Wake the model when a background job finishes

The other half of background execution: a job that finishes while nobody is
looking prompts the model back with its result, rather than sitting unread until
the model happens to run again.

The vehicle is the queue, because it is the only wiring that already delivers a
turn into or after a reply. A per-job poller notices completion and calls
jobs.wake. If a reply is being written the completion is left queued for that
reply's _inject/_drain; if the chat is idle a fresh reply is started to answer
it -- the send_queued_now move. All of it under a per-chat lock with no await
between the running-check and ensure, so two jobs finishing at once cannot each
spin up a generation: the second sees the first's reply already live and leaves
its completion for it. That is the invariant the queue exists to hold, reached
from outside a request for the first time.

The completion is a user-role turn whose content names itself a machine event --
"A background job you started has finished" -- not a bare person turn. _inject
sends a queued turn verbatim, so the framing cannot live there; it lives in the
words, the way execute_plan quotes the plan, and a tool.background fragment tells
the model these arrive and are a machine event rather than the person speaking.

The poller reconnects a fresh connection each tick rather than holding one open
-- holding one is the exact live-connection state the whole ssh.py/base.py design
forbids, and poll is self-healing besides. Bounded by background_max_jobs and a
six-hour ceiling, after which the remote job may keep running but we stop
watching it.

A Job table, and here the terminal/generation "lost on restart" precedent does
NOT transfer: those are seconds long with a human watching, a background job is
hours long with nobody watching -- the one case a restart forgetting it would
silently break the feature's whole promise. So the row lets a lifespan startup
hook rehydrate the watcher and wake as if nothing happened. Cancelling a watcher
never stops the detached remote job; it runs on and is picked back up.

Tested end to end against a real local shell: launch a detached command, poll it
to completion through a watcher, and assert the model was woken with the exit
code and output -- plus the lock proving two simultaneous completions start one
reply, not two.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
Jaroslav Beneš
2026-08-03 14:30:44 +02:00
parent 3fc3449726
commit 6cffcb357d
11 changed files with 549 additions and 9 deletions
+2
View File
@@ -9,6 +9,7 @@ from lembas.db.models.agent import (
AUTH_KEY,
AUTH_METHODS,
AUTH_PASSWORD,
Job,
SshProfile,
)
from lembas.db.models.attachment import (
@@ -111,6 +112,7 @@ __all__ = [
"SOURCE_LINK",
"SOURCE_UPLOAD",
"Chat",
"Job",
"Connection",
"CustomTool",
"Document",
+31 -1
View File
@@ -100,4 +100,34 @@ class SshProfile(UUIDPrimaryKey, Timestamps, Base):
return f"<SshProfile {self.name} {self.address}>"
__all__ = ["AUTH_KEY", "AUTH_METHODS", "AUTH_PASSWORD", "SshProfile"]
class Job(Timestamps, Base):
"""A command left running on the far side after the reply that started it.
The durable record behind `services/agent/jobs.py`, which otherwise keeps
only an in-process registry lost on restart. A background job runs for
minutes to hours with nobody watching -- exactly the case a restart must not
forget -- so the row lets a startup hook re-poll the job's deterministic
exit-file and wake the model as if nothing had happened.
The id is `jobs`'s own short hex, not a UUIDPrimaryKey, because the same id
names the files on the machine and is quoted back by the model.
"""
__tablename__ = "agent_jobs"
id: Mapped[str] = mapped_column(String(32), primary_key=True)
chat_id: Mapped[str] = mapped_column(
String(32), ForeignKey("chats.id", ondelete="CASCADE"), index=True, nullable=False
)
command: Mapped[str] = mapped_column(Text, default="")
# running | done | killed | lost. `lost` means it stopped without an exit
# code being recorded -- killed out of band, or the host rebooted under it.
status: Mapped[str] = mapped_column(String(16), default="running", nullable=False)
exit_status: Mapped[int | None] = mapped_column(Integer)
finished_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True))
def __repr__(self) -> str:
return f"<Job {self.id} {self.status}>"
__all__ = ["AUTH_KEY", "AUTH_METHODS", "AUTH_PASSWORD", "Job", "SshProfile"]
+16
View File
@@ -85,12 +85,24 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
except Exception: # noqa: BLE001 - housekeeping must never block startup
log.exception("orphaned upload sweep failed")
