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* ♻️ refactor(core): 重构 AI 编排框架与记忆及 RAG 子系统 - 【重构】重构 `BaseRunnable` 并引入统一的 `RunIntent` 意图载体，规范 Agent、Team 和 Workflow 的执行流 - 【解耦】将中期记忆槽和长期向量记忆从 `MemoryConfig` 中解耦，转为独立的能力组件与工具箱进行管理 - 【记忆】移除 `MemoryReader` 和 `MemoryWriter`，统一封装为 `SessionMemoryContext` 会话记忆门面 - 【RAG】重构检索器与存储后端接口，统一采用 `QueryRequest` 进行多维度联合检索，并引入 `InMemoryScorer` 提升打分性能 - 【事件】优化 `EventBus` 异步事件分发机制，引入队列机制确保事件按序处理，避免并发竞态问题 - 【依赖注入】移除 `memory` 注入项，优化 `DependencyInjector` 的签名解析缓存以提升性能 * 🚨 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>
284 lines
10 KiB
Python
284 lines
10 KiB
Python
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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import uuid
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from pydantic import BaseModel, ConfigDict, Field
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from zhenxun.services.ai.core.messages import AgentMessage, PromptInput
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from zhenxun.services.ai.core.options import BaseOutputDefinition
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from zhenxun.services.ai.flow.core.base import BaseRunnable
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from zhenxun.services.ai.flow.core.models import BaseRuntimeConfig
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from zhenxun.services.ai.run import AgentTask
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class TeamRuntimeConfig(BaseRuntimeConfig):
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"""Team 专属的运行时配置"""
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leader_enable_hitl: bool = Field(default=False)
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"""是否允许团队的隐式 Leader / Router 发起人机求助 (Human-in-the-Loop)"""
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class RouteDecision(BaseModel):
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"""大模型动态路由决策的数据契约"""
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target_name: str
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"""选定的最合适的团队成员名称"""
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reason: str = ""
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"""选择该成员的详细理由"""
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context_data: Any = ""
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"""传递的上下文载荷"""
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class Transition(BaseModel):
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"""
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声明式移交契约。
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用于定义 Team 模式下，智能体之间转移控制权的条件和目标。
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"""
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target: str
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"""目标智能体的名称"""
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description: str = ""
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"""自然语言描述的移交条件（提供给大模型 LLMRouter 思考时使用）"""
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input_schema: type[BaseModel] | BaseOutputDefinition | None = None
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"""(可选) 强类型的输入约束。如果设置，
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LLMRouter 决定移交时必须且只能生成符合该 Schema 的 JSON 参数，
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并作为 context_data 传递。"""
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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[..., 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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class TeamAction(BaseModel):
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"""多智能体团队协作动作基类"""
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model_config = ConfigDict(arbitrary_types_allowed=True)
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class CallAction(TeamAction):
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"""
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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 | 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: PromptInput | 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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kwargs: dict[str, Any] | None = None
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"""其他透传给 Agent.run_stream 的 kwargs（可选）"""
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class ConcurrentCallAction(TeamAction):
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"""
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并发调度动作：同时呼叫多个 Agent 执行任务
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"""
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actions: list[CallAction]
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"""并发执行的呼叫动作列表"""
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class FinishAction(TeamAction):
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"""
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结束动作：团队协作完成，返回最终结果
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"""
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result: Any
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"""团队协作的最终产出"""
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class TaskNodeStatus(str, Enum):
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"""团队自主任务节点状态枚举"""
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pending = "pending"
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"""待处理：所有前置依赖已完成，等待分配执行"""
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in_progress = "in_progress"
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"""进行中：正在被 Member Agent 执行"""
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completed = "completed"
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"""已完成：执行成功"""
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failed = "failed"
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"""已失败：执行报错或由于前置依赖失败而自动失败"""
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blocked = "blocked"
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"""阻塞中：有前置依赖任务尚未完成"""
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class SubTaskRecord(BaseModel):
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"""单条子任务（工单）数据契约"""
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id: str = Field(default_factory=lambda: str(uuid.uuid4())[:8])
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"""子任务的唯一标识 ID"""
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title: str = ""
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"""子任务标题"""
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description: str = ""
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"""子任务的具体描述"""
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assignee: str | None = None
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"""执行该任务的指派成员 Agent 名称"""
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dependencies: list[str] = Field(default_factory=list)
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"""该任务依赖的前置任务 ID 列表"""
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status: TaskNodeStatus = TaskNodeStatus.pending
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"""任务的当前执行状态"""
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result: str | None = None
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"""任务执行结果或输出信息"""
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notes: list[str] = Field(default_factory=list)
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"""执行过程中的追加备注或错误记录"""
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metadata: dict[str, Any] = Field(default_factory=dict)
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"""附加元数据，供系统底层或第三方插件挂载隐式上下文，对大模型不可见"""
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class TaskBoardState(BaseModel):
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"""
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Team 自主任务模式下的全局共享黑板状态 (Task Board)。
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提供任务的 CRUD、依赖拓扑计算和格式化渲染功能。
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"""
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tasks: list[SubTaskRecord] = Field(default_factory=list)
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"""看板中存储的所有子任务记录列表"""
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is_goal_complete: bool = False
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"""团队的终极目标是否已宣告完成"""
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final_summary: str | None = None
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"""目标完成后的终结总结报告"""
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def create_task(
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self,
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title: str,
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description: str = "",
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assignee: str | None = None,
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dependencies: list[str] | None = None,
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metadata: dict[str, Any] | None = None,
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) -> SubTaskRecord:
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"""创建一个新任务并加入看板。Python 引擎和 Tool 均调用此方法。"""
