mirror of
https://github.com/ThearchyHelios/AgentLab.git
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ThearchyHelios
c980da65d0
库里 28 条 failed 的构成说明了为什么值得单独开这条路：
模型 id 写错（404） 7
循环条件语法错 3
401 3
工具参数名不对 3
缺必填输入 2
大半是**配置错了**，改一下就能跑。而"改一下再跑"原来意味着整张图从头来
一遍——前面花两分钟查完的表结构、跑完的 SQL 全部重跑，尽管那些结果一直
躺在 checkpoint 里。checkpointer 本来就一直开着（thread_id = run_id），
挡住这条路的只是 resume 里的一行状态判定：它只认 interrupted，failed 进不去。
**带着改过的图续。** 不让改配置的话这功能基本没用：上面那几类续下去会
立刻再撞同一个错。所以 /runs/{id}/continue 接受一张改过的图，画布上点
「接着跑」带的就是当前编辑中的那张——用户正是改完它才点的。
**但只准改配置。** checkpoint 是按节点名存的（编译时 add_node(node.id)），
而节点配置是运行时从 spec 现读的（NodeContext.cfg）。所以只改配置对得上，
增删节点或改连线就对不上——续下去会拿着错位的通道状态跑出一份似是而非的
结果，比直接报错糟得多。加了 schema.topology_of() 做这道判据：节点 id +
类型 + 边，不含任何配置；对不上就 409，让用户重新发起。
这正是 resume 那边踩过的坑的同一类：不看有没有 checkpoint 就发 Command，
LangGraph 拿空 state 从 START 重跑，最后还落成 succeeded。所以这里也先问
一次 aget_state，没有待跑节点就拒绝，而不是硬发一个 None 下去。
时间线上要说清楚是接着跑、保了几步（"从「lp」接着跑，前面 2 个节点的结果
保留"）——否则用户看到时间线又动起来，分不清这次是续的还是整张图又跑了一遍。
验证：后端 249 passed（新增 test_continue_run.py 7 条，核心那条断言的是
node.started 事件——前面的节点确实没有再出现）。端到端真跑了一遍：
第一遍 start → prep → lp 挂在 lp，改好条件后第二遍只跑 lp → out，
成果里带着 prep 那步的结果；改了结构的图被 409 拒绝；没有失败的运行时
画布上不显示这个按钮。
顺带：_drive 里 resumed 的判定漏了 payload is None 这种（从 checkpoint
直接往下走），run.started 事件会说成不是续跑。
599 lines
25 KiB
Python
599 lines
25 KiB
Python
from __future__ import annotations
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import asyncio
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import contextlib
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import logging
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import time
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from datetime import datetime, timezone
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from typing import Any
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from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
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from langgraph.types import Command
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from sqlalchemy import select, update
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from app.core.bus import bus
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from app.core.config import settings
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from app.core.events import EventType, RunEventModel
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from app.db.base import SessionLocal
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from app.db.models import Approval, Run, RunEvent, Workflow
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from app.engine.compiler import compile_graph, initial_state
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from app.engine.context import NodeError, RunContext
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from app.engine.schema import GraphSpec, topology_of, validate_graph
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logger = logging.getLogger(__name__)
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# 流式增量（正文 token、思考 delta）量太大，只做实时推送不落库；
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# 轨迹里正文靠 node.finished 的 preview，思考靠调用结束时的单条 llm.thinking 汇总
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_EPHEMERAL = {EventType.LLM_TOKEN, EventType.LLM_THINKING_DELTA}
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class RunManager:
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"""负责一次运行的完整生命周期：启动、串流、中断、恢复、取消。"""
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def __init__(self) -> None:
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self._tasks: dict[str, asyncio.Task[None]] = {}
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self._checkpointer: AsyncSqliteSaver | None = None
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self._cm: Any = None
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self._semaphore = asyncio.Semaphore(settings.max_concurrent_runs)
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# ---------------- 生命周期 ----------------
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async def setup(self) -> None:
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settings.ensure_dirs()
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self._cm = AsyncSqliteSaver.from_conn_string(str(settings.checkpoint_path))
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self._checkpointer = await self._cm.__aenter__()
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# 上次进程被强杀时留下的记录。running 和 queued 要分开处理：
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# running 至少跑过一步、有 checkpoint，可以续；queued 还在排队，
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# 一个 checkpoint 都没写过，"恢复"它只会从 START 用默认值重跑一遍，
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# 还丢掉 run.input——那不是恢复，是伪造一份结果。
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async with SessionLocal() as session:
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await session.execute(
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update(Run)
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.where(Run.status == "running")
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.values(status="interrupted", error="服务重启，运行已挂起，可从断点恢复")
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)
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await session.execute(
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update(Run)
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.where(Run.status == "queued")
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.values(status="failed", error="服务重启时这次运行还在排队，没有可恢复的进度，请重新发起")
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)
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await session.commit()
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async def shutdown(self) -> None:
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for task in list(self._tasks.values()):
