Files
zhenxun_bot/zhenxun/services/ai/tools/engine/registry.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

602 lines
22 KiB
Python

from __future__ import annotations
import asyncio
from collections.abc import Callable, Iterable
import inspect
from typing import Any, Generic, SupportsIndex, TypeVar, cast, overload
from typing_extensions import Self
from nonebot.utils import is_coroutine_callable
from zhenxun.services.ai.core.exceptions import ConfigurationException
from zhenxun.services.ai.core.protocols.tool import (
ToolExecutable,
ToolProvider,
)
from zhenxun.services.ai.run.context import RunContext
from zhenxun.services.ai.tools.core.toolkit import BaseToolkit
from zhenxun.services.ai.tools.models import Query, ResolvedToolPayload
from zhenxun.services.log import logger
from zhenxun.utils.utils import infer_plugin_namespace
T = TypeVar("T", bound=ToolExecutable)
class ToolCollection(list[T], Generic[T]):
"""支持按索引和按名称获取的工具集合 (List + Dict)"""
def __init__(self, iterable: Iterable[T] | None = None):
"""初始化工具集合。"""
super().__init__(iterable or [])
self._name_cache: dict[str, T] = {}
self._build_name_cache()
def _build_name_cache(self) -> None:
"""构建工具名称小写到工具实例的映射缓存。"""
self._name_cache = {}
for tool in self:
name = getattr(tool, "name", None)
if name:
self._name_cache[name.lower()] = tool
@overload
def __getitem__(self, key: SupportsIndex) -> T: ...
@overload
def __getitem__(self, key: slice) -> list[T]: ...
@overload
def __getitem__(self, key: str) -> T: ...
def __getitem__(self, key: Any) -> Any:
if isinstance(key, str):
return self._name_cache[key.lower()]
return super().__getitem__(key)
@overload
def __setitem__(self, key: SupportsIndex, value: T) -> None: ...
@overload
def __setitem__(self, key: slice, value: Iterable[T]) -> None: ...
@overload
def __setitem__(self, key: str, value: T) -> None: ...
def __setitem__(self, key: Any, value: Any) -> None:
if isinstance(key, str):
name = key.lower()
if name in self._name_cache:
old_tool = self._name_cache[name]
try:
idx = super().index(old_tool)
super().__setitem__(idx, value)
except ValueError:
super().append(value)
else:
super().append(value)
self._name_cache[name] = value
else:
super().__setitem__(key, value)
self._name_cache[value.name.lower()] = value
def get(self, key: str, default: Any = None) -> T | Any:
"""通过名称获取工具,若不存在则返回默认值。"""
return self._name_cache.get(key.lower(), default)
def append(self, object: T) -> None:
"""向集合中添加工具,并更新名称缓存。"""
name = object.name
if name.lower() in self._name_cache:
old_tool = self._name_cache[name.lower()]
try:
idx = super().index(old_tool)
super().__setitem__(idx, object)
except ValueError:
super().append(object)
else:
super().append(object)
self._name_cache[name.lower()] = object
def extend(self, iterable: Iterable[T]) -> None:
"""批量添加工具到集合中。"""
for t in iterable:
self.append(t)
def remove(self, value: T) -> None:
"""从集合中移除指定工具,并同步更新缓存。"""
super().remove(value)
name = getattr(value, "name", None)
if name and name.lower() in self._name_cache:
del self._name_cache[name.lower()]
def pop(self, index: SupportsIndex = -1) -> T:
"""弹出指定位置的工具,并从缓存中移除。"""
tool = super().pop(index)
name = getattr(tool, "name", None)
if name and name.lower() in self._name_cache:
del self._name_cache[name.lower()]
return tool
def filter_by_names(self, names: list[str] | None = None) -> "ToolCollection[T]":
"""根据名称列表筛选并返回新的工具子集合。"""
if names is None:
return self
return ToolCollection(
[
tool
for name in names
if (tool := self._name_cache.get(name.lower())) is not None
]
)
def clear(self) -> None:
"""清空集合及所有名称缓存。"""
super().clear()
self._name_cache.clear()
def keys(self):
"""获取所有工具名称缓存的键。"""
return self._name_cache.keys()
def values(self):
"""获取所有已缓存的工具实例。"""
return self._name_cache.values()
def items(self):
"""获取所有工具名称与实例的键值对。"""
return self._name_cache.items()
class _StringResolver:
"""字符串格式的工具路由解析器。
负责解析像 'ns.tool_name'、'ns.*' 或 'ns.#tag' 的语法路由。