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clean_deps = [d for d in (dependencies or []) if d.strip()]
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task = SubTaskRecord(
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title=title,
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description=description,
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assignee=assignee,
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dependencies=clean_deps,
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metadata=metadata or {},
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)
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self.tasks.append(task)
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self._update_blocked_statuses()
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return task
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def get_task(self, task_id: str) -> SubTaskRecord | None:
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"""根据 ID 或标题获取对应的子任务记录"""
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return next(
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(t for t in self.tasks if t.id == task_id or t.title == task_id), None
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)
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def update_task_status(
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self, task_id: str, status: TaskNodeStatus, result: str | None = None
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) -> SubTaskRecord | None:
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"""更新指定任务的状态以及执行结果"""
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task = self.get_task(task_id)
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if not task:
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return None
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task.status = status
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if result is not None:
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task.result = result
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self._update_blocked_statuses()
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return task
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def _is_blocked(self, task: SubTaskRecord) -> bool:
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"""检查该任务是否有尚未完成的前置依赖"""
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if not task.dependencies:
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return False
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for dep_id in task.dependencies:
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dep = self.get_task(dep_id)
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if dep is None:
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return True
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if dep.status != TaskNodeStatus.completed:
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return True
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return False
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def _has_failed_dependency(self, task: SubTaskRecord) -> bool:
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"""检查该任务是否有已经失败的前置依赖"""
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if not task.dependencies:
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return False
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for dep_id in task.dependencies:
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dep = self.get_task(dep_id)
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if dep is not None and dep.status == TaskNodeStatus.failed:
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return True
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return False
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def _update_blocked_statuses(self) -> None:
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"""重新计算所有未终结任务的阻塞状态 (基于拓扑依赖)"""
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for task in self.tasks:
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if task.status == TaskNodeStatus.blocked:
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if self._has_failed_dependency(task):
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task.status = TaskNodeStatus.failed
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task.result = "自动标记失败: 前置依赖任务已失败。"
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elif not self._is_blocked(task):
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task.status = TaskNodeStatus.pending
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elif task.status == TaskNodeStatus.pending:
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if self._has_failed_dependency(task):
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task.status = TaskNodeStatus.failed
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task.result = "自动标记失败: 前置依赖任务已失败。"
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elif self._is_blocked(task):
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task.status = TaskNodeStatus.blocked
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def get_available_tasks(
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self, for_assignee: str | None = None
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) -> list[SubTaskRecord]:
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"""获取所有当前无依赖阻塞、可立即执行的 Pending 任务"""
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available = []
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for task in self.tasks:
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if task.status != TaskNodeStatus.pending:
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continue
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if self._is_blocked(task):
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continue
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if for_assignee and task.assignee and task.assignee != for_assignee:
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continue
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available.append(task)
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return available
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def all_terminal(self) -> bool:
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"""检查是否所有的任务均已进入终结状态（已完成或已失败）"""
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if not self.tasks:
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return False
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return all(
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t.status in (TaskNodeStatus.completed, TaskNodeStatus.failed)
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for t in self.tasks
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)
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def render_board_to_string(self) -> str:
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"""渲染供 LLM 阅读的 Markdown 看板战报"""
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if not self.tasks:
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return "目前尚未创建任何任务。"
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counts: dict[str, int] = {}
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for t in self.tasks:
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counts[t.status.value] = counts.get(t.status.value, 0) + 1
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parts = [f"{v} {k}" for k, v in counts.items()]
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header = (
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f"### 📋 任务状态总览 (共计 {len(self.tasks)} 个任务: {', '.join(parts)}):"
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)
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lines = [header]
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for t in self.tasks:
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status_str = t.status.value.upper()
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assignee_str = f" (指派给: {t.assignee})" if t.assignee else " (尚未指派)"
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lines.append(f" [{t.id}] {t.title} - {status_str}{assignee_str}")
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if t.dependencies:
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lines.append(f" 依赖于: {t.dependencies}")
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if t.result:
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result_preview = (
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t.result[:1000] + "..." if len(t.result) > 1000 else t.result
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)
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lines.append(f" 结果: {result_preview}")
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if t.notes:
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for note in t.notes[-3:]:
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lines.append(f" 附注: {note}")
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if self.is_goal_complete and self.final_summary:
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lines.append(f"\n✅ 终极目标已标记完成: {self.final_summary}")
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return "<current_task_state>\n" + "\n".join(lines) + "\n</current_task_state>"
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