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task.cancel()
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await asyncio.gather(*self._tasks.values(), return_exceptions=True)
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if self._cm is not None:
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with contextlib.suppress(Exception):
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await self._cm.__aexit__(None, None, None)
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@property
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def checkpointer(self) -> AsyncSqliteSaver:
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if self._checkpointer is None:
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raise RuntimeError("RunManager 还没初始化")
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return self._checkpointer
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# ---------------- 事件 ----------------
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async def _emit(
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self,
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run_id: str,
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event_type: EventType | str,
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*,
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node_id: str | None = None,
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data: dict[str, Any] | None = None,
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persist: bool = True,
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) -> None:
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event = RunEventModel(
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run_id=run_id,
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seq=bus.next_seq(run_id),
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type=EventType(str(event_type)),
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node_id=node_id,
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data=data or {},
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)
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# 先落库，再广播。顺序反过来会漏事件，而且是结构性的漏：
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#
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# 订阅者的完整性靠"读历史 + 接实时"两段拼起来。它先订阅、再读历史，
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# 于是需要这条保证——**提交早于我这次 SELECT 的，在历史里；提交晚于
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# 我这次 SELECT 的，广播也晚于我订阅，在实时流里**。这条保证只有在
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# "提交先于广播"时才成立。
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#
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# 先广播的话，一条在订阅建立之前广播、却在读历史之后才提交的事件，
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# 两边都拿不到。实测跑一次 25ms 的图，六条事件里的 run.started 有
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# 一半几率就这么没了——界面表现为某个节点永远在转圈。
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if persist and event.type not in _EPHEMERAL:
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async with SessionLocal() as session:
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session.add(
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RunEvent(
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run_id=run_id,
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seq=event.seq,
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type=str(event.type),
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node_id=event.node_id,
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ts=event.ts,
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data=event.data,
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)
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)
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await session.execute(
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update(Run).where(Run.id == run_id).values(last_seq=event.seq)
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)
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await session.commit()
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await bus.publish(event)
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async def note(
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self, run_id: str, event_type: EventType | str, *, node_id: str | None = None,
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**data: Any,
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) -> None:
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"""给 API 层用的事件入口（比如 formal 启动时记录口径升版处置）。"""
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await self._emit(run_id, event_type, node_id=node_id, data=data)
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# ---------------- 启动 ----------------
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async def start(
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self,
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*,
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graph: dict[str, Any],
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input_payload: dict[str, Any],
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workflow_id: str | None = None,
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workflow_name: str = "",
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memory_scope: str = "default",
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collection: str = "default",
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run_class: str = "exploratory",
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version: int | None = None,
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version_hash: str | None = None,
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started_by: str | None = None,
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) -> Run:
