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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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parent
0b32d69c9c
commit
922d092650
@@ -6,8 +6,11 @@ from nonebot.utils import is_coroutine_callable
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from zhenxun.services.ai.capabilities import AbstractCapability
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from zhenxun.services.ai.run import RunContext
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from zhenxun.services.ai.run.di import DependencyInjector
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from zhenxun.services.ai.tools.bridges.handoff import HandoffTool
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from .models import Transition
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class TeamRoutingCapability(AbstractCapability):
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"""团队路由能力组件：动态向所有团队成员"""
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@@ -17,10 +20,12 @@ class TeamRoutingCapability(AbstractCapability):
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team_name: str,
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members: list[Any],
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state_flow: Mapping[str, Sequence[Any]] | Callable | None = None,
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max_handoffs: int = 3,
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):
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self.team_name = team_name
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self.members = members
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self.state_flow = state_flow
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self.max_handoffs = max_handoffs
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async def _get_allowed_transitions(self, context: RunContext) -> list[Any] | None:
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"""核心FSM解析：解析静态字典或动态执行函数获取允许的 Transition 列表"""
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@@ -34,15 +39,12 @@ class TeamRoutingCapability(AbstractCapability):
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current_speaker,
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[m.name for m in self.members if m.name != current_speaker],
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)
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from zhenxun.services.ai.flow.team.models import Transition
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return [
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Transition(target=t) if isinstance(t, str) else t for t in raw_targets
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]
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if callable(self.state_flow):
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from zhenxun.services.ai.run.di import DependencyInjector
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sig = inspect.signature(self.state_flow)
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kwargs = await DependencyInjector.resolve_all(
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sig, call_kwargs={}, context=context
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@@ -55,7 +57,6 @@ class TeamRoutingCapability(AbstractCapability):
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if result is None:
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return None
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from zhenxun.services.ai.flow.team.models import Transition
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return [Transition(target=t) if isinstance(t, str) else t for t in result]
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@@ -97,6 +98,7 @@ class TeamRoutingCapability(AbstractCapability):
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target_name=m.name,
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target_description=desc,
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input_schema=input_schema,
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max_handoffs=self.max_handoffs,
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)
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)
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return tools
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@@ -1,3 +1,5 @@
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from __future__ import annotations
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from collections.abc import Callable, Sequence
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from enum import Enum
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from typing import Any
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@@ -7,7 +9,8 @@ from pydantic import BaseModel, ConfigDict, Field
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from zhenxun.services.ai.core.messages import AgentMessage
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from zhenxun.services.ai.core.options import BaseOutputDefinition
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from zhenxun.services.ai.flow.base import BaseRuntimeConfig
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from zhenxun.services.ai.flow.base import BaseRunnable, BaseRuntimeConfig
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from zhenxun.services.ai.run import AgentTask
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class TeamRuntimeConfig(BaseRuntimeConfig):
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@@ -45,7 +48,7 @@ class Transition(BaseModel):
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trigger_regex: str | None = None
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"""(可选) 正则表达式。
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如果用户的输入匹配此正则，将触发极速硬路由，跳过大模型思考。"""
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trigger_func: Callable[..., Any] | None = None
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trigger_func: Callable[..., bool | str | None] | None = None
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"""(可选) 自定义校验函数。返回 True 或目标名称时触发硬路由。支持依赖注入。"""
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model_config = ConfigDict(arbitrary_types_allowed=True)
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@@ -62,9 +65,9 @@ class CallAction(TeamAction):
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调度动作：呼叫指定的 Agent 执行任务
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"""
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agent: str | Any
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agent: str | BaseRunnable[Any]
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"""目标 Agent 的名称（字符串）或动态生成的 Agent 实例"""
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task: str | Any
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task: str | AgentTask
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"""派发给该 Agent 的具体任务或提示词"""
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history: Sequence[AgentMessage] | None = None
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"""需要传递给该 Agent 的上下文历史记录（可选）"""
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@@ -8,10 +8,11 @@ from nonebot.utils import is_coroutine_callable
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from zhenxun.services.ai.core.messages import AgentMessage
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from zhenxun.services.ai.core.templates import PromptTemplate