"""
def __init__(
self, name: str, manager: "ToolProviderManager", default_namespace: str
):
"""初始化字符串路由解析器。"""
self.name = name
self.manager = manager
self.default_namespace = default_namespace
async def resolve(self, context: RunContext | None = None) -> ResolvedToolPayload:
"""解析字符串路由并返回匹配的工具载荷。"""
if self.name in self.manager._macro_resolvers:
resolver = self.manager._macro_resolvers[self.name]
resolved = (
await resolver() if is_coroutine_callable(resolver) else resolver()
)
return await self.manager._normalize_to_resolver(
resolved, self.default_namespace
).resolve(context)
s = self.name
if "." in s:
ns, target = s.split(".", 1)
else:
ns = self.default_namespace
target = s
from zhenxun.services.ai.tools.models import Query
if target == "*":
query = Query(namespace=ns)
elif target.startswith("#"):
tags = [t for t in target.split("#") if t]
query = Query(tags=tags, namespace=ns)
else:
query = Query(name=target, namespace=ns)
logger.debug(f"🔍 [StringRouter] 语法解析: '{self.name}' -> {query}")
return await _QueryResolver(
query, self.manager, self.default_namespace
).resolve(context)
class _QueryResolver:
"""Query 查询对象格式的工具路由解析器。
负责根据 namespace、标签或工具名称检索匹配的工具。
"""
def __init__(
self, query: Query, manager: "ToolProviderManager", default_namespace: str
):
"""初始化查询对象路由解析器。"""
self.query = query
self.manager = manager
self.default_namespace = default_namespace
async def resolve(self, context: RunContext | None = None) -> ResolvedToolPayload:
"""执行查询以解析并返回匹配的工具载荷。"""
payload = ResolvedToolPayload()
namespaces_to_search = []
target_namespace = self.query.namespace or self.default_namespace
if target_namespace == "global":
namespaces_to_search = list(self.manager._namespaced_tools.keys())
elif target_namespace:
namespaces_to_search = [target_namespace]
else:
raise ValueError(f"Query 对象必须显式指定 namespace 作用域: {self.query}")
for ns in namespaces_to_search:
if ns in self.manager._namespaced_tools:
for tool in self.manager._namespaced_tools[ns]:
if self.query.match(tool):
p = await tool.resolve(context)
if p:
payload.tools.extend(p.tools)
payload.injected_prompts.extend(p.injected_prompts)
payload.toolkits.extend(p.toolkits)
if self.query.name and not payload.tools and not self.query.tags:
specific = await self.manager.resolve_specific_tools([self.query.name])
for t in specific:
if self.query.match(t):
payload.tools.append(t)
return payload
class _CallableResolver:
"""普通 Python 函数/可调用对象格式的工具路由解析器。
负责将其包装为 FunctionTool 实例。
"""
def __init__(self, func: Callable, manager: "ToolProviderManager"):
"""初始化可调用对象路由解析器。"""
self.func = func
self.manager = manager
async def resolve(self, context: RunContext | None = None) -> ResolvedToolPayload:
"""将可调用对象转换为函数工具并返回其解析载荷。"""
for candidate in (
getattr(self.func, "__tool_name__", None),
getattr(self.func, "__name__", None),
):
if candidate:
for ns_tools in self.manager._namespaced_tools.values():
if t := ns_tools.get(candidate):
return await t.resolve(context)
from zhenxun.services.ai.tools.core.tool import FunctionTool
t = FunctionTool(func=self.func)
return await t.resolve(context)
class _TypeAdapterResolver:
"""基于自定义类型映射注册的工具路由解析器。负责调用对应类型的解析函数。"""
def __init__(
self,
item: Any,
resolver_func: Callable,
manager: "ToolProviderManager",
default_namespace: str,
):
"""初始化类型适配器解析器。"""
self.item = item
self.resolver_func = resolver_func
self.manager = manager
self.default_namespace = default_namespace
async def resolve(self, context: RunContext | None = None) -> ResolvedToolPayload:
"""执行类型适配器函数并解析返回对应的工具载荷。"""
resolved = (
await self.resolver_func(self.item)
if is_coroutine_callable(self.resolver_func)
else self.resolver_func(self.item)
)
return await self.manager._normalize_to_resolver(
resolved, self.default_namespace
).resolve(context)
class ToolProviderManager:
"""工具提供者的中心化管理器,采用单例模式。"""
_instance: "ToolProviderManager | None" = None
def __new__(cls) -> Self:
