Files
zhenxun_bot/zhenxun/services/ai/tools/providers/mcp/toolkit.py
T
0b32d69c9c ♻️ refactor(tools): 重构工具装饰器系统并优化沙箱与文档注释 (#2147)
* ♻️ refactor(ai): 重构 AI 服务模块并完善文档注释

- 【重构】统一清理并优化所有 AI 服务模块文件的导入语句,将其移至文件顶部
- 【重构】重构 `hooks.py` 中的 `Hooks` 派发逻辑,使用通用管道函数消除重复代码,并引入 `HookPoint` 描述符
- 【重构】重构工具装饰器实现,新增 `toolkit` 类装饰器,优化 `BaseToolkit` 配置合并与前缀处理
- 【功能】Docker 沙箱容器创建时支持自动注入系统代理环境变量并配置 `ExtraHosts`
- 【功能】Jupyter 服务启动前自动清理旧进程并初始化临时目录权限
- 【修复】优化 Pydantic 结构化输出校验失败时的错误信息提取,提供更详细的字段级错误反馈
- 【修复】在 `api.py` 中避免将 `ModelRetry` 和 `ControlFlowExit` 异常错误地包装为 `LLMException`
- 【文档】为 AI 服务、沙箱、工具链、工作流等核心模块补充完整的 Docstring 和类型注释

* 📝 docs(ai): 补全核心模块文档注释并清理冗余代码

- 补全 `run/context`、`run/hooks` 和 `tools/engine/registry` 中类与方法的中文文档注释
- 清理 `tools/providers/builtin/sandbox` 中未使用的 `PythonPluginProtocol` 协议及相关导入
- 规范化部分代码的格式与尾随逗号

* ♻️ refactor!(flow): 重构 Task 为 AgentTask 并优化工作流元数据定义

- 【Breaking Change】将 `Task` 重命名为 `AgentTask` 以避免命名冲突
- 更新 Agent、Team、Workflow 等模块中的类型声明与相关逻辑
- 引入 `AutoNodeMeta` 强类型元数据,替换工作流装饰器中的裸字典定义
- 将 `StepMeta`、`ConditionMeta` 和 `RouterMeta` 统一移动至 `types.py`
- 优化 `RunnableNode` 对上游 `AgentTask` 的处理与拼接逻辑
- 调整团队协作策略中 `FinishAction` 的返回值为完整结果对象

* ♻️ refactor(workflow): 移除人工确认机制并重构错误策略

- 移除工作流节点的人工确认(HITL)与挂起继续机制
- 删除 `auto` 自动化工作流及相关装饰器文件
- 将错误处理策略类从 `types.py` 拆分并移动到新文件 `policies.py`
- 优化节点执行失败时的异常信息格式化输出
- 移除 `WorkflowRunResult` 和 `StepOutput` 中与挂起相关的状态字段

* 🚨 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>
2026-07-05 11:47:21 +08:00