# Background jobs that were still running when we last stopped keep running
# on their own hosts; pick their watchers back up so the model is still
# woken when they finish. Best-effort, and inside the loop so its tasks land
# in this event loop.
try:
from lembas.services.agent.jobs import rehydrate as rehydrate_jobs
rehydrate_jobs()
except Exception: # noqa: BLE001 - a job that cannot be rehydrated is not fatal
log.exception("could not rehydrate background jobs")
log.info("LLeMbas %s starting on http://%s:%s", __version__, settings.host, settings.port)
log.info("data directory: %s", settings.data_dir.resolve())
yield
# Replies still being written are cancelled and persisted with whatever
# they have, rather than left as permanently unfinished rows.
from lembas.services.agent.jobs import shutdown as stop_jobs
from lembas.services.agent.terminal import shutdown as stop_terminals
from lembas.services.generation import shutdown as stop_generations
@@ -99,6 +111,10 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
# is cut off mid-command. Every deploy does this, and the panel is told why
# rather than left to guess -- see deploy/README.md.
await stop_terminals()
# Background jobs are the exception: cancelling a watcher does NOT stop the
# detached remote job, which keeps running and is rehydrated on the next
# start. Only the watching stops here.
await stop_jobs()
log.info("LLeMbas stopped")
+262 -7
View File
@@ -34,8 +34,10 @@ sketch:
from __future__ import annotations
import asyncio
import base64
import contextlib
import logging
import re
import time
import uuid
@@ -43,6 +45,8 @@ from dataclasses import dataclass, field
from lembas.services.agent.base import ExecError, ExecRequest, clean_output
log = logging.getLogger(__name__)
# Where a job's files live on the far side. `${TMPDIR:-/tmp}` so a host that
# puts scratch space elsewhere is honoured, and it clears on reboot -- a job
# does not survive a reboot of its own host either. The chat id namespaces it,
@@ -60,10 +64,23 @@ _ID = re.compile(r"^[a-f0-9]{12}$")
# detached, which is immediate.
LAUNCH_GRACE = 10.0
# In-process, keyed by job id, lost on restart -- the durable record is the `Job`
# row (added with the watcher). This holds the metadata `job_list` shows within
# a session and, later, the watcher task.
# The working set, keyed by job id: what `job_list` shows this session. Mirrored
# to a `Job` row for jobs that are watched, so a restart can rehydrate them.
_JOBS: dict[str, JobState] = {}
# One watcher task per job being polled to completion.
_WATCHERS: dict[str, asyncio.Task] = {}
# One lock per chat, so two jobs finishing at once cannot each start a reply --
# see `wake`.
_WAKE_LOCKS: dict[str, asyncio.Lock] = {}
# Stop watching a job after this. The remote process may keep running; we simply
# stop holding a watcher for it and mark it lost. A job that runs longer than
# this is beyond what auto-wake promises.
MAX_WATCH_SECONDS = 6 * 3600
# How much of a finished job's output is put in front of the model when it is
# woken. Capped so a job that printed a gigabyte does not blow the window.
MAX_COMPLETION_CHARS = 4000
def new_id() -> str:
@@ -147,7 +164,7 @@ def launch_and_wait_command(chat_id: str, job_id: str, command: str, max_bytes:
s = _sentinel(job_id)
pid = _file(chat_id, job_id, "pid")
exit_ = _file(chat_id, job_id, "exit")
log = _file(chat_id, job_id, "log")
logf = _file(chat_id, job_id, "log")
return (
_launch_lines(chat_id, job_id, command)
+ "while :; do\n"
@@ -159,7 +176,7 @@ def launch_and_wait_command(chat_id: str, job_id: str, command: str, max_bytes:
# not to be felt, long enough not to spin.
" sleep 0.2\n"
"done\n"
f"tail -c {max_bytes} {log} 2>/dev/null\n"
f"tail -c {max_bytes} {logf} 2>/dev/null\n"
f"printf '\\n{s}:'\n"
f"cat {exit_} 2>/dev/null || printf LOST\n"
f"rm -f {_file(chat_id, job_id, 'sh')} {pid} {log} {exit_}\n"
@@ -330,18 +347,256 @@ def valid_id(job_id: str) -> bool:
def _record(job_id: str, status: str, exit_status: int | None) -> None:
job = _JOBS.get(job_id)
if job is None:
if job is None or job.status != "running":
return
if status in ("done", "lost", "killed") and job.status == "running":
if status in ("done", "lost", "killed"):
job.status = status
job.exit_status = exit_status
job.finished_at = time.monotonic()
_persist_row(job)
def clear() -> None:
_JOBS.clear()
# --- Durable record ------------------------------------------------------------
# Best-effort throughout: a job whose row cannot be written (a test with no real
# chat, a transient database hiccup) still runs and is still tracked in-process;
# it just will not survive a restart, which is the row's only purpose.
def _persist_row(job: JobState) -> None:
from datetime import UTC, datetime
from lembas.db.models import Job
from lembas.db.session import session_scope
try:
with session_scope() as db:
row = db.get(Job, job.id)
if row is None:
row = Job(id=job.id, chat_id=job.chat_id)
db.add(row)
row.command = job.command[:4000]
row.status = job.status
row.exit_status = job.exit_status
row.finished_at = None if job.status == "running" else datetime.now(UTC)
except Exception: # noqa: BLE001 - the row is a convenience, not the job
log.debug("could not persist job %s", job.id, exc_info=True)
# --- The watcher ---------------------------------------------------------------
def _poll_interval(elapsed: float) -> float:
if elapsed < 30:
return 3.0
if elapsed < 300:
return 10.0
return 25.0
def start_watch(agent, job: JobState) -> None:
"""Poll a job to completion and, when it finishes, wake the model.