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from zhenxun.services.ai.flow.team.models import RouteDecision, Transition
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from zhenxun.services.ai.run import AgentTask, RunContext
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from zhenxun.services.ai.run.di import DependencyInjector
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from zhenxun.services.log import logger
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from zhenxun.services.ai.utils.logger import log_team as logger
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from .models import RouteDecision, Transition
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class BaseRouter(ABC):
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@@ -148,6 +149,7 @@ class LLMRouter(BaseRouter):
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runtime_config: Any = None,
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custom_prompt: str | None = None,
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allowed_transitions: list[Transition] | None = None,
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max_handoffs: int = 3,
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):
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"""
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初始化基于大模型的意图路由器。
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@@ -161,6 +163,7 @@ class LLMRouter(BaseRouter):
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runtime_config: 团队级别的运行时全局配置。
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custom_prompt: 自定义的系统提示词模板，用以覆盖默认的路由系统指令。
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allowed_transitions: 允许的状态移交规则与前置条件列表。
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max_handoffs: 同一会话中允许连续移交的最大次数。
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"""
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self.team_name = team_name
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self.members = members
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@@ -170,6 +173,7 @@ class LLMRouter(BaseRouter):
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self.runtime_config = runtime_config
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self.custom_prompt = custom_prompt
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self.allowed_transitions = allowed_transitions
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self.max_handoffs = max_handoffs
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async def route(
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self,
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@@ -179,7 +183,8 @@ class LLMRouter(BaseRouter):
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) -> RouteDecision | None:
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from zhenxun.services.ai.flow.agent.agent import Agent
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from zhenxun.services.ai.flow.agent.models import AgentConfig
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from zhenxun.services.ai.flow.team.capabilities import TeamRoutingCapability
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from .capabilities import TeamRoutingCapability
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default_system_prompt = """## 角色与目标
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你是一个高级任务路由器 (所在团队: {{ team_name }})。
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@@ -200,7 +205,10 @@ class LLMRouter(BaseRouter):
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route_prompt = PromptTemplate(template).render(team_name=self.team_name)
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routing_cap = TeamRoutingCapability(
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team_name=self.team_name, members=self.members, state_flow=self.state_flow
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team_name=self.team_name,
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members=self.members,
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state_flow=self.state_flow,
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max_handoffs=self.max_handoffs,
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)
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leader_config = AgentConfig(
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@@ -8,17 +8,19 @@ from zhenxun.services.ai.core.exceptions import (
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LLMException,
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)
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from zhenxun.services.ai.core.messages import UsageInfo
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from zhenxun.services.ai.flow.team.capabilities import TeamRoutingCapability
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from zhenxun.services.ai.flow.team.models import (
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from zhenxun.services.ai.flow.agent.models import AgentConfig
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from zhenxun.services.ai.run import AgentRunResult, RunContext
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from zhenxun.services.ai.run.models import AgentRunEnd
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from zhenxun.services.ai.utils.logger import log_team as logger
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from zhenxun.utils.pydantic_compat import model_construct
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from .capabilities import TeamRoutingCapability
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from .models import (
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CallAction,
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ConcurrentCallAction,
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FinishAction,
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)
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from zhenxun.services.ai.flow.team.strategy import BaseTeamStrategy
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from zhenxun.services.ai.run import AgentRunResult, RunContext
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from zhenxun.services.ai.run.models import AgentRunEnd
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from zhenxun.services.log import logger
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from zhenxun.utils.pydantic_compat import model_construct
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from .strategy import BaseTeamStrategy, RouteStrategy
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class TeamRunner:
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@@ -47,7 +49,7 @@ class TeamRunner:
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(m for m in self.team.members if m.name == action.agent), None
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)
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if not target_agent:
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logger.error(f"❌ [TeamRunner] 找不到团队成员: {action.agent}")
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logger.error(f"❌ 找不到团队成员: {action.agent}")
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await queue.put(
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(
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"result",
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@@ -67,13 +69,12 @@ class TeamRunner:
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sub_context = context.clone_for_member(target_agent.name)
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sub_context.capabilities = list(sub_context.capabilities)