647 lines
25 KiB
Python

import asyncio
import base64
from collections.abc import AsyncGenerator, Callable
from contextlib import AsyncExitStack, asynccontextmanager
import re
from typing import Any, Literal, cast
import anyio
from anyio.streams.memory import MemoryObjectReceiveStream, MemoryObjectSendStream
import httpx
from mcp import ClientSession # type: ignore
from mcp.client.sse import sse_client
from mcp.client.stdio import StdioServerParameters, stdio_client
from mcp.client.streamable_http import streamable_http_client
from mcp.shared.message import SessionMessage
from pydantic import ValidationError
from zhenxun.services.ai.core.models import ToolDefinition
from zhenxun.services.ai.core.stream_events import UserCustomEvent
from zhenxun.services.ai.run.context import RunContext
from zhenxun.services.ai.sandbox.addons.base import BaseMcpProxyExtension
from zhenxun.services.ai.sandbox.models import SandboxBlueprint
from zhenxun.services.ai.tools.core.tool import BaseTool
from zhenxun.services.ai.tools.core.toolkit import BaseToolkit
from zhenxun.services.ai.tools.models import ToolkitConfig, ToolResult
from zhenxun.services.log import logger
from zhenxun.utils.lifespan import LifespanManager
from zhenxun.utils.pydantic_compat import model_dump
_MESSAGE_START_CHARS = {"{", "["}
_LITERAL_PREFIXES: tuple[str, ...] = ("true", "false", "null")
def _should_ignore_exception(exc: Exception) -> bool:
"""
判断该异常是否是由非 JSON 的脏数据标准输出引起的。
如果是脏数据,则可以安全忽略。
"""
if not isinstance(exc, ValidationError):
return False
errors = exc.errors()
first = next(iter(errors), None)
if not first or first.get("type") != "json_invalid":
return False
input_value = first.get("input")
if not isinstance(input_value, str):
return False
stripped = input_value.strip()
if not stripped:
return True
first_char = stripped[0]
lowered = stripped.lower()
if first_char in _MESSAGE_START_CHARS or any(
lowered.startswith(prefix) for prefix in _LITERAL_PREFIXES
):
return False
return True
@asynccontextmanager
async def filtered_stdio_client(
server_name: str, server: StdioServerParameters
) -> AsyncGenerator[
tuple[
MemoryObjectReceiveStream[SessionMessage | Exception],
MemoryObjectSendStream[SessionMessage],
],
None,
]:
"""
包裹官方的 stdio_client,拦截并过滤掉非 JSON 格式的标准输出噪音。
"""
async with stdio_client(server=server) as (read_stream, write_stream):
filtered_send, filtered_recv = anyio.create_memory_object_stream[
SessionMessage | Exception
](0)
async def _forward_stdout() -> None:
try:
async with read_stream:
async for item in read_stream:
if isinstance(item, Exception) and _should_ignore_exception(
item
):
if isinstance(item, ValidationError):
err_input = item.errors()[0].get("input", "")
logger.debug(
f"🔇 [MCP Stdout Filter] {server_name} 忽略脏数据: "
f"{str(err_input)[:100].strip()}..."
)
continue
await filtered_send.send(item)
except anyio.ClosedResourceError:
pass
finally:
await filtered_send.aclose()
async with anyio.create_task_group() as tg:
tg.start_soon(_forward_stdout)
try:
yield filtered_recv, write_stream
finally:
tg.cancel_scope.cancel()
class MCPRemoteTool(BaseTool):
"""远端 MCP 工具在本地的代理对象"""
def __init__(
self,
name: str,
original_tool_name: str,
description: str,
parameters: dict,
toolkit: "MCPToolkit",
):
"""
初始化远端 MCP 工具在本地的代理对象。
参数:
name: 工具在本地注册的唯一标识名称。
original_tool_name: 该工具在远端 MCP 服务器上的原始名称。
description: 工具的描述信息,用于指导大模型选用此工具。
parameters: 工具参数的 JSON 模式描述。
toolkit: 所属的 MCPToolkit 工具箱实例。
"""
super().__init__(name=name, description=description)
self.original_tool_name = original_tool_name
self.parameters = parameters
self.toolkit = toolkit
self.parent_toolkit = toolkit
self.args_schema = None
self.metadata = (
{"admin_level": toolkit.admin_level} if toolkit.admin_level > 0 else {}
)
@property
def effective_ttl(self) -> float:
"""获取当前工具关联的有效生存期 TTL"""
try:
from zhenxun.services.ai.config import get_llm_config
mcp_ttl = get_llm_config().agent_settings.mcp_cleanup_timeout
return 31536000.0 if mcp_ttl <= 0 else float(mcp_ttl)
except Exception:
return 31536000.0 if self.toolkit.ttl <= 0 else float(self.toolkit.ttl)
async def get_definition(