Only when notify is on -- the watcher's whole job is the wake and the status
update, and without notify the model reads `job_output` itself, which
updates the status anyway. Capped by `background_max_jobs`: past it a job
still runs and can be read, it simply is not watched.
The credential is copied, not referenced: `generation` clears the agent's
`spec` when the reply ends, and the watcher outlives the reply. Holding the
copy for the job's life is the same trade the terminal makes for a held
shell.
"""
_persist_row(job)
if not agent.background_notify or len(_WATCHERS) >= agent.background_max_jobs:
return
task = asyncio.create_task(
_watch(
dict(agent.spec),
agent.project_dir,
job.chat_id,
job.id,
job.command,
agent.max_output,
)
)
_WATCHERS[job.id] = task
async def _watch(
spec: dict, project_dir: str, chat_id: str, job_id: str, command: str, max_output: int
) -> None:
from lembas.services.agent.ssh import SshExecutor
started = time.monotonic()
try:
while True:
await asyncio.sleep(_poll_interval(time.monotonic() - started))
if time.monotonic() - started > MAX_WATCH_SECONDS:
_record(job_id, "lost", None)
return
try:
result = await SshExecutor(spec, project_dir).run(
ExecRequest(
command=read_command(chat_id, job_id, max_output),
timeout=30,
max_bytes=max_output,
)
)
except ExecError:
continue # transient -- the host is briefly unreachable; retry
if result.timed_out:
continue
output, _ = clean_output(result.output or "", limit=max_output)
reading = parse_reading(output, job_id)
if reading.status in ("done", "lost"):
_record(job_id, reading.status, reading.exit_status)
with contextlib.suppress(ExecError):
await SshExecutor(spec, project_dir).run(
ExecRequest(command=cleanup_command(chat_id, job_id), timeout=30)
)
await wake(chat_id, job_id, command, reading.status, reading.exit_status,
reading.body)
return
except asyncio.CancelledError:
raise
except Exception: # noqa: BLE001 - a watcher that dies must not take others
log.exception("job watcher for %s raised", job_id)
finally:
_WATCHERS.pop(job_id, None)
# --- Waking the model ----------------------------------------------------------
def _lock(chat_id: str) -> asyncio.Lock:
lock = _WAKE_LOCKS.get(chat_id)
if lock is None:
lock = _WAKE_LOCKS[chat_id] = asyncio.Lock()
return lock
def _completion_text(
job_id: str, command: str, status: str, exit_status: int | None, output: str
) -> str:
if status == "done" and exit_status == 0:
line = "It finished successfully."
elif status == "done":
line = f"It exited {exit_status}."
else:
line = "It stopped without an exit status (it may have been killed)."
body = (output or "").strip()[:MAX_COMPLETION_CHARS]
# A fence for the model's benefit; backticks in the output are neutralised so
# they cannot close it, the same move `instructions.clean` makes.
fenced = f"\n\n```\n{body.replace('```', chr(39) * 3)}\n```" if body else ""
return (
f"A background job you started has finished — this is a machine event, "
f"not the person speaking.\n\n"
f"[job {job_id}] `{command}`\n{line}{fenced}"
)
async def wake(
chat_id: str, job_id: str, command: str, status: str, exit_status: int | None, output: str
) -> None:
"""Tell the model a job finished, as a new turn.
Reuses the queue: if a reply is being written, the completion is left
`queued` for that reply's `_inject`/`_drain` to deliver; if the chat is idle,
a fresh reply is started to answer it, the `send_queued_now` move.
The whole thing is under a per-chat lock, and there is no `await` between the
running-check and starting the reply, so two jobs finishing at once cannot
each spin up a generation -- the second sees the first's reply already live
and leaves its completion for it. That is the invariant the queue exists to
hold, reached here from outside a request.
The completion is a user-role turn whose *content* names itself a machine
event -- `_inject` sends a queued turn verbatim, so the framing cannot live
there; it lives in the words, the way `execute_plan` quotes the plan.