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spec = GraphSpec.model_validate(graph)
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report = validate_graph(spec)
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if not report.ok:
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raise ValueError(
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"图校验未通过：" + "；".join(i.message for i in report.issues if i.level == "error")
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)
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async with SessionLocal() as session:
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run = Run(
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workflow_id=workflow_id,
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workflow_name=workflow_name,
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status="queued",
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graph=graph,
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input=input_payload,
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run_class=run_class,
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version=version,
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version_hash=version_hash,
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started_by=started_by,
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)
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run.thread_id = run.id # 一个 run 一条 checkpoint 线程
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session.add(run)
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await session.commit()
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await session.refresh(run)
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self._tasks[run.id] = asyncio.create_task(
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self._drive(
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run.id,
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spec,
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initial_state(input_payload),
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workflow_id=workflow_id,
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memory_scope=memory_scope,
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collection=collection,
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)
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)
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return run
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async def resume(
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self, run_id: str, response: Any, *, approval_id: str | None = None,
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actor: str | None = None,
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) -> Run:
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"""从人工介入的断点继续。
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两件事以前是错的：
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一是不看有没有 checkpoint 就发 Command。重启扫描会把 queued（从没跑过、
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没有任何 checkpoint）也标成 interrupted，对这种 run 发 Command，LangGraph
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会拿一个空 state 从 START 重跑整张图——run.input 完全没被注入，最后还落成
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succeeded。跑出来的是一份用默认值算的假结果。
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二是同一 superstep 里有多个 interrupt 时，只发标量 Command 会让 LangGraph
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直接抛 RuntimeError 打爆整个 run，而所有 pending 审批还都被写成同一个回复。
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现在按 interrupt_id 逐条收集，凑齐了才继续，没凑齐就继续等下一个人回复。
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"""
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async with SessionLocal() as session:
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run = await session.get(Run, run_id)
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if not run:
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raise KeyError(f"找不到运行 {run_id}")
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if run.status not in ("interrupted",):
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raise ValueError(f"当前状态是 {run.status}，无法恢复")
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spec = GraphSpec.model_validate(run.graph)
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workflow_id = run.workflow_id
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# 先问引擎：这条线程到底停在哪、还等着哪些 interrupt
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run_ctx = RunContext(run_id=run_id, thread_id=run_id, spec=spec, workflow_id=workflow_id)
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app = compile_graph(spec, run_ctx).compile(checkpointer=self.checkpointer)
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config = {"configurable": {"thread_id": run_id}}
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snapshot = await app.aget_state(config)
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waiting = list(getattr(snapshot, "interrupts", None) or [])
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if not waiting and not getattr(snapshot, "next", None):
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# 没有断点可续。多半是重启时被标成 interrupted 的 queued 运行。
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raise ValueError(
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"这次运行没有可恢复的断点（很可能重启前还没真正开始跑）。"
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"请重新发起一次运行，而不是恢复——继续下去只会用默认值跑出一份假结果。"
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)
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answers: dict[str, Any] = {}
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async with SessionLocal() as session:
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pending = list((
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await session.execute(
