Files
AgentLab/backend/app/engine/runner.py
T
ThearchyHelios b0575a7d1b 引擎四处:错误处理、恢复语义、幂运算炸弹
## 一条分支条件能把后端冻死

求值器放行 ast.Pow,唯一护栏是 AST 节点数 <= 200。`9**9**9**9` 只有 11 个节点,
却让 CPython 无限期算大整数。而求值是在事件循环里同步执行的(分支条件、
transform、口径卡、每个节点的 skip_if),没有线程池隔离也没有超时,asyncio 的
cancel 打断不了同步 CPU。给底数和指数加上界,超界报 ExpressionError。
2**10、2**0.5、10**-2 这些正常用法不受影响。

## NodeError 绕过 retries / on_error / node.failed

`except NodeError: raise` 排在重试与兜底之前,于是节点自己抛的错既不重试、
也不发 node.failed、更不被 on_error=continue 接住——而 NodeError 恰恰是所有
执行器表达失败的标准方式(缺必填输入、模型没配、口径卡算不出…)。同一张图
配着同样的 retries=1 + on_error=continue,1/0 会重试并继续,而 JSON 模板非法
直接整个 run 失败。两条路径现在行为一致,node.failed 也带上 node_id
(前端靠它把出错节点从"转圈"收敛成"失败")。

## 没有 checkpoint 的运行被"恢复"成一份假结果

重启扫描把 running 和 queued 一律标成 interrupted,而 resume 不检查有没有
checkpoint 就发 Command。queued 的运行从没写过 checkpoint,LangGraph 会拿空
state 从 START 重跑整张图——run.input 完全没注入,用字段默认值算完还落成
succeeded。现在 queued 直接标 failed(没有进度可恢复,请重新发起),resume
先 aget_state 确认有断点,没有就 409 并说清为什么。

## 并行人工节点:一次 resume 打爆整个 run

同一 superstep 有多个 interrupt 时,resume 仍只发标量 Command,LangGraph 直接
抛 RuntimeError;而所有 pending 审批已经被写成同一个回复。Approval.interrupt_id
和 ResumeIn.approval_id 这两个字段一直存在却从没被用过。现在按 interrupt_id
逐条收集:多条待办时必须指定 approval_id,回复的那条转 answered 继续等,
凑齐引擎在等的全部 interrupt 才发 Command(resume={iid: value})。

验证:两个并行 human 节点——不指定 approval_id 被 409 拒、回复第一条后仍
interrupted 且剩 1 条 pending、凑齐后 succeeded。单人审批与 decide 通道回归通过。
2026-09-14 15:35:47 +08:00

