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✨ feat!(llm): 重构并升级大语言模型服务为全新 AI 智能体框架 (#2146)
* ✨ feat!(llm): 重构并升级大语言模型服务为全新 AI 智能体框架 - 【重构】将原 services/llm 重构并迁移至全新的 services/ai 架构，提供向下兼容垫片 - 【新增】引入 Agent、Team、Workflow 三大智能体与工作流编排范式 - 【新增】引入基于 RAG 的长期向量记忆与中期槽位记忆系统 - 【新增】引入基于 Docker 的安全代码执行沙箱环境 - 【新增】支持 MCP 协议，允许动态管理和调用 MCP 服务 - 【新增】引入输入输出安全合规护栏与自愈反思机制 - 【优化】重构并优化多厂商 API 适配器 (Gemini, OpenAI, DeepSeek, GLM 等) - 【优化】优化日志脱敏与 Token 预估机制 - 【移除】移除旧版 llm default 和 llm reset-key 命令，新增 llm mcp 管理命令 * 🔧 chore(deps): 更新项目依赖与配置 - 添加 mcp、jieba 和 aiodocker 依赖到配置文件及 requirements.txt - 在 pyright 配置中设置 reportMissingImports 为 none - 调整 .gitignore 中 resources 目录的忽略规则 * ♻️ refactor(tools): 重构工具终止机制并清理知识库日志输出 - 统一使用 `context.state["__end_run__"]` 替代 `EndRunResult` 控制任务结束 - 移除文件系统和向量知识库检索工具中 `ToolResult` 的 `.with_log` 调用 - 调整指令处理器（Directive）的返回值为 `tool_res.output` - 修复部分类型检查警告并优化联合类型判断语法 * ♻️ refactor(tools): 重构工具副作用指令与控制流熔断机制 - 引入 `DirectivePayload` 及 `ToolResult` 的子类以结构化表达工具副作用 - 移除通过 `context.state` 传递魔术变量的隐式控制流设计 - 重构 `DirectiveManager` 处理器接口，直接在处理器中修改 `AgentState` 并构建 `AgentRunResult` - 在 `StandardAgentExecutor` 中统一通过 `directive_manager` 调度工具返回的副作用指令 - 补全 `MessageBuilder` 中部分核心方法的文档注释 * 🐛 fix(sandbox): 修复 Docker 沙箱容器状态检测与会话清理逻辑 -【修复】修正 `is_alive` 中直接读取私有属性的问题，改用 `show()` 返回值 -【修复】解决 `execute_code` 中缓存的执行器与当前会话不一致的问题 -【优化】在清理工作区前增加容器存活检测，避免向已死容器发送请求 -【优化】创建容器时增加运行状态校验，若已停止则自动从缓存中移除并重建 -【优化】优化容器销毁和清理逻辑，静默处理容器不存在 (404) 的异常 * 📝 docs(core): 补充核心模块初始化方法的文档注释 * 🚨 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>
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parent
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commit
80fc5b86a7
@@ -0,0 +1,189 @@
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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 zhenxun.services.ai.sandbox.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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