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from zhenxun.services.ai.flow.team.strategy import RouteStrategy
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if isinstance(self.strategy, RouteStrategy):
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routing_cap = TeamRoutingCapability(
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team_name=self.team.name,
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members=self.team.members,
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state_flow=getattr(self.strategy, "state_flow", None),
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max_handoffs=getattr(self.strategy, "max_handoffs", 3),
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)
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sub_context.capabilities.append(routing_cap)
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@@ -82,8 +83,6 @@ class TeamRunner:
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agent_res = None
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try:
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from zhenxun.services.ai.flow.agent.models import AgentConfig
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async with target_agent.run_stream(
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prompt=action.task,
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context=sub_context,
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@@ -10,19 +10,26 @@ from zhenxun.services.ai.core.stream_events import ToolStreamChunkEvent
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from zhenxun.services.ai.core.templates import PromptTemplate
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from zhenxun.services.ai.flow.agent.agent import Agent, ToolSource
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from zhenxun.services.ai.flow.agent.models import AgentConfig
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from zhenxun.services.ai.flow.team.models import (
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from zhenxun.services.ai.run import AgentTask, RunContext
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from zhenxun.services.ai.run.blackboard import BlackboardManager
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from zhenxun.services.ai.tools.bridges.delegate import DelegateTool
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from zhenxun.services.ai.tools.providers.builtin.blackboard import BlackboardToolkit
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from zhenxun.services.ai.utils.logger import log_team as logger
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from .models import (
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CallAction,
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ConcurrentCallAction,
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FinishAction,
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TaskBoardState,
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TaskNodeStatus,
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TeamAction,
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Transition,
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)
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from zhenxun.services.ai.flow.team.router import BaseRouter
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from zhenxun.services.ai.run import AgentTask, RunContext
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from zhenxun.services.ai.tools.bridges.delegate import DelegateTool
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from zhenxun.services.log import logger
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from .router import BaseRouter
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from .task_tools import TaskPlanningToolkit
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if TYPE_CHECKING:
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from zhenxun.services.ai.flow.team.team import Team
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from .team import Team
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class BaseTeamStrategy(ABC):
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@@ -106,6 +113,7 @@ class RouteStrategy(BaseTeamStrategy):
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leader_model: str | None = None,
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leader_tools: list[ToolSource] | None = None,
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custom_prompt: str | None = None,
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max_handoffs: int = 3,
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):
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"""
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路由策略初始化，基于挂载的 Router 进行最合适的专家分发。
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@@ -117,16 +125,16 @@ class RouteStrategy(BaseTeamStrategy):
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leader_model: 路由节点 (Leader) 使用的大模型名称，若为空则默认继承全局。
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leader_tools: 挂载给路由节点 (Leader) 的专属工具列表。
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custom_prompt: 自定义系统提示词，用于覆盖默认的路由系统提示词。
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max_handoffs: 同一会话中允许连续移交的最大次数。
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"""
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super().__init__(custom_prompt=custom_prompt)
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self.selector_func = selector_func
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self.router = router
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self.leader_model = leader_model
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self.leader_tools = leader_tools or []
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self.max_handoffs = max_handoffs
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if isinstance(state_flow, dict):
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from zhenxun.services.ai.flow.team.models import Transition
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normalized_flow = {}
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for k, targets in state_flow.items():
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normalized_targets = []
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@@ -163,6 +171,7 @@ class RouteStrategy(BaseTeamStrategy):
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state_flow=self.state_flow,
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runtime_config=getattr(team, "runtime_config", None),
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custom_prompt=self.custom_prompt,
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max_handoffs=self.max_handoffs,
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)
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)
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router = ChainRouter(routers)
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@@ -171,13 +180,11 @@ class RouteStrategy(BaseTeamStrategy):
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exec_config = kwargs.get("config")
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max_cycles = getattr(exec_config, "max_cycles", 15) if exec_config else 15
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logger.info(f"🛣️ [RouteStrategy] '{team.name}' 正在获取初始路由决策...")
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logger.debug(f"🛣️ '{team.name}' 正在获取初始路由决策...")
