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♻️ refactor(core): 重构 AI 能力与定时任务调度系统 (#2148)
* ♻️ 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>
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commit
922d092650
@@ -5,9 +5,8 @@ from pathlib import Path
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from typing import Any, Generic, cast
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from zhenxun.services.ai.capabilities import (
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AbstractCapability,
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CapabilitySource,
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CombinedCapability,
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DynamicCapability,
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)
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from zhenxun.services.ai.config import get_llm_config
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from zhenxun.services.ai.context.knowledge.base import BaseKnowledge
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@@ -67,7 +66,7 @@ from zhenxun.services.ai.tools.providers.skills.capabilities import (
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)
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from zhenxun.services.ai.tools.providers.skills.models import Skill, SkillSource
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from zhenxun.services.ai.utils import ContextUtils
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from zhenxun.services.log import logger
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from zhenxun.services.ai.utils.logger import log_agent as logger
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from zhenxun.utils.pydantic_compat import (
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model_construct,
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model_copy,
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@@ -78,7 +77,9 @@ from zhenxun.utils.utils import infer_plugin_namespace
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from .engine.builders import (
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AgentProfileResolver,
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CapabilityBuilder,
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ContextBuilder,
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SessionBuilder,
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ToolBuilder,
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)
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from .engine.executor import BaseAgentExecutor, StandardAgentExecutor
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@@ -94,9 +95,6 @@ ToolSource = (
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)
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"""任何可以作为工具提供给大模型的实体对象（函数、基础工具类、字典定义、工具名、工具箱、声明式查询对象）"""
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CapabilitySource = Callable | AbstractCapability
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"""能力/拦截器来源（函数或 AbstractCapability 实例）"""
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class AgentBuilder(Generic[AgentDepsT, OutputDataT]):
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"""
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@@ -148,7 +146,7 @@ class AgentBuilder(Generic[AgentDepsT, OutputDataT]):
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return self
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def with_tools(
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self, *tools: ToolSource | list[ToolSource]
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self, *tools: ToolSource | Sequence[ToolSource]
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) -> "AgentBuilder[AgentDepsT, OutputDataT]":
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"""
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配置可供智能体调用的工具列表。
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@@ -158,7 +156,7 @@ class AgentBuilder(Generic[AgentDepsT, OutputDataT]):
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"""
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current_tools = self._kwargs.setdefault("tools", [])
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for t in tools:
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if isinstance(t, list):
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if isinstance(t, Sequence) and not isinstance(t, str):
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current_tools.extend(t)
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else:
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current_tools.append(t)
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@@ -353,7 +351,7 @@ class Agent(
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description: str | None = None,
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persona: Persona | dict | None = None,
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model: str | Callable[[], str] | None = None,
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tools: list[ToolSource] | None = None,
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tools: Sequence[ToolSource] | None = None,
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skills: Sequence[str | Path | Skill | SkillSource] | None = None,
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generation_config: GenerationConfig | IntentBuilder | dict | None = None,
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response_model: BaseOutputDefinition | type[OutputDataT] | None = None,
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@@ -458,14 +456,14 @@ class Agent(
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def _assemble_plugins(self, tools, knowledge, capabilities, skills):
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"""私有方法：集中处理各类能力、知识与技能的挂载，消解冗余样板代码"""
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self.tool_definitions = tools or []
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self.tool_definitions = list(tools) if tools else []
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if knowledge:
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if not isinstance(knowledge, list):
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knowledge = [knowledge]
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self.tool_definitions.extend(knowledge)
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self.capabilities: list[AbstractCapability] = []
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self.capabilities: list[CapabilitySource] = []
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if self.memory_config.long_term.enable and self.memory_config.long_term.agentic:
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self.capabilities.append(
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@@ -478,11 +476,7 @@ class Agent(
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)
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if capabilities:
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for cap in capabilities:
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if isinstance(cap, AbstractCapability):
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self.capabilities.append(cap)
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elif callable(cap):
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self.capabilities.append(DynamicCapability(cap))
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self.capabilities.extend(capabilities)
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if self.config.enable_hitl:
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self.tool_definitions.append(HITLToolkit())
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@@ -789,11 +783,6 @@ class Agent(
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**kwargs: Any,
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) -> tuple[AgentState, AgentRunResources]:
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"""解析任务意图，初始化隔离域与基础状态载体"""
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from zhenxun.services.ai.flow.agent.engine.builders import (
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AgentProfileResolver,
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CapabilityBuilder,
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SessionBuilder,
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)
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if context is None:
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raise ValueError("RunContext 不能为空")
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@@ -900,7 +889,6 @@ class Agent(
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toolset_funcs=getattr(self, "toolset_funcs", []),
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system_tools=[],
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namespace=self.namespace or "unknown",
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tool_filter=resources.config.tool_filter,
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run_context=context,
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run_scoped_cap=run_scoped_cap,
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)
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