self, context: RunContext | None = None
) -> ToolDefinition | None:
if hasattr(self, "_dynamic_def") and self._dynamic_def is not None:
return self._dynamic_def
tool_def = ToolDefinition(
name=self.name,
description=self.description,
parameters=self.parameters,
metadata=self.metadata or {},
)
if context and self.settings.capabilities:
from zhenxun.services.ai.capabilities import (
CombinedCapability,
)
combined_cap = CombinedCapability(self.settings.capabilities)
defs = await combined_cap.prepare_tools(context, [tool_def])
if not defs:
return None
tool_def = defs[0]
return tool_def
async def execute(self, context: RunContext | None = None, **kwargs) -> ToolResult:
max_retries = 3
last_error = None
for attempt in range(max_retries):
await self.toolkit.lifespan_manager.touch(
self.toolkit.server_name, self.toolkit.effective_ttl
)
session = await self.toolkit.get_session(context)
if not session:
return ToolResult(output="MCP 连接错误").as_error()
try:
result = await session.call_tool(self.original_tool_name, kwargs)
break
except Exception as e:
last_error = e
logger.warning(
f"MCP 工具 '{self.name}' 执行失败 "
f"(尝试 {attempt + 1}/{max_retries}): {e}。"
"正在尝试自动重连自愈..."
)
if attempt < max_retries - 1:
await self.toolkit.close()
await asyncio.sleep(2**attempt)
else:
logger.error(
f"MCP 工具 '{self.name}' "
f"在重试 {max_retries} 次后仍然执行失败: {last_error}"
)
return ToolResult(output=f"MCP 错误: {last_error}").as_error()
if result.isError:
return ToolResult(output=str(result.content)).as_error()
from zhenxun.services.ai.core.messages import ImagePart, TextPart
output_content = []
img_count = 0
for item in result.content:
item_type = getattr(item, "type", "text")
if item_type == "image":
b64_data = getattr(item, "data", "")
mime_type = getattr(item, "mimeType", "image/png")
if b64_data:
try:
img_bytes = base64.b64decode(b64_data)
output_content.append(
ImagePart(raw=img_bytes, mime_type=mime_type)
)
img_count += 1
continue
except Exception as e:
logger.warning(f"MCP 图片 Base64 解码失败: {e}")
output_content.append(TextPart(text="[图片解码失败]"))
elif item_type == "text":
text = getattr(item, "text", str(item))
output_content.append(TextPart(text=text))
md_images = re.findall(r"!\[.*?\]\((https?://[^\)]+)\)", text)
for img_url in md_images:
output_content.append(ImagePart(url=img_url))
img_count += 1
else:
dumped = model_dump(item) if hasattr(item, "model_dump") else str(item)
output_content.append(TextPart(text=str(dumped)))
tool_result = ToolResult(output=output_content)
logger.info(
f"获取到 {len(output_content)} 条返回数据,提取了 {img_count} 张图片"
)
if img_count > 0 and context and context.run.event_bus:
await context.run.event_bus.emit(UserCustomEvent(display=output_content))
return tool_result
class MCPToolkit(BaseToolkit):
"""模型上下文协议 (MCP) 的工具箱封装 (支持声明式挂载与动态隔离)"""
def __init__(
self,
server_name: str,
prefix: str | None = None,
transport: Literal[
"stdio", "sse", "streamable-http", "sandbox_proxy"
] = "stdio",
command: str | None = None,
args: list[str] | None = None,
url: str | None = None,
env: dict | None = None,
cwd: str | None = None,
install_command: str | None = None,
isolation: Literal["shared", "per_session"] = "shared",
timeout: int = 30,
admin_level: int = 0,
header_provider: Callable[[RunContext], dict[str, str]] | None = None,
env_provider: Callable[[RunContext], dict[str, str]] | None = None,
ttl: int = 600,
sandbox_session_id: str | None = None,
sandbox_blueprint: SandboxBlueprint | None = None,
):
"""
初始化模型上下文协议 (MCP) 的工具箱封装。
参数:
server_name: MCP 服务器的唯一标识名称。
prefix: 工具名称的前缀,防止工具命名冲突。
transport: 连接 MCP 服务器的通信传输协议,可选 "stdio", "sse", "streamable-http", "sandbox_proxy"。
command: 用于 stdio 或 sandbox_proxy 模式启动服务器的可执行命令。
args: 启动服务器时附加的命令行参数。
url: 用于 sse 或 streamable-http 模式的服务器连接 URL。
env: 启动服务器时的进程环境变量。
cwd: 启动服务器时的进程工作目录。
install_command: 首次启动前执行的环境热装配/依赖安装命令。
isolation: 环境隔离模式,可选 "shared" (共享模式) 或 "per_session" (每个会话独立)。
timeout: 初始化和请求网络接口时的超时秒数,默认 30。
admin_level: 调用工具所需的管理权限等级,默认 0 (无限制)。
header_provider: 动态生成 HTTP 头部信息的工厂函数。
env_provider: 动态生成进程环境变量的工厂函数。
ttl: 闲置清理的生存时间 (秒),默认 600。