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decision = await router.route(context, [], prompt)
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if not decision:
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logger.warning(
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f"🚨 [RouteStrategy] Team '{team.name}' 的所有路由策略未能命中目标。"
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)
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logger.warning(f"🚨 Team '{team.name}' 的所有路由策略未能命中目标。")
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raise AbortException(
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reason=f"Team '{team.name}' 无法找到合适的路由节点处理该任务",
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display="🚨 团队协作失败，无法分配任务。",
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@@ -191,7 +198,7 @@ class RouteStrategy(BaseTeamStrategy):
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cycle_count += 1
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if cycle_count > max_cycles:
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logger.error(
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f"🚨 [RouteStrategy] Team '{team.name}' 路由陷入死循环！"
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f"🚨 Team '{team.name}' 路由陷入死循环！"
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f"已达到最大限制 {max_cycles} 次。"
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)
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raise AbortException(
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@@ -229,7 +236,7 @@ class RouteStrategy(BaseTeamStrategy):
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run_result = yield CallAction(
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agent=current_target,
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task=prompt,
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task=prompt or "",
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history=handoff_history_messages,
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kwargs=kwargs,
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)
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@@ -268,7 +275,7 @@ class RouteStrategy(BaseTeamStrategy):
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pass
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if fast_routed:
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logger.info(
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logger.debug(
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f"🛣️ **路由决策**: 委派给专员 👨💼`{current_target}`"
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"(系统拦截：正则/函数状态流发生转移)"
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)
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@@ -291,18 +298,21 @@ class CoordinateStrategy(BaseTeamStrategy):
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leader_model: str | None = None,
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leader_tools: list[ToolSource] | None = None,
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custom_prompt: str | None = None,
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max_delegations: int = 3,
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):
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"""
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协作策略初始化，Leader 主动拆解任务，委派给 Sub-Agents 并汇总结果。
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参数:
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leader_model: 协调节点 (Leader) 使用的大模型名称，若为空则默认继承全局。
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leader_tools: 挂载给协调节点 (Leader) 的专属工具列表。
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leader_tools: 挂载给协调节点 (Leader) 的专属工具列表.
|
||||
custom_prompt: 自定义系统提示词，用于覆盖默认的协调系统提示词。
|
||||
max_delegations: 允许向同一个专员连续委派失败的最大重试次数。
|
||||
"""
|
||||
super().__init__(custom_prompt=custom_prompt)
|
||||
self.leader_model = leader_model
|
||||
self.leader_tools = leader_tools or []
|
||||
self.max_delegations = max_delegations
|
||||
|
||||
async def generate_plan(
|
||||
self,
|
||||
@@ -323,6 +333,7 @@ class CoordinateStrategy(BaseTeamStrategy):
|
||||
runnable=m,
|
||||
name=f"delegate_to_{m.name}",
|
||||
description=f"将子任务委派给专员 [{m.name}] 处理。专长：{desc}",
|
||||
max_delegations=self.max_delegations,
|
||||
)
|
||||
)
|
||||
|
||||
@@ -338,17 +349,16 @@ class CoordinateStrategy(BaseTeamStrategy):
|
||||
|
||||
logger.debug(f"✨ **团队 [{team.name}] Leader** 正在汇总各方报告...")
|
||||
|
||||
if context.run.event_bus:
|
||||
await context.run.event_bus.emit(
|
||||
ToolStreamChunkEvent(
|
||||
tool_name="Team Leader",
|
||||
content="✨ 团队 Leader 正在汇总各方报告...",
|
||||
)
|
||||
await context.run.emit(
|
||||
ToolStreamChunkEvent(
|
||||
tool_name="Team Leader",
|
||||
content="✨ 团队 Leader 正在汇总各方报告...",
|
||||
)
|
||||
)
|
||||
|
||||
logger.debug(f"👨💼 [CoordinateStrategy] '{team.name}' 正在启动协调推理循环...")
|
||||
|
||||
leader_res = yield CallAction(agent=leader_agent, task=prompt)
|
||||
leader_res = yield CallAction(agent=leader_agent, task=prompt or "")
|
||||
|
||||
yield FinishAction(result=leader_res)
|
||||
|
||||
@@ -389,24 +399,22 @@ class BroadcastStrategy(BaseTeamStrategy):
|
||||
prompt.description if isinstance(prompt, AgentTask) else (prompt or "")
|
||||
)
|
||||
|
||||
if context.run.event_bus:
|
||||
await context.run.event_bus.emit(
|
||||
ToolStreamChunkEvent(
|
||||
tool_name="Team Broadcaster",
|
||||
content=f"🚀 正在并发广播任务给 {len(team.members)} 位专家...",
|
||||
)
|
||||
await context.run.emit(
|
||||
ToolStreamChunkEvent(
|
||||
tool_name="Team Broadcaster",
|
||||
content=f"🚀 正在并发广播任务给 {len(team.members)} 位专家...",
|
||||
)
|
||||
)
|
||||
|
||||
actions = [CallAction(agent=m.name, task=task_desc_str) for m in team.members]
|
||||
results = yield ConcurrentCallAction(actions=actions)
|
||||
|
||||
if context.run.event_bus:
|
||||
await context.run.event_bus.emit(
|
||||
ToolStreamChunkEvent(
|
||||
tool_name="Team Leader",
|
||||
content="✨ 所有专家汇报完毕，Leader 正在融合各方观点...",
|
||||
)
|
||||
await context.run.emit(
|
||||
ToolStreamChunkEvent(
|
||||
tool_name="Team Leader",
|
||||
content="✨ 所有专家汇报完毕，Leader 正在融合各方观点...",
|
||||
)
|
||||
)
|
||||
|
||||
logger.debug(f"✨ **团队 [{team.name}] Leader** 正在汇总各方报告...")