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select(Approval).where(
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Approval.run_id == run_id, Approval.status == "pending"
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)
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)
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).scalars())
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# 定位这次回复的是哪一条：显式指定优先，否则只在唯一 pending 时才敢猜
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target = None
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if approval_id:
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target = next((a for a in pending if a.id == approval_id), None)
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if target is None:
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raise ValueError(f"审批 {approval_id} 不在待处理列表里")
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elif len(pending) == 1:
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target = pending[0]
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elif len(pending) > 1:
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raise ValueError(
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f"这次运行有 {len(pending)} 条待处理的人工介入，"
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"恢复时必须指定 approval_id 说明回复的是哪一条"
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)
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now = datetime.now(timezone.utc)
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if target is not None:
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target.status = "answered" # 已回复，但还没提交给引擎
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target.response = (
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_safe(response) if isinstance(response, dict) else {"value": _safe(response)}
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)
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target.resolved_at = now
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if actor:
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target.resolved_by = actor
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await session.commit()
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# 凑齐没有？引擎还在等的每一个 interrupt 都得有答案
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answered = list((
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await session.execute(
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select(Approval).where(
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Approval.run_id == run_id,
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Approval.status.in_(["answered", "pending"]),
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)
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)
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).scalars())
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by_iid = {a.interrupt_id: a for a in answered if a.interrupt_id}
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missing = []
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for item in waiting:
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iid = getattr(item, "id", None)
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rec = by_iid.get(iid)
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if rec is None or rec.status != "answered":
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missing.append(iid)
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continue
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payload = rec.response or {}
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answers[iid] = payload.get("value", payload) if isinstance(payload, dict) else payload
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if missing:
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# 还差人没回。保持 interrupted，把已回复的那条留在 answered 上等齐
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await session.commit()
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run = await session.get(Run, run_id)
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return run
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# 齐了：正式落 resolved，然后驱动引擎
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for rec in answered:
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if rec.status == "answered":
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rec.status = "resolved"
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run = await session.get(Run, run_id)
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bus.set_seq(run_id, run.last_seq)
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run.status = "running"
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run.error = None
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await session.commit()
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await session.refresh(run)
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# 单个 interrupt 用标量（LangGraph 两种都认），多个必须用 {interrupt_id: value} 映射
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command = (
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Command(resume=response)
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if len(waiting) <= 1
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else Command(resume=answers)
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)
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await self._emit(run_id, EventType.RUN_RESUMED, data={"response": _safe(response)})
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self._tasks[run_id] = asyncio.create_task(
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self._drive(run_id, spec, command, workflow_id=workflow_id)
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)
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return run