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from __future__ import annotations
import asyncio
import contextlib
import logging
import time
from datetime import datetime, timezone
from typing import Any
from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
from langgraph.types import Command
from sqlalchemy import select, update
from app.core.bus import bus
from app.core.config import settings
from app.core.events import EventType, RunEventModel
from app.db.base import SessionLocal
from app.db.models import Approval, Run, RunEvent, Workflow
from app.engine.compiler import compile_graph, initial_state
from app.engine.context import RunContext
from app.engine.schema import GraphSpec, validate_graph
logger = logging.getLogger(__name__)
# 流式增量(正文 token、思考 delta)量太大,只做实时推送不落库;
# 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
_EPHEMERAL = {EventType.LLM_TOKEN, EventType.LLM_THINKING_DELTA}
class RunManager:
"""负责一次运行的完整生命周期:启动、串流、中断、恢复、取消。"""
def __init__(self) -> None:
self._tasks: dict[str, asyncio.Task[None]] = {}
self._checkpointer: AsyncSqliteSaver | None = None
self._cm: Any = None
self._semaphore = asyncio.Semaphore(settings.max_concurrent_runs)
# ---------------- 生命周期 ----------------
async def setup(self) -> None:
settings.ensure_dirs()
self._cm = AsyncSqliteSaver.from_conn_string(str(settings.checkpoint_path))
self._checkpointer = await self._cm.__aenter__()
# 上次进程被强杀时留下的记录。running 和 queued 要分开处理:
# running 至少跑过一步、有 checkpoint,可以续;queued 还在排队,
# 一个 checkpoint 都没写过,"恢复"它只会从 START 用默认值重跑一遍,
# 还丢掉 run.input——那不是恢复,是伪造一份结果。
async with SessionLocal() as session:
await session.execute(
update(Run)
.where(Run.status == "running")
.values(status="interrupted", error="服务重启,运行已挂起,可从断点恢复")
)
await session.execute(
update(Run)
.where(Run.status == "queued")
.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")
)
await session.commit()
async def shutdown(self) -> None:
for task in list(self._tasks.values()):
task.cancel()
await asyncio.gather(*self._tasks.values(), return_exceptions=True)
if self._cm is not None:
with contextlib.suppress(Exception):
await self._cm.__aexit__(None, None, None)
@property
def checkpointer(self) -> AsyncSqliteSaver:
if self._checkpointer is None:
raise RuntimeError("RunManager 还没初始化")
return self._checkpointer
# ---------------- 事件 ----------------
async def _emit(
self,
run_id: str,
event_type: EventType | str,
*,
node_id: str | None = None,
data: dict[str, Any] | None = None,
persist: bool = True,
) -> None:
event = RunEventModel(
run_id=run_id,
seq=bus.next_seq(run_id),
type=EventType(str(event_type)),
node_id=node_id,
data=data or {},
)
await bus.publish(event)
if persist and event.type not in _EPHEMERAL:
async with SessionLocal() as session:
session.add(
RunEvent(
run_id=run_id,
seq=event.seq,
type=str(event.type),
node_id=event.node_id,
ts=event.ts,
data=event.data,
)
)
await session.execute(
update(Run).where(Run.id == run_id).values(last_seq=event.seq)
)
await session.commit()
async def note(
self, run_id: str, event_type: EventType | str, *, node_id: str | None = None,
**data: Any,
) -> None:
"""给 API 层用的事件入口(比如 formal 启动时记录口径升版处置)。"""
await self._emit(run_id, event_type, node_id=node_id, data=data)
# ---------------- 启动 ----------------
async def start(
self,
*,
graph: dict[str, Any],
input_payload: dict[str, Any],
workflow_id: str | None = None,
workflow_name: str = "",
memory_scope: str = "default",
collection: str = "default",
run_class: str = "exploratory",
version: int | None = None,
version_hash: str | None = None,
started_by: str | None = None,
) -> Run:
spec = GraphSpec.model_validate(graph)
report = validate_graph(spec)
if not report.ok:
raise ValueError(
"图校验未通过:" + ";".join(i.message for i in report.issues if i.level == "error")
)
async with SessionLocal() as session:
run = Run(
workflow_id=workflow_id,
workflow_name=workflow_name,
status="queued",
graph=graph,
input=input_payload,
run_class=run_class,
version=version,
version_hash=version_hash,
started_by=started_by,
)
run.thread_id = run.id # 一个 run 一条 checkpoint 线程
session.add(run)
await session.commit()
await session.refresh(run)
self._tasks[run.id] = asyncio.create_task(
self._drive(
run.id,
spec,
initial_state(input_payload),
workflow_id=workflow_id,
memory_scope=memory_scope,
collection=collection,
)
)
return run
async def resume(
self, run_id: str, response: Any, *, approval_id: str | None = None,
actor: str | None = None,
) -> Run:
"""从人工介入的断点继续。
两件事以前是错的:
一是不看有没有 checkpoint 就发 Command。重启扫描会把 queued(从没跑过、
没有任何 checkpoint)也标成 interrupted,对这种 run 发 Command,LangGraph
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
succeeded。跑出来的是一份用默认值算的假结果。
二是同一 superstep 里有多个 interrupt 时,只发标量 Command 会让 LangGraph
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。
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。
"""
async with SessionLocal() as session:
run = await session.get(Run, run_id)
if not run:
raise KeyError(f"找不到运行 {run_id}")
if run.status not in ("interrupted",):
raise ValueError(f"当前状态是 {run.status},无法恢复")
spec = GraphSpec.model_validate(run.graph)
workflow_id = run.workflow_id
# 先问引擎:这条线程到底停在哪、还等着哪些 interrupt
run_ctx = RunContext(run_id=run_id, thread_id=run_id, spec=spec, workflow_id=workflow_id)
app = compile_graph(spec, run_ctx).compile(checkpointer=self.checkpointer)
config = {"configurable": {"thread_id": run_id}}
snapshot = await app.aget_state(config)
waiting = list(getattr(snapshot, "interrupts", None) or [])
if not waiting and not getattr(snapshot, "next", None):
# 没有断点可续。多半是重启时被标成 interrupted 的 queued 运行。
raise ValueError(
"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)。"
"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。"
)
answers: dict[str, Any] = {}
async with SessionLocal() as session:
pending = list((
await session.execute(
select(Approval).where(
Approval.run_id == run_id, Approval.status == "pending"
)
)
).scalars())
# 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
target = None
if approval_id:
target = next((a for a in pending if a.id == approval_id), None)
if target is None:
raise ValueError(f"审批 {approval_id} 不在待处理列表里")
elif len(pending) == 1:
target = pending[0]
elif len(pending) > 1:
raise ValueError(
f"这次运行有 {len(pending)} 条待处理的人工介入,"
"恢复时必须指定 approval_id 说明回复的是哪一条"
)
now = datetime.now(timezone.utc)
if target is not None:
target.status = "answered" # 已回复,但还没提交给引擎
target.response = (
_safe(response) if isinstance(response, dict) else {"value": _safe(response)}
)
target.resolved_at = now
if actor:
target.resolved_by = actor
await session.commit()
# 凑齐没有?引擎还在等的每一个 interrupt 都得有答案
answered = list((
await session.execute(
select(Approval).where(
Approval.run_id == run_id,
Approval.status.in_(["answered", "pending"]),
)
)
).scalars())
by_iid = {a.interrupt_id: a for a in answered if a.interrupt_id}
missing = []
for item in waiting:
iid = getattr(item, "id", None)
rec = by_iid.get(iid)
if rec is None or rec.status != "answered":
missing.append(iid)
continue
payload = rec.response or {}
answers[iid] = payload.get("value", payload) if isinstance(payload, dict) else payload
if missing:
# 还差人没回。保持 interrupted,把已回复的那条留在 answered 上等齐
await session.commit()
run = await session.get(Run, run_id)
return run
# 齐了:正式落 resolved,然后驱动引擎
for rec in answered:
if rec.status == "answered":
rec.status = "resolved"
run = await session.get(Run, run_id)
bus.set_seq(run_id, run.last_seq)
run.status = "running"
run.error = None
await session.commit()
await session.refresh(run)
# 单个 interrupt 用标量(LangGraph 两种都认),多个必须用 {interrupt_id: value} 映射
command = (
Command(resume=response)
if len(waiting) <= 1
else Command(resume=answers)
)
await self._emit(run_id, EventType.RUN_RESUMED, data={"response": _safe(response)})
self._tasks[run_id] = asyncio.create_task(
self._drive(run_id, spec, command, 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": 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"
error = 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)
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()