|
||||
|
||||
@@ -451,8 +459,7 @@ class TaskStrategy(BaseTeamStrategy):
|
||||
leader_model: str | None = None,
|
||||
leader_tools: list[ToolSource] | None = None,
|
||||
max_iterations: int = 15,
|
||||
blackboard_schema: type[BaseModel] | None = None,
|
||||
initial_blackboard_state: BaseModel | None = None,
|
||||
blackboard: type[BaseModel] | BaseModel | None = None,
|
||||
custom_prompt: str | None = None,
|
||||
):
|
||||
"""
|
||||
@@ -463,10 +470,9 @@ class TaskStrategy(BaseTeamStrategy):
|
||||
leader_model: 规划节点 (Leader) 使用的大模型名称，若为空则默认继承全局。
|
||||
leader_tools: 挂载给规划节点 (Leader) 的专属附加工具列表。
|
||||
max_iterations: 引擎驱动的状态机最大迭代/循环次数，防止死循环。
|
||||
blackboard_schema: 团队共享黑板的数据结构类型 (Pydantic Model 类)。
|
||||
initial_blackboard_state: 共享黑板的初始数据状态实例。
|
||||
blackboard: (可选) 团队共享黑板。可传入 Schema 类型类，或直接传入带有初始数据的 Schema 实例对象。
|
||||
custom_prompt: 自定义系统提示词，用于覆盖默认的规划系统提示词。
|
||||
"""
|
||||
""" # noqa: E501
|
||||
super().__init__(custom_prompt=custom_prompt)
|
||||
self.leader_model = leader_model
|
||||
self.leader_tools = leader_tools or []
|
||||
@@ -474,14 +480,21 @@ class TaskStrategy(BaseTeamStrategy):
|
||||
|
||||
self.blackboard = None
|
||||
self.bb_toolkit = None
|
||||
if blackboard_schema is not None:
|
||||
from zhenxun.services.ai.run.blackboard import BlackboardManager
|
||||
from zhenxun.services.ai.tools.providers.builtin.blackboard import (
|
||||
BlackboardToolkit,
|
||||
)
|
||||
if blackboard is not None:
|
||||
schema = None
|
||||
initial_state = None
|
||||
if isinstance(blackboard, type) and issubclass(blackboard, BaseModel):
|
||||
schema = blackboard
|
||||
elif isinstance(blackboard, BaseModel):
|
||||
schema = type(blackboard)
|
||||
initial_state = blackboard
|
||||
else:
|
||||
raise ValueError(
|
||||
"blackboard 参数必须是 Pydantic BaseModel 的子类(类型)或其实例"
|
||||
)
|
||||
|
||||
self.blackboard = BlackboardManager(
|
||||
schema=blackboard_schema, initial_state=initial_blackboard_state
|
||||
schema=schema, initial_state=initial_state
|
||||
)
|
||||
self.bb_toolkit = BlackboardToolkit(self.blackboard)
|
||||
self.leader_tools.append(self.bb_toolkit)
|
||||
@@ -493,9 +506,6 @@ class TaskStrategy(BaseTeamStrategy):
|
||||
context: RunContext,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator[TeamAction, Any]:
|
||||
from zhenxun.services.ai.flow.team.models import TaskBoardState, TaskNodeStatus
|
||||
from zhenxun.services.ai.flow.team.task_tools import TaskPlanningToolkit
|
||||
|
||||
if self.blackboard is not None:
|
||||
context.session.blackboard = self.blackboard
|
||||
|
||||
@@ -541,9 +551,7 @@ class TaskStrategy(BaseTeamStrategy):
|
||||
)
|
||||
|
||||
if "__task_board__" not in context.session.shared_state:
|
||||
context.session.shared_state["__task_board__"] = (
|
||||
self.blackboard._state if self.blackboard else TaskBoardState()
|
||||
)
|
||||
context.session.shared_state["__task_board__"] = TaskBoardState()
|
||||
board = cast(TaskBoardState, context.session.shared_state["__task_board__"])
|
||||
|
||||
max_iterations = self.max_iterations
|
||||
@@ -576,15 +584,17 @@ class TaskStrategy(BaseTeamStrategy):
|
||||
请检查是否有 failed 的任务需要修复重新指派？或者如果所有任务均已 completed，
|
||||
请立刻调用 `mark_all_complete` 汇报总结。"""
|
||||
|
||||
logger.info(f"🧠 [TaskStrategy] 唤醒 Planner (Iter: {iteration})")
|
||||
leader_res = yield CallAction(agent=leader_agent, task=planner_prompt)
|
||||
logger.debug(f"🧠 [TaskStrategy] 唤醒 Planner (Iter: {iteration})")
|
||||
leader_res = yield CallAction(
|
||||
agent=leader_agent, task=planner_prompt or ""
|
||||
)
|
||||
|
||||
if board.is_goal_complete:
|
||||
yield FinishAction(result=board.final_summary or leader_res.output)
|
||||
return
|
||||
continue
|
||||
|
||||
logger.info(
|
||||
logger.debug(
|
||||
f"🚀 [TaskStrategy] 引擎接管：并发执行 {len(available_tasks)} 个任务..."
