feat(agent): 实现委派工具重构,支持子代理和代理团队模式

- 新增 spawn_subagent 和 spawn_agent_team 工具,替代原有的 spawn 工具
- 重构 DelegationManager 以支持单个子代理和代理团队两种委派模式
- 更新系统提示词中的委派策略说明,明确使用场景和区别
- 添加技能上下文传递功能,确保委派任务遵循指定技能
- 实现代理内部的受控下游委派机制,防止无限嵌套
- 更新工具注册和上下文设置逻辑以适配新架构
This commit is contained in:
2026-03-30 17:21:39 +08:00
parent 29dfd14aa6
commit fee9007da6
6 changed files with 490 additions and 90 deletions

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@ -1,4 +1,4 @@
"""spawn 工具:用于把任务委派给后台 agent"""
"""委派工具:分别暴露 subagent 与 agent team 两种调用接口"""
from typing import TYPE_CHECKING, Any
@ -8,74 +8,178 @@ if TYPE_CHECKING:
from nanobot.agent.delegation import DelegationManager
class SpawnTool(Tool):
"""
后台委派工具。
作用:
1. 把耗时/可并行的任务委派给 DelegationManager
2. 目标可以是本地 agent、A2A 远端 agent 或 agent group
3. 后台任务异步执行,不阻塞当前对话回合。
"""
class DelegationTool(Tool):
"""委派类工具的公共上下文注入逻辑。"""
def __init__(self, manager: "DelegationManager"):
# manager 负责真正创建 asyncio 后台任务并管理生命周期。
self._manager = manager
# 默认来源会话CLI 直连场景)。实际会在每轮由 loop._set_tool_context 覆盖。
self._origin_channel = "cli"
self._origin_chat_id = "direct"
self._announce_via_bus = True
def set_context(self, channel: str, chat_id: str, announce_via_bus: bool = True) -> None:
"""设置后台委派结果回传的目标会话。"""
# 委派任务完成后并不会直接给用户发消息,
# 而是把结果发回这里记录的 originchannel/chat_id对应会话。
self._origin_channel = channel
self._origin_chat_id = chat_id
self._announce_via_bus = announce_via_bus
class SpawnSubagentTool(DelegationTool):
"""把任务委派给单个 subagent。"""
@property
def name(self) -> str:
# 暴露给 LLM 的工具名;模型会用这个名字发起 function call。
return "spawn"
return "spawn_subagent"
@property
def description(self) -> str:
# 给模型看的能力描述,强调“后台执行 + 完成后回报”语义。
return (
"Delegate a task to a background agent. "
"Delegate a focused task to one background subagent. "
"Use this for complex or time-consuming work that can run independently. "
"You can target a specific agent, a group of agents, or let the system choose. "
"The delegated agent(s) will report back when done."
"You only provide the task and optional required skills; downstream routing decides the concrete agent. "
"The subagent will report back when done."
)
@property
def parameters(self) -> dict[str, Any]:
# OpenAI function schema定义模型可传入的参数结构。
return {
"type": "object",
"properties": {
"task": {
"type": "string",
"description": "The task for the delegated agent to complete",
"description": "The task for the delegated subagent to complete",
},
"label": {
"type": "string",
"description": "Optional short label for the task (for display)",
},
"target": {
"type": "string",
"description": "Optional agent ID or name for a single target",
},
"targets": {
"skills": {
"type": "array",
"items": {"type": "string"},
"description": "Optional list of agent IDs/names for a group task",
"description": "Optional list of skill names the delegated worker must follow",
},
},
"required": ["task"],
}
async def execute(
self,
task: str,
label: str | None = None,
skills: list[str] | None = None,
**kwargs: Any,
) -> str:
"""创建并启动一个 subagent 后台任务。"""
return await self._manager.dispatch_subagent(
task=task,
label=label,
skills=skills,
origin_channel=self._origin_channel,
origin_chat_id=self._origin_chat_id,
announce_via_bus=self._announce_via_bus,
)
class SpawnAgentTeamTool(DelegationTool):
"""启动一个 agent team 任务。"""
@property
def name(self) -> str:
return "spawn_agent_team"
@property
def description(self) -> str:
return (
"Start an agent team for parallel exploration. "
"Use this when multiple agents should investigate the task in parallel and return a combined result. "
"You only provide the task and optional required skills; downstream routing selects the concrete members."
)
@property
def parameters(self) -> dict[str, Any]:
return {
"type": "object",
"properties": {
"task": {
"type": "string",
"description": "The shared task for the agent team",
},
"label": {
"type": "string",
"description": "Optional short label for the team task (for display)",
},
"skills": {
"type": "array",
"items": {"type": "string"},
"description": "Optional list of skill names the team must follow",
},
},
"required": ["task"],
}
async def execute(
self,
task: str,
label: str | None = None,
skills: list[str] | None = None,
**kwargs: Any,
) -> str:
"""创建并启动一个 agent team 后台任务。"""
return await self._manager.dispatch_agent_team(
task=task,
label=label,
skills=skills,
origin_channel=self._origin_channel,
origin_chat_id=self._origin_chat_id,
announce_via_bus=self._announce_via_bus,
)
class NestedDelegateTool(Tool):
"""供 delegated worker 使用的受控下游委派工具。"""
def __init__(self, manager: "DelegationManager", default_skills: list[str] | None = None):
self._manager = manager
self._default_skills = [str(item).strip() for item in (default_skills or []) if str(item).strip()]
@property
def name(self) -> str:
return "delegate_task"
@property
def description(self) -> str:
return (
"Synchronously delegate a downstream task from a delegated worker. "
"Use this only when specialized help is needed. "
"It can route to an A2A agent or an ephemeral local subagent, but never creates a persistent subagent."
)
@property
def parameters(self) -> dict[str, Any]:
return {
"type": "object",
"properties": {
"task": {
"type": "string",
"description": "The downstream task to delegate",
},
"label": {
"type": "string",
"description": "Optional short label for the downstream task",
},
"target": {
"type": "string",
"description": "Optional agent ID or name for the downstream worker",
},
"strategy": {
"type": "string",
"enum": ["auto", "local", "plugin", "a2a", "group"],
"description": "Routing strategy. Default is auto.",
"enum": ["auto", "a2a", "ephemeral_subagent"],
"description": "Routing strategy for downstream delegation. Default is auto.",
},
"skills": {
"type": "array",
"items": {"type": "string"},
"description": "Optional required skills for the downstream delegate. Defaults to the current worker's required skills.",
},
},
"required": ["task"],
@ -86,20 +190,15 @@ class SpawnTool(Tool):
task: str,
label: str | None = None,
target: str | None = None,
targets: list[str] | None = None,
strategy: str = "auto",
skills: list[str] | None = None,
**kwargs: Any,
) -> str:
"""创建并启动一个后台委派任务"""
# 这里仅负责转发请求,不在本工具内执行实际任务逻辑。
# 返回值是“已启动”状态文本,真正结果稍后通过主消息总线回传。
return await self._manager.dispatch(
"""同步执行一次受控下游委派,并把结果返回给当前 worker"""
return await self._manager.delegate_for_subagent(
task=task,
label=label,
target=target,
targets=targets,
strategy=strategy,
origin_channel=self._origin_channel,
origin_chat_id=self._origin_chat_id,
announce_via_bus=self._announce_via_bus,
skills=skills if skills is not None else list(self._default_skills),
)