sandbox_session_id: 当 transport 为 sandbox_proxy 时指定的沙箱会话 ID。
sandbox_blueprint: 用于沙箱自动装配的环境蓝图配置。
""" # noqa: E501
super().__init__(
config=ToolkitConfig(prefix=prefix) if prefix is not None else None
)
self.server_name = server_name
self.transport = transport
self.command = command
self.args = args or []
self.url = url
self.env = env or {}
self.cwd = cwd
self.install_command = install_command
self.timeout = timeout
self.admin_level = admin_level
self.header_provider = header_provider
self.env_provider = env_provider
self.sandbox_session_id = sandbox_session_id
self.sandbox_blueprint = sandbox_blueprint
self.ttl = ttl
self._shared_session: ClientSession | None = None
self._tools: list[BaseTool] = []
self._is_initialized = False
self.lifespan_manager = LifespanManager()
self._shared_task: asyncio.Task | None = None
self._stop_event: asyncio.Event = asyncio.Event()
self._ready_event: asyncio.Event = asyncio.Event()
self._init_exception: Exception | None = None
@property
def effective_ttl(self) -> float:
"""获取当前工具箱的有效闲置生存期 TTL"""
try:
from zhenxun.services.ai.config import get_llm_config
mcp_ttl = get_llm_config().agent_settings.mcp_cleanup_timeout
return 31536000.0 if mcp_ttl <= 0 else float(mcp_ttl)
except Exception:
return 31536000.0 if self.ttl <= 0 else float(self.ttl)
async def _run_install_command(self, force: bool = False):
"""在本地运行预热依赖安装命令以准备 MCP 服务器环境"""
if not self.install_command or not self.cwd:
return
from pathlib import Path
marker_file = Path(self.cwd) / ".zx_installed"
heuristic_missing = False
if (
"npm" in self.install_command
and not (Path(self.cwd) / "node_modules").exists()
):
heuristic_missing = True
if not force and not heuristic_missing and marker_file.exists():
return
reason = "强制触发自愈重装" if force else "首次启动或检测到环境缺失"
logger.info(
f"🔧 [{self.server_name}] {reason},正在执行: `{self.install_command}` ..."
)
try:
proc = await asyncio.create_subprocess_shell(
self.install_command,
cwd=self.cwd,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await proc.communicate()
if proc.returncode != 0:
err_msg = (
stderr.decode("utf-8", errors="ignore")
if stderr
else stdout.decode("utf-8", errors="ignore")
)
logger.error(
f"❌ [{self.server_name}] 环境安装失败!\n错误输出:\n{err_msg}"
)
raise RuntimeError(f"安装命令执行失败: {self.install_command}")
else:
marker_file.touch()
logger.info(f"✅ [{self.server_name}] 环境装配成功!")
except Exception as e:
logger.error(f"执行预热安装异常: {e}")
raise e
async def get_session(
self, context: RunContext | None = None
) -> ClientSession | None:
"""获取或建立与 MCP 服务器的会话连接,并刷新其生存状态"""
await self.lifespan_manager.register(
self.server_name,
ttl=self.effective_ttl,
cleanup_callback=self.release_resource,
)
if not self._is_initialized:
await self.initialize(context)
return self._shared_session
async def _spawn_session_task(self, dynamic_headers: dict, dynamic_env: dict):
"""在后台异步拉起 MCP 传输协议通道并进行服务初始化"""
max_attempts = 2 if (self.transport == "stdio" and self.install_command) else 1
try:
for attempt in range(1, max_attempts + 1):
try:
if self.transport == "stdio":
await self._run_install_command(force=(attempt > 1))
async with AsyncExitStack() as stack:
read_stream: Any = None
write_stream: Any = None
if self.transport == "stdio":
if not self.command:
raise ValueError("stdio requires 'command'")
params = StdioServerParameters(
command=self.command,
args=self.args,
env=dynamic_env,
cwd=self.cwd,
)
transport_ctx = filtered_stdio_client(
self.server_name, params
)
elif self.transport == "sse":
if not self.url:
raise ValueError("sse requires 'url'")
transport_ctx = sse_client(
url=self.url,
headers=dynamic_headers,
timeout=self.timeout,
)
elif self.transport == "streamable-http":
if not self.url:
raise ValueError("streamable-http requires 'url'")
http_client = httpx.AsyncClient(
headers=dynamic_headers, timeout=self.timeout
)
await stack.enter_async_context(http_client)
transport_ctx = streamable_http_client(
url=self.url, http_client=http_client
)
elif self.transport == "sandbox_proxy":
from zhenxun.services.ai.sandbox.manager import (
sandbox_manager,
)
target_session_id = (
self.sandbox_session_id or "mcp_global_session"