|
||||
)
|
||||
actions = []
|
||||
|
||||
@@ -6,8 +6,8 @@ from zhenxun.services.ai.flow.base import BaseRunnable
|
||||
from zhenxun.services.ai.run.context import RunContext
|
||||
from zhenxun.services.ai.tools.core.decorators import tool
|
||||
from zhenxun.services.ai.tools.core.toolkit import BaseToolkit
|
||||
from zhenxun.services.ai.tools.models import ToolResult
|
||||
from zhenxun.services.log import logger
|
||||
from zhenxun.services.ai.tools.models import EndRunResult, ToolResult
|
||||
from zhenxun.services.ai.utils.logger import log_team as logger
|
||||
|
||||
from .models import TaskBoardState, TaskNodeStatus
|
||||
|
||||
@@ -188,8 +188,6 @@ class TaskPlanningToolkit(BaseToolkit):
|
||||
],
|
||||
context: RunContext,
|
||||
) -> ToolResult:
|
||||
from zhenxun.services.ai.tools.models import EndRunResult
|
||||
|
||||
board = self._get_board(context)
|
||||
board.is_goal_complete = True
|
||||
board.final_summary = summary
|
||||
|
||||
@@ -1,27 +1,42 @@
|
||||
import asyncio
|
||||
from collections.abc import Callable, Mapping, Sequence
|
||||
import contextlib
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
from typing_extensions import Self
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from zhenxun.services.ai.capabilities import AbstractCapability, DynamicCapability
|
||||
from zhenxun.services.ai.capabilities import (
|
||||
AbstractCapability,
|
||||
CapabilitySource,
|
||||
DynamicCapability,
|
||||
)
|
||||
from zhenxun.services.ai.core.exceptions import ConcurrencyInterruptException
|
||||
from zhenxun.services.ai.core.messages import PromptInput
|
||||
from zhenxun.services.ai.core.models import CancellationToken
|
||||
from zhenxun.services.ai.core.stream_events import EventBus
|
||||
from zhenxun.services.ai.flow.agent.agent import CapabilitySource, ToolSource
|
||||
from zhenxun.services.ai.flow.agent.agent import ToolSource
|
||||
from zhenxun.services.ai.flow.agent.models import Persona
|
||||
from zhenxun.services.ai.flow.base import BaseRunnable
|
||||
from zhenxun.services.ai.flow.team.models import TeamRuntimeConfig, Transition
|
||||
from zhenxun.services.ai.flow.team.router import BaseRouter
|
||||
from zhenxun.services.ai.flow.team.strategy import (
|
||||
from zhenxun.services.ai.flow.base import BaseRunnable, ConcurrencyPolicy
|
||||
from zhenxun.services.ai.flow.concurrency import apply_concurrency_policy
|
||||
from zhenxun.services.ai.run import (
|
||||
AgentRunResult,
|
||||
AgentTask,
|
||||
RunContext,
|
||||
StreamedRunResult,
|
||||
)
|
||||
from zhenxun.services.ai.run.models import AgentRunError
|
||||
from zhenxun.services.ai.tools.providers.skills.capabilities import SkillCapability
|
||||
from zhenxun.services.ai.tools.providers.skills.models import Skill, SkillSource
|
||||
from zhenxun.services.ai.utils import ContextUtils
|
||||
from zhenxun.utils.utils import infer_plugin_namespace
|
||||
|
||||
from .models import TeamRuntimeConfig, Transition
|
||||
from .router import BaseRouter
|
||||
from .strategy import (
|
||||
BaseTeamStrategy,
|
||||
)
|
||||
from zhenxun.services.ai.run import AgentRunResult, AgentTask, RunContext
|
||||
from zhenxun.services.ai.tools.providers.skills.models import Skill, SkillSource
|
||||
from zhenxun.utils.utils import infer_plugin_namespace
|
||||
|
||||
|
||||
class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