"""单例模式的实例创建方法。"""
if cls._instance is None:
cls._instance = super().__new__(cls)
return cast(Self, cls._instance)
def __init__(self):
"""初始化工具提供者管理器。"""
if hasattr(self, "_initialized") and self._initialized:
return
self._providers: list[ToolProvider] = []
self._namespaced_tools: dict[str, ToolCollection] = {}
self._resolved_tools: ToolCollection | None = None
self._init_lock = asyncio.Lock()
self._init_promise: asyncio.Task | None = None
self._initialized = True
self._macro_resolvers: dict[str, Callable] = {}
self._type_resolvers: dict[type, Callable] = {}
def register_macro_resolver(self, macro_str: str, resolver_func: Callable) -> None:
"""注册宏解析器函数。"""
self._macro_resolvers[macro_str] = resolver_func
def register_type_resolver(
self, target_type: type, resolver_func: Callable
) -> None:
"""注册特定类型的工具解析函数。"""
self._type_resolvers[target_type] = resolver_func
def register(self, provider: ToolProvider):
"""注册一个新的 ToolProvider。"""
if provider not in self._providers:
self._providers.append(provider)
logger.debug(f"已注册工具提供者: {provider.__class__.__name__}")
def register_tool(self, tool: ToolExecutable):
"""注册由 @tool 生成的单一工具"""
ns = infer_plugin_namespace()
if ns not in self._namespaced_tools:
self._namespaced_tools[ns] = ToolCollection()
self._namespaced_tools[ns].append(tool)
self._resolved_tools = None
def register_toolkit(self, toolkit: Any) -> None:
"""
注册一个完整的 Toolkit 实例,使其可通过智能字符串路由(Tag或Name)被动态发现。
"""
ns = infer_plugin_namespace()
if ns not in self._namespaced_tools:
self._namespaced_tools[ns] = ToolCollection()
self._namespaced_tools[ns].append(toolkit)
self._resolved_tools = None
async def initialize(self) -> None:
"""懒加载初始化所有已注册的 ToolProvider。"""
if not self._init_promise:
async with self._init_lock:
if not self._init_promise:
self._init_promise = asyncio.create_task(
self._initialize_providers()
)
await self._init_promise
async def _initialize_providers(self) -> None:
"""并发初始化所有已注册的工具提供者。"""
logger.info(f"开始初始化 {len(self._providers)} 个工具提供者...")
init_tasks = [provider.initialize() for provider in self._providers]
await asyncio.gather(*init_tasks, return_exceptions=True)
logger.info("所有工具提供者初始化完成。")
async def discover_tools(
self,
allowed_servers: list[str] | None = None,
excluded_servers: list[str] | None = None,
) -> dict[str, ToolExecutable]:
"""向所有已初始化的 ToolProvider 并发执行工具发现。"""
discover_tasks = []
provider_indices = []
for i, provider in enumerate(self._providers):
sig = inspect.signature(provider.discover_tools)
params_to_pass = {}
if "allowed_servers" in sig.parameters:
params_to_pass["allowed_servers"] = allowed_servers
if "excluded_servers" in sig.parameters:
params_to_pass["excluded_servers"] = excluded_servers
discover_tasks.append(provider.discover_tools(**params_to_pass))
provider_indices.append(i)
results = await asyncio.gather(*discover_tasks, return_exceptions=True)
provider_tools = {}
for result_idx, provider_result in enumerate(results):
provider = self._providers[provider_indices[result_idx]]
provider_name = provider.__class__.__name__
if isinstance(provider_result, dict):
logger.debug(
f"提供者 '{provider_name}' 发现了 {len(provider_result)} 个工具。"
)
for name, executable in provider_result.items():
if provider_tools.get(name):
logger.warning(
f"发现重复的工具名称 '{name}',后发现的将覆盖前者。"
)
provider_tools[name] = executable
elif isinstance(provider_result, Exception):
logger.error(
f"提供者 '{provider_name}' 在发现工具时出错: {provider_result}"
)
return provider_tools
async def _query_engine(
self,
names: list[str] | None = None,
allowed_servers: list[str] | None = None,
excluded_servers: list[str] | None = None,
include_providers: bool = True,
) -> ToolCollection:
"""统一查询引擎:收敛所有本地与云端的工具检索逻辑"""
await self.initialize()
resolved = ToolCollection()
for ns_tools in self._namespaced_tools.values():
for t in ns_tools:
if names and t.name not in names:
continue
resolved.append(t)
if not include_providers:
return resolved