)
bp = self.sandbox_blueprint or SandboxBlueprint()
bp.enable_network = True
driver = await sandbox_manager.get_or_create_session(
target_session_id,
blueprint=bp,
)
plugin_name = "universal_mcp"
await driver.mount_extension(plugin_name)
mcp_plugin = cast(
BaseMcpProxyExtension, driver.get_extension(plugin_name)
)
if not self.command:
raise ValueError("sandbox_proxy requires 'command'")
streams = await stack.enter_async_context(
mcp_plugin.connect_mcp(
self.command, self.args, dynamic_env
)
)
read_stream, write_stream = streams[0], streams[1]
transport_ctx = None
else:
raise ValueError(f"Unknown transport: {self.transport}")
if transport_ctx:
transport = await stack.enter_async_context(transport_ctx)
read_stream, write_stream = transport[0], transport[1]
client_session = await stack.enter_async_context(
ClientSession(read_stream, write_stream)
)
await client_session.initialize()
self._shared_session = client_session
if not self._is_initialized:
mcp_tools_res = await client_session.list_tools()
tools_list = list(mcp_tools_res.tools)
cursor = getattr(mcp_tools_res, "nextCursor", None)
while cursor:
mcp_tools_res = await client_session.list_tools(
cursor=cursor
)
tools_list.extend(mcp_tools_res.tools)
cursor = getattr(mcp_tools_res, "nextCursor", None)
for t in tools_list:
t_name = t.name.replace("-", "_")
final_name = (
f"{self.config.prefix}{t_name}"
if self.config.prefix
else t_name
)
self._tools.append(
MCPRemoteTool(
name=final_name,
original_tool_name=t.name,
description=t.description or "",
parameters=t.inputSchema,
toolkit=self,
)
)
self._is_initialized = True
self._ready_event.set()
logger.info(
f"成功连接 MCP 服务器: {self.server_name}, "
f"获取了 {len(self._tools)} 个工具"
)
await self._stop_event.wait()
return
except Exception as e:
from zhenxun.services.ai.core.exceptions import SandboxFatalError
if isinstance(e, SandboxFatalError):
raise e
if attempt < max_attempts:
logger.warning(
f"⚠️ [{self.server_name}] 进程启动或运行异常崩溃,"
"疑似环境损坏。触发自愈机制 (准备重试)..."
)
self._init_exception = e
self._shared_session = None
if not self._is_initialized:
self._is_initialized = False
continue
raise e
except Exception as e:
self._init_exception = e
logger.error(
f"MCP 服务器 '{self.server_name}' "
f"初始化连接失败(模式: {self.transport})。"
f"错误原因: {e}"
)
if "Connection closed" in str(e):
logger.error(
"提示:若是使用沙箱隧道,请进入 Docker Desktop 检查容器的日志。"
"多半是因为 npx 命令执行出错"
"(例如:镜像中缺少 Node 环境或国内网络无法连接 npm 等)。"
)
finally:
if not self._is_initialized:
self._is_initialized = False
self._shared_session = None
self._ready_event.set()
async def initialize(self, context: RunContext | None = None):
"""清空当前工具集并异步执行 MCP 服务端的全套初始化流程"""
if self._is_initialized:
return
self._tools.clear()
self._stop_event.clear()
self._ready_event.clear()
self._init_exception = None
dynamic_headers = {}
dynamic_env = self.env.copy()
self._shared_task = asyncio.create_task(
self._spawn_session_task(dynamic_headers, dynamic_env)
)
await self._ready_event.wait()
if self._init_exception:
raise self._init_exception
async def get_tools(self, context: RunContext | None = None) -> dict[str, BaseTool]:
await self.lifespan_manager.register(
self.server_name,
ttl=self.effective_ttl,
cleanup_callback=self.release_resource,
)
if not self._is_initialized:
await self.initialize(context)
tools_dict = {}
for t in self._tools:
tools_dict[t.name] = t
return tools_dict
async def release_resource(self, resource_id: str):
await self.close()
async def close(self):
"""彻底关闭 MCP 工具箱,注销生存期并释放底层 WebSocket/进程通道"""
current_task = asyncio.current_task()
if (
self.lifespan_manager._watchdog_task
and self.lifespan_manager._watchdog_task is not current_task
):
await self.lifespan_manager.stop()
self._stop_event.set()
self._is_initialized = False
self._shared_session = None
self._tools.clear()
if (
self._shared_task
and not self._shared_task.done()
and self._shared_task is not current_task
):
try:
await asyncio.wait_for(self._shared_task, timeout=5.0)
except asyncio.TimeoutError:
logger.warning(
f"MCP 服务器 '{self.server_name}' 的任务执行超时,正在取消。"
)
self._shared_task.cancel()
self._shared_task = None