@@ -115,6 +130,7 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model: str | None = None,
|
||||
leader_tools: list[ToolSource] | None = None,
|
||||
custom_prompt: str | None = None,
|
||||
max_handoffs: int = 3,
|
||||
) -> Self:
|
||||
"""
|
||||
应用路由策略，基于挂载的 Router 进行最合适的专家动态分发。
|
||||
@@ -128,8 +144,9 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model: 路由节点 (Leader) 使用的大模型名称，若为空则默认继承全局。
|
||||
leader_tools: 挂载给路由节点 (Leader) 的专属工具列表。
|
||||
custom_prompt: 自定义系统提示词，用于覆盖默认的路由系统提示词。
|
||||
max_handoffs: 同一会话中允许连续移交的最大次数，防止无限踢皮球。
|
||||
"""
|
||||
from zhenxun.services.ai.flow.team.strategy import RouteStrategy
|
||||
from .strategy import RouteStrategy
|
||||
|
||||
self.strategy = RouteStrategy(
|
||||
state_flow=state_flow,
|
||||
@@ -138,6 +155,7 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model=leader_model,
|
||||
leader_tools=leader_tools,
|
||||
custom_prompt=custom_prompt,
|
||||
max_handoffs=max_handoffs,
|
||||
)
|
||||
self.selector_func = selector_func
|
||||
return self
|
||||
@@ -147,6 +165,7 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model: str | None = None,
|
||||
leader_tools: list[ToolSource] | None = None,
|
||||
custom_prompt: str | None = None,
|
||||
max_delegations: int = 3,
|
||||
) -> Self:
|
||||
"""
|
||||
应用协作策略，Leader 自主规划并主动将子任务委派给 Sub-Agents，最后汇总结果。
|
||||
@@ -158,13 +177,15 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model: 协调节点 (Leader) 使用的大模型名称，若为空则默认继承全局。
|
||||
leader_tools: 挂载给协调节点 (Leader) 的专属附加工具列表。
|
||||
custom_prompt: 自定义系统提示词，用于覆盖默认的协调系统提示词。
|
||||
max_delegations: 允许向同一个专员连续委派失败的最大重试次数。
|
||||
"""
|
||||
from zhenxun.services.ai.flow.team.strategy import CoordinateStrategy
|
||||
from .strategy import CoordinateStrategy
|
||||
|
||||
self.strategy = CoordinateStrategy(
|
||||
leader_model=leader_model,
|
||||
leader_tools=leader_tools,
|
||||
custom_prompt=custom_prompt,
|
||||
max_delegations=max_delegations,
|
||||
)
|
||||
return self
|
||||
|
||||
@@ -184,7 +205,7 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_tools: 挂载给总结节点 (Leader) 的专属附加工具列表。
|
||||
custom_prompt: 自定义系统提示词，用于覆盖默认的广播总结系统提示词。
|
||||
"""
|
||||
from zhenxun.services.ai.flow.team.strategy import BroadcastStrategy
|
||||
from .strategy import BroadcastStrategy
|
||||
|
||||
self.strategy = BroadcastStrategy(
|
||||
leader_model=leader_model,
|
||||
@@ -198,8 +219,7 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model: str | None = None,
|
||||
leader_tools: list[ToolSource] | None = None,
|
||||
max_iterations: int = 15,
|
||||
blackboard_schema: type[BaseModel] | None = None,
|
||||
initial_blackboard_state: BaseModel | None = None,
|
||||
blackboard: type[BaseModel] | BaseModel | None = None,
|
||||
custom_prompt: str | None = None,
|
||||
) -> Self:
|
||||
"""
|
||||
@@ -213,18 +233,16 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
leader_model: 规划节点 (Leader) 使用的大模型名称，若为空则默认继承全局。
|
||||
leader_tools: 挂载给规划节点 (Leader) 的专属附加工具列表。
|
||||
max_iterations: 引擎驱动的状态机最大迭代/循环次数，防止死循环。
|
||||
blackboard_schema: 团队共享黑板的数据结构类型 (Pydantic Model 类)。
|
||||
initial_blackboard_state: 共享黑板的初始数据状态实例。
|
||||
blackboard: (可选) 团队共享黑板。可传入 Schema 类型类，或直接传入带有初始数据的 Schema 实例对象。
|
||||
custom_prompt: 自定义系统提示词，用于覆盖默认的规划系统提示词。
|
||||
"""
|
||||
from zhenxun.services.ai.flow.team.strategy import TaskStrategy
|
||||
""" # noqa: E501
|
||||
from .strategy import TaskStrategy
|
||||
|
||||
