...
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class BaseEngineManager(Protocol):
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"""沙箱后台引擎生命周期管理器协议"""
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@abstractmethod
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async def ensure_started(self, env_vars: dict[str, str] | None = None) -> None:
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"""确保后台引擎主服务已在沙箱中成功启动"""
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...
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@abstractmethod
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async def get_client(self, kernel_name: str) -> StatefulCodeClient:
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"""分配并获取指定语言内核的通信客户端"""
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...
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@abstractmethod
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async def close(self) -> None:
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"""安全关闭引擎并回收所有分配的客户端资源"""
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...
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@dataclass
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class ProcessStreamMessage:
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"""统一的进程流消息载体"""
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stream_type: int
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data: bytes
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