Files
zhenxun_bot/zhenxun/services/ai/flow/team/runner.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

239 lines
8.9 KiB
Python

import asyncio
from collections.abc import AsyncGenerator
from typing import Any
from zhenxun.services.ai.core.exceptions import (
AbortException,
ControlFlowExit,
LLMException,
)
from zhenxun.services.ai.core.messages import UsageInfo
from zhenxun.services.ai.flow.team.capabilities import TeamRoutingCapability
from zhenxun.services.ai.flow.team.models import (
CallAction,
ConcurrentCallAction,
FinishAction,
)
from zhenxun.services.ai.flow.team.strategy import BaseTeamStrategy
from zhenxun.services.ai.run import AgentRunResult, RunContext
from zhenxun.services.ai.run.models import AgentRunEnd
from zhenxun.services.log import logger
from zhenxun.utils.pydantic_compat import model_construct
class TeamRunner:
"""
多智能体团队核心执行引擎。
"""
def __init__(self, team: Any, strategy: BaseTeamStrategy):
self.team = team
self.strategy = strategy
async def _execute_call_action_to_queue(
self,
index: int,
action: CallAction,
context: RunContext,
session_id: str,
queue: asyncio.Queue,
):
"""
辅助方法:执行单一 Agent 任务,
并将内部产生的 UI 事件与最终结果通过队列透传回主线程
"""
if isinstance(action.agent, str):
target_agent = next(
(m for m in self.team.members if m.name == action.agent), None
)
if not target_agent:
logger.error(f"❌ [TeamRunner] 找不到团队成员: {action.agent}")
await queue.put(
(
"result",
(
action.agent,
AgentRunResult(
output=f"Error: {action.agent} not found",
usage=UsageInfo(),
),
),
)
)
return
else:
target_agent = action.agent
sub_context = context.clone_for_member(target_agent.name)
sub_context.capabilities = list(sub_context.capabilities)
from zhenxun.services.ai.flow.team.strategy import RouteStrategy
if isinstance(self.strategy, RouteStrategy):
routing_cap = TeamRoutingCapability(
team_name=self.team.name,
members=self.team.members,
state_flow=getattr(self.strategy, "state_flow", None),
)
sub_context.capabilities.append(routing_cap)
logger.debug(f"🚀 **专员 👨💼`{target_agent.name}`** 开始执行子任务...")
agent_res = None
try:
from zhenxun.services.ai.flow.agent.models import AgentConfig
async with target_agent.run_stream(
prompt=action.task,
context=sub_context,
config=AgentConfig(message_history=action.history),
**(action.kwargs or {}),
) as stream_result:
async for event in stream_result.stream_events():
if isinstance(event, AgentRunEnd):
agent_res = event.result
else:
await queue.put(("yield_event", event))
except ControlFlowExit as cfe:
if isinstance(cfe, AbortException):
await queue.put(("control_flow_error", cfe))
return
else:
logger.debug(
f"Agent {target_agent.name} 触发局部控制流: "
f"{type(cfe).__name__} - {cfe}"
)
agent_res = AgentRunResult(output=str(cfe), usage=UsageInfo())
except Exception as e:
logger.error(f"Agent {target_agent.name} 执行崩溃: {e}")
if isinstance(e, LLMException):
abort_msg = getattr(e, "user_friendly_message", str(e))
display_msg = (
f"❌ 智能体 {target_agent.name} 执行发生致命故障: {abort_msg}"
)
abort_err = AbortException(
reason=str(e),
display=display_msg,
)
await queue.put(("control_flow_error", abort_err))
return
agent_res = AgentRunResult(output=f"Error: {e}", usage=UsageInfo())
if agent_res and agent_res.handoff:
target_name = agent_res.handoff.target
reason = agent_res.handoff.reason
logger.info(
f"🛣️ **路由决策**: 委派给专员 👨💼`{target_name}` (理由: {reason})"
)
if not agent_res:
agent_res = AgentRunResult(
output="Error: No result returned", usage=UsageInfo()
)
logger.debug(f"✅ **专员 👨💼`{target_agent.name}`** 完成任务!")
await queue.put(("result", index, target_agent.name, agent_res))
async def run_stream(
self, prompt: Any, context: RunContext, **kwargs: Any
) -> AsyncGenerator[Any, None]:
session_id = context.session_id or "default_team_session"
task_desc = getattr(prompt, "description", str(prompt))
logger.info(f"🤝 **团队 [{self.team.name}] 开始协作**: `{task_desc}`")
plan_gen = self.strategy.generate_plan(self.team, prompt, context, **kwargs)
send_value = None
final_result = None
cumulative_usage = UsageInfo()
try:
while True:
try:
action = await plan_gen.asend(send_value)
except StopAsyncIteration:
break
if isinstance(action, CallAction):
queue = asyncio.Queue()
task = asyncio.create_task(
self._execute_call_action_to_queue(
0, action, context, session_id, queue
)
)
try:
while True:
msg_type, *payload = await queue.get()
if msg_type == "yield_event":
yield payload[0]
elif msg_type == "control_flow_error":
raise payload[0]
elif msg_type == "result":
idx, agent_name, agent_res = payload
send_value = agent_res
cumulative_usage += agent_res.usage
break
finally:
if not task.done():
task.cancel()
elif isinstance(action, ConcurrentCallAction):
queue = asyncio.Queue()
tasks = []
for i, act in enumerate(action.actions):
tasks.append(
asyncio.create_task(
self._execute_call_action_to_queue(
i, act, context, session_id, queue
)
)
)
results_dict = {}
try:
while len(results_dict) < len(action.actions):
msg_type, *payload = await queue.get()
if msg_type == "yield_event":
yield payload[0]
elif msg_type == "control_flow_error":
for t in tasks:
t.cancel()
raise payload[0]
elif msg_type == "result":
idx, agent_name, agent_res = payload
results_dict[idx] = (agent_name, agent_res)
cumulative_usage += agent_res.usage
send_value = [
results_dict[i] for i in range(len(action.actions))
]
finally:
for task in tasks:
if not task.done():
task.cancel()
elif isinstance(action, FinishAction):
final_result = action.result
break
else:
raise ValueError(f"TeamRunner 遇到了未知的动作类型: {type(action)}")
except Exception as e:
raise e
logger.info(f"🏁 **团队 [{self.team.name}]** 协作圆满结束!")
if not isinstance(final_result, AgentRunResult):
final_result = model_construct(
AgentRunResult, output=final_result, usage=cumulative_usage
)
else:
final_result.usage += cumulative_usage
yield AgentRunEnd(result=final_result)