self.strategy = TaskStrategy(
|
||||
leader_model=leader_model,
|
||||
leader_tools=leader_tools,
|
||||
max_iterations=max_iterations,
|
||||
blackboard_schema=blackboard_schema,
|
||||
initial_blackboard_state=initial_blackboard_state,
|
||||
blackboard=blackboard,
|
||||
custom_prompt=custom_prompt,
|
||||
)
|
||||
return self
|
||||
@@ -260,10 +278,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
"""
|
||||
self._ensure_strategy()
|
||||
if skills:
|
||||
from zhenxun.services.ai.tools.providers.skills.capabilities import (
|
||||
SkillCapability,
|
||||
)
|
||||
|
||||
capabilities = list(capabilities) if capabilities else []
|
||||
capabilities.append(
|
||||
SkillCapability(skills=skills, namespace=self.namespace)
|
||||
@@ -273,8 +287,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
prompt=prompt, context=context, capabilities=capabilities, **kwargs
|
||||
)
|
||||
|
||||
import contextlib
|
||||
|
||||
@contextlib.asynccontextmanager
|
||||
async def run_stream(
|
||||
self,
|
||||
@@ -297,10 +309,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
context.capabilities.extend(self.capabilities)
|
||||
|
||||
if skills:
|
||||
from zhenxun.services.ai.tools.providers.skills.capabilities import (
|
||||
SkillCapability,
|
||||
)
|
||||
|
||||
capabilities = list(capabilities) if capabilities else []
|
||||
capabilities.append(
|
||||
SkillCapability(skills=skills, namespace=self.namespace)
|
||||
@@ -313,8 +321,7 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
elif callable(cap):
|
||||
context.capabilities.append(DynamicCapability(cap))
|
||||
|
||||
from zhenxun.services.ai.flow.team.runner import TeamRunner
|
||||
from zhenxun.services.ai.run import StreamedRunResult
|
||||
from .runner import TeamRunner
|
||||
|
||||
event_bus = EventBus()
|
||||
context.run.event_bus = event_bus
|
||||
@@ -323,8 +330,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
|
||||
policy = getattr(self.runtime_config, "concurrency_policy", None)
|
||||
if policy is None:
|
||||
from zhenxun.services.ai.flow.base import ConcurrencyPolicy
|
||||
|
||||
policy = (
|
||||
ConcurrencyPolicy.ALLOW
|
||||
if getattr(self.runtime_config, "stateless", True)
|
||||
@@ -333,8 +338,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
|
||||
intervention_policy = getattr(self.runtime_config, "intervention_policy", None)
|
||||
|
||||
from zhenxun.services.ai.utils import ContextUtils
|
||||
|
||||
lock_id = ContextUtils.extract_concurrency_lock_id(
|
||||
context,
|
||||
getattr(self.runtime_config, "concurrency_scope", None),
|
||||
@@ -342,8 +345,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
)
|
||||
|
||||
async def _execution_task():
|
||||
from zhenxun.services.ai.flow.concurrency import apply_concurrency_policy
|
||||
|
||||
cancel_token = context.run.cancellation_token or CancellationToken()
|
||||
context.run.cancellation_token = cancel_token
|
||||
|
||||
@@ -359,8 +360,6 @@ class Team(BaseRunnable[AgentRunResult[Any]]):
|
||||
async for event in runner.run_stream(prompt, context, **kwargs):
|
||||
await event_bus.emit(event)
|
||||
except BaseException as e:
|
||||
from zhenxun.services.ai.run.models import AgentRunError
|
||||
|
||||
if isinstance(e, asyncio.CancelledError):
|
||||
e = ConcurrencyInterruptException("团队执行已被新请求打断并接管")
|
||||
await event_bus.emit(AgentRunError(error=e))
|
||||
|
||||
Reference in New Issue
Block a user