if names:
missing_names = [n for n in names if not resolved.get(n)]
for name in missing_names:
config = {"name": name}
for provider in self._providers:
try:
if executable := await provider.get_tool_executable(
name, config
):
resolved.append(executable)
break
except Exception as exc:
logger.error(
f"provider '{provider.__class__.__name__}'"
f"解析工具 '{name}' 出错: {exc}"
)
else:
provider_tools = await self.discover_tools(
allowed_servers, excluded_servers
)
for t in provider_tools.values():
resolved.append(t)
return resolved
async def get_resolved_tools(
self,
allowed_servers: list[str] | None = None,
excluded_servers: list[str] | None = None,
namespaces: list[str] | None = None,
) -> ToolCollection:
"""获取已解析完成的所有可用工具集合。"""
has_filters = (
allowed_servers is not None
or excluded_servers is not None
or namespaces is not None
)
if not has_filters and self._resolved_tools is not None:
return self._resolved_tools
tools = await self._query_engine(
allowed_servers=allowed_servers, excluded_servers=excluded_servers
)
if not has_filters:
self._resolved_tools = tools
return tools
async def resolve_specific_tools(self, tool_names: list[str]) -> ToolCollection:
"""根据名称列表检索并返回特定的工具集合。"""
return await self._query_engine(names=tool_names, include_providers=True)
async def get_function_tools(
self, names: list[str] | None = None
) -> ToolCollection:
"""获取本地注册的所有函数工具集合。"""
return await self._query_engine(names=names, include_providers=False)
def _normalize_to_resolver(self, item: Any, default_ns: str) -> Any:
"""将任意工具配置或定义包装为标准的多态解析器对象。"""
if hasattr(item, "resolve"):
return item
if isinstance(item, Query):
return _QueryResolver(item, self, default_ns)
if isinstance(item, str):
return _StringResolver(item, self, default_ns)
if type(item) in self._type_resolvers:
return _TypeAdapterResolver(
item, self._type_resolvers[type(item)], self, default_ns
)
if callable(item):
return _CallableResolver(item, self)
if not hasattr(item, "resolve"):
raise TypeError(
f"严格协议校验失败: 工具对象 {type(item)} 必须实现 ToolResolvable 协议 "
"(包含 resolve 方法)。如果你想注册普通函数,请使用 @tool 装饰器。"
)
return item
async def resolve_tools(
self,
tool_definitions: Iterable[Any] | None,
namespace: str | None = None,
context: RunContext | None = None,
) -> ResolvedToolPayload:
"""
统一解析工具配置,全面采用多态解析器与并发聚合管线。
"""
if not tool_definitions:
return ResolvedToolPayload()
if not namespace:
namespace = infer_plugin_namespace()
logger.debug(
f"🔍 [StringRouter] 自动推断当前调用者所在插件为: '{namespace}'"
)
defs = []
def _flatten(items):
for item in items:
if isinstance(item, list):
_flatten(item)
else:
defs.append(item)
_flatten(tool_definitions)
resolvers = [self._normalize_to_resolver(t, namespace) for t in defs]
for i, r in enumerate(resolvers):
if asyncio.iscoroutine(r):
r = await r
resolvers[i] = self._normalize_to_resolver(r, namespace)
tasks = [r.resolve(context) for r in resolvers]
payloads = await asyncio.gather(*tasks, return_exceptions=False)
final_payload = ResolvedToolPayload()
global_toolkit = BaseToolkit(prefix="")
for p in payloads:
if not p:
continue
p = cast(ResolvedToolPayload, p)
for t in p.tools:
if not getattr(t, "parent_toolkit", None):
t.parent_toolkit = global_toolkit
final_payload.tools.append(t)
final_payload.injected_prompts.extend(p.injected_prompts)
final_payload.toolkits.extend(p.toolkits)
final_payload.tools = ToolCollection(final_payload.tools)
return final_payload
tool_provider_manager = ToolProviderManager()
async def _dict_ad_hoc_resolver(config: dict):
"""针对字典类型的 ad-hoc 工具配置的类型解析器。"""
name = config.get("name")
if not name:
raise ConfigurationException(
"工具配置字典必须包含 'name' 字段。",
)
for provider in tool_provider_manager._providers:
executable = await provider.get_tool_executable(name, config)
if executable:
return executable
raise ConfigurationException(
f"没有为 ad-hoc 工具 '{name}' 找到合适的提供者。",
)
tool_provider_manager.register_type_resolver(dict, _dict_ad_hoc_resolver)