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async def continue_failed(
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self, run_id: str, *, graph: dict[str, Any] | None = None, actor: str | None = None
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) -> Run:
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"""从失败的地方接着跑，而不是整张图从头来一遍。
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为什么值得单独开这条路：库里 28 条 failed 里，模型 id 写错、401、循环
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条件语法错、缺必填输入加起来占了大半——全是**配置错了**，改一下就能跑。
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而现在"改一下再跑"意味着前面花两分钟查完的表结构、跑完的 SQL 全部重来。
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checkpointer 一直开着（thread_id = run_id），那些结果本来就在库里躺着。
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graph 可以带一张改过的图，但只准改配置：节点 id、类型、连线必须和原来
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一模一样。checkpoint 是按节点名存的，改了结构就对不上，续下去会拿着
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错位的通道状态跑出一份似是而非的结果——那比直接报错糟得多。
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"""
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async with SessionLocal() as session:
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run = await session.get(Run, run_id)
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if not run:
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raise KeyError(f"找不到运行 {run_id}")
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if run.status != "failed":
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raise ValueError(
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f"当前状态是 {run.status}，只有失败的运行能接着跑。"
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"（等人工介入的用恢复，已完成的重新发起一次。）"
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)
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spec = GraphSpec.model_validate(run.graph)
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workflow_id = run.workflow_id
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if graph is not None:
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revised = GraphSpec.model_validate(graph)
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if topology_of(revised) != topology_of(spec):
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raise ValueError(
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"接着跑只能改节点配置，不能增删节点或改连线——"
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"断点是按节点名存的，结构变了就对不上了。"
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"要改结构请重新发起一次运行。"
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)
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report = validate_graph(revised)
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if not report.ok:
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first = next((i.message for i in report.issues if i.level == "error"), "")
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raise ValueError(f"改过的图没有通过校验：{first}")
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spec = revised
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# 先问引擎到底停在哪。没有待跑的节点就不是"能接着跑"的情形——
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# 硬发一个 None 下去，LangGraph 会从 START 重跑整张图
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run_ctx = RunContext(run_id=run_id, thread_id=run_id, spec=spec, workflow_id=workflow_id)
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app = compile_graph(spec, run_ctx).compile(checkpointer=self.checkpointer)
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config = {"configurable": {"thread_id": run_id}}
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snapshot = await app.aget_state(config)
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pending = [str(n) for n in (getattr(snapshot, "next", None) or [])]
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if not pending:
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raise ValueError(
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"这次运行没有留下可以接着跑的断点（多半是还没跑到第一个节点就挂了）。"
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"请重新发起一次运行——继续下去只会从头跑一遍，还看不出来。"
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)
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done = [n for n in (snapshot.values or {}).get("nodes", {}) if n not in pending]
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async with SessionLocal() as session:
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||
run = await session.get(Run, run_id)
|
||
bus.set_seq(run_id, run.last_seq)
|
||
run.status = "running"
|
||
run.error = None
|
||
if graph is not None:
|
||
run.graph = spec.model_dump(mode="json")
|
||
if actor:
|
||
run.started_by = actor
|
||
await session.commit()
|
||
await session.refresh(run)
|
||
|
||
labels = {n.id: n.title for n in spec.nodes}
|
||
await self._emit(
|
||
run_id, EventType.RUN_RESUMED,
|
||
data={
|
||
"from": pending,
|
||
# 说清楚"哪些没重来"——否则用户看到时间线又动起来，
|
||
# 分不清这次是接着跑还是整张图又跑了一遍
|
||
"message": f"从「{labels.get(pending[0], pending[0])}」接着跑"
|
||
+ (f"，前面 {len(done)} 个节点的结果保留" if done else ""),
|
||
},
|
||
)
|
||
self._tasks[run_id] = asyncio.create_task(
|
||
self._drive(run_id, spec, None, workflow_id=workflow_id)
|
||
)
|
||
return run
|
||
|
||
async def cancel(self, run_id: str) -> bool:
|
||
task = self._tasks.get(run_id)
|
||
if task and not task.done():
|
||
task.cancel()
|
||
return True
|
||
return False
|
||
|
||
def is_active(self, run_id: str) -> bool:
|
||
task = self._tasks.get(run_id)
|
||
return bool(task and not task.done())
|
||
|
||
# ---------------- 执行 ----------------
|
||
|
||
async def _drive(
|
||
self,
|
||
run_id: str,
|
||
spec: GraphSpec,
|
||
payload: Any,
|
||
*,
|
||
workflow_id: str | None = None,
|
||
memory_scope: str = "default",
|
||
collection: str = "default",
|
||
) -> None:
|
||
started = time.perf_counter()
|
||
status = "succeeded"
|
||
error: str | None = None
|
||
final_state: dict[str, Any] = {}
|
||
|
||
async with self._semaphore:
|
||
try:
|
||
async with SessionLocal() as session:
|
||
await session.execute(
|
||
update(Run)
|
||
.where(Run.id == run_id)
|
||
.values(status="running", started_at=datetime.now(timezone.utc))
|
||
)
|
||
await session.commit()
|
||
await self._emit(
|
||
run_id,
|
||
EventType.RUN_STARTED,
|
||
data={"nodes": len(spec.nodes),
|
||
"resumed": payload is None or isinstance(payload, Command)},
|
||
)
|
||
|
||
run_ctx = RunContext(
|
||
run_id=run_id,
|
||
thread_id=run_id,
|
||
spec=spec,
|
||
workflow_id=workflow_id,
|
||
memory_scope=memory_scope,
|
||
collection=collection,
|
||
)
|
||
app = compile_graph(spec, run_ctx).compile(checkpointer=self.checkpointer)
|
||
config = {
|
||
"configurable": {"thread_id": run_id},
|
||
"recursion_limit": settings.max_graph_steps,
|
||
}
|
||
|
||
interrupted = False
|
||
async for mode, chunk in app.astream(
|
||
payload, config=config, stream_mode=["custom", "updates"]
|
||
):
|
||
if mode == "custom":
|
||
await self._handle_custom(run_id, chunk)
|
||
elif mode == "updates":
|
||
if await self._handle_updates(run_id, chunk):
|
||
interrupted = True
|
||
|
||
snapshot = await app.aget_state(config)
|
||
final_state = dict(snapshot.values or {})
|
||
if interrupted or snapshot.interrupts:
|
||
status = "interrupted"
|
||
elif snapshot.next:
|
||
status = "interrupted"
|
||
|
||
except asyncio.CancelledError:
|
||
status = "cancelled"
|
||
error = "用户取消"
|
||
await self._emit(run_id, EventType.RUN_CANCELLED, data={})
|
||
raise
|
||
except Exception as e: # noqa: BLE001
|
||
status = "failed"
|
||
# NodeError 的 message 本来就是写给人看的（"人工驳回：…"），
|
||
# 再套一层类型名只会让界面上的错误更难读
|
||
error = str(e) if isinstance(e, NodeError) else f"{type(e).__name__}: {e}"
|
||
logger.exception("run %s 失败", run_id)
|
||
await self._emit(run_id, EventType.RUN_FAILED, data={"error": error})
|
||
finally:
|
||
elapsed = int((time.perf_counter() - started) * 1000)
|
||
await self._finalize(run_id, status, error, final_state, elapsed)
|
||
self._tasks.pop(run_id, None)
|
||
# 运行到终态就把沙箱会话收掉。thread_id 每个 run 都是新的，
|
||
# 不收的话每跑一次带代码节点的图就多一台常驻 microVM（几百 MB），
|
||
# 而且没有任何自动回收路径会碰它——闲置回收只在"下次有人执行
|
||
# 代码"时才触发。interrupted 要留着，人回来还得接着跑。
|
||
if status in ("succeeded", "failed", "cancelled"):
|
||
with contextlib.suppress(Exception):
|
||
from app.sandbox.manager import sandbox_manager
|
||
|
||
await sandbox_manager.cleanup(run_id)
|
||
|
||
async def _handle_custom(self, run_id: str, chunk: Any) -> None:
|
||
"""节点通过 get_stream_writer 发来的事件。"""
|
||
if not isinstance(chunk, dict) or not chunk.get("__agentlab__"):
|
||
return
|
||
await self._emit(
|
||
run_id,
|
||
chunk.get("type", EventType.LOG),
|
||
node_id=chunk.get("node_id"),
|
||
data=chunk.get("data") or {},
|
||
)
|
||
|
||
async def _handle_updates(self, run_id: str, chunk: Any) -> bool:
|
||
"""LangGraph 的状态更新。这里只关心中断信号 —— 节点级事件已经由 custom 流覆盖。"""
|
||
if not isinstance(chunk, dict):
|
||
return False
|
||
interrupts = chunk.get("__interrupt__")
|
||
if not interrupts:
|
||
return False
|
||
|
||
for item in interrupts:
|
||
value = getattr(item, "value", item)
|
||
interrupt_id = getattr(item, "id", None)
|
||
payload = value if isinstance(value, dict) else {"value": value}
|
||
async with SessionLocal() as session:
|
||
existing = (
|
||
await session.execute(
|
||
select(Approval).where(
|
||
Approval.run_id == run_id,
|
||
Approval.interrupt_id == interrupt_id,
|
||
Approval.status == "pending",
|
||
)
|
||
)
|
||
).scalar_one_or_none()
|
||
if existing is None:
|
||
session.add(
|
||
Approval(
|
||
run_id=run_id,
|
||
node_id=str(payload.get("node_id") or ""),
|
||
interrupt_id=interrupt_id,
|
||
mode=str(payload.get("mode") or "approve"),
|
||
title=str(payload.get("title") or "需要你确认"),
|
||
payload=payload,
|
||
schema_=payload.get("schema") or {},
|
||
)
|
||
)
|
||
await session.commit()
|
||
await self._emit(
|
||
run_id,
|
||
EventType.RUN_INTERRUPTED,
|
||
node_id=payload.get("node_id"),
|
||
data={"interrupt_id": interrupt_id, "payload": _safe(payload)},
|
||
)
|
||
return True
|
||
|
||
async def _finalize(
|
||
self,
|
||
run_id: str,
|
||
status: str,
|
||
error: str | None,
|
||
state: dict[str, Any],
|
||
elapsed_ms: int,
|
||
) -> None:
|
||
usage = dict(state.get("usage") or {})
|
||
usage["duration_ms"] = elapsed_ms
|
||
output = dict(state.get("output") or {})
|
||
|
||
async with SessionLocal() as session:
|
||
run = await session.get(Run, run_id)
|
||
if run:
|
||
run.status = status
|
||
run.error = error
|
||
run.output = output
|
||
run.usage = usage
|
||
if status != "interrupted":
|
||
run.finished_at = datetime.now(timezone.utc)
|
||
# 终态时对全部已落库事件计算清单哈希：事后任何对事件流的
|
||
# 增删改都会与这个值对不上。中断态不算——事件还会继续追加。
|
||
from app.core.artifact_store import manifest_hash as _manifest
|
||
|
||
rows = await session.execute(
|
||
select(RunEvent.seq, RunEvent.type, RunEvent.node_id, RunEvent.data)
|
||
.where(RunEvent.run_id == run_id)
|
||
.order_by(RunEvent.seq)
|
||
)
|
||
run.manifest_hash = _manifest([tuple(r) for r in rows])
|
||
await session.commit()
|
||
|
||
if status == "succeeded":
|
||
await self._emit(
|
||
run_id,
|
||
EventType.RUN_FINISHED,
|
||
data={"output": _safe(output), "usage": usage, "duration_ms": elapsed_ms},
|
||
)
|
||
if status in ("succeeded", "failed", "cancelled"):
|
||
await bus.close(run_id)
|
||
|
||
|
||
def _safe(value: Any, limit: int = 4000) -> Any:
|
||
"""把任意对象裁剪成能安全放进事件负载的形状。"""
|
||
if isinstance(value, str):
|
||
return value[:limit]
|
||
if isinstance(value, dict):
|
||
return {k: _safe(v, limit // 2) for k, v in list(value.items())[:50]}
|
||
if isinstance(value, list):
|
||
return [_safe(v, limit // 2) for v in value[:50]]
|
||
if isinstance(value, (int, float, bool)) or value is None:
|
||
return value
|
||
return str(value)[:limit]
|
||
|
||
|
||
run_manager = RunManager()
|