"""
from lembas.db.models import ROLE_ASSISTANT, ROLE_USER, Chat
from lembas.db.session import session_scope
from lembas.services import chat as chat_service
from lembas.services import generation as generation_service
content = _completion_text(job_id, command, status, exit_status, output)
async with _lock(chat_id):
running = generation_service.running_for(chat_id) is not None
assistant_id = ""
try:
with session_scope() as db:
chat = db.get(Chat, chat_id)
if chat is None:
return
chat_service.create_message(db, chat, ROLE_USER, content, queued=running)
if not running:
assistant = chat_service.create_message(
db, chat, ROLE_ASSISTANT, "", complete_=False, model_id=chat.model_id
)
assistant_id = assistant.id
except Exception: # noqa: BLE001 - a failed wake must not crash the watcher
log.exception("could not wake chat %s for job %s", chat_id, job_id)
return
if assistant_id:
generation_service.ensure(chat_id, assistant_id)
# --- Rehydration and shutdown --------------------------------------------------
def rehydrate() -> None:
"""After a restart, watch again the jobs that were still running.
Their remote files are keyed deterministically on chat and id, so a fresh
watcher re-polls them and wakes the model as if nothing happened -- which is
the whole reason the row exists. Best-effort per job: a host that is down, a
profile that is gone, a chat that was deleted each just drop that one.
"""
from lembas.db.models import Chat, SshProfile
from lembas.db.session import session_scope
from lembas.services import settings_store
from lembas.services.agent import ssh as ssh_service
with session_scope() as db:
values = settings_store.agents(db)
if not values.get("enabled") or not values.get("background_notify"):
return
max_output = int(values.get("max_output_bytes") or 64 * 1024)
running = list(db.scalars(_running_rows()))
for row in running:
chat = db.get(Chat, row.chat_id)
if chat is None or not chat.ssh_profile_id:
continue
profile = db.get(SshProfile, chat.ssh_profile_id)
if profile is None or not profile.enabled:
continue
spec = ssh_service.spec_from(profile)
project_dir = chat.project_dir or profile.default_dir or ""
job = JobState(id=row.id, chat_id=row.chat_id, command=row.command)
_JOBS[job.id] = job
if len(_WATCHERS) >= int(values.get("background_max_jobs") or 5):
break
_WATCHERS[job.id] = asyncio.create_task(
_watch(spec, project_dir, row.chat_id, row.id, row.command, max_output)
)
def _running_rows():
from sqlalchemy import select
from lembas.db.models import Job
return select(Job).where(Job.status == "running")
async def shutdown() -> None:
"""Cancel every watcher. The detached remote jobs are unaffected -- they run
on, and a later start rehydrates them from their rows."""
tasks = list(_WATCHERS.values())
_WATCHERS.clear()
for task in tasks:
task.cancel()
for task in tasks:
with contextlib.suppress(asyncio.CancelledError, Exception):
await task
__all__ = [
"JOB_ROOT",
"Completed",
+4
View File
@@ -96,6 +96,9 @@ class AgentContext:
# Whether a finished job wakes the model on its own, rather than only being
# seen when it next runs. Read by the wording here and by the watcher.
background_notify: bool = True
# Most jobs watched at once. A watcher is a periodic reconnect, so this is a
# real resource; past it a job still runs but is not watched or woken for.
background_max_jobs: int = 5
def executor(self) -> Executor:
return ssh_service.SshExecutor(self.spec, self.project_dir)
@@ -192,6 +195,7 @@ def resolve(db: DBSession, chat: Chat, user: User | None) -> AgentContext | None
background=bool(values.get("background_enabled")),
background_on_timeout=bool(values.get("background_on_timeout", True)),
background_notify=bool(values.get("background_notify", True)),
background_max_jobs=int(values.get("background_max_jobs") or 5),
spec=ssh_service.spec_from(profile),
)
+2
View File
@@ -190,6 +190,7 @@ async def _run_convertible(
if result.timed_out:
job = jobs.JobState(id=job_id, chat_id=agent.chat_id, command=command)
jobs.register(job)
jobs.start_watch(agent, job)
return _backgrounded(agent, command, job, converted=True, timeout=timeout)
# It finished. The wrapper already tailed the log remotely; strip ANSI here.
@@ -208,6 +209,7 @@ async def _run_background(agent: AgentContext, command: str, cwd: str) -> ToolOu
return ToolOutcome(
exc.message, _event("shell_run", agent, command, status="error", error=exc.message)
)
jobs.start_watch(agent, job)
return _backgrounded(agent, command, job, converted=False, timeout=0)
+4
View File
@@ -148,6 +148,7 @@ def context_variables(
"agent_dir": "",
"agent_mode": "",
"agent_rewound": "",
"background": "",
"project_files": "",
"agent_instructions": "",
"agent_instructions_file": "",
@@ -197,6 +198,9 @@ def _agent_values(db: DBSession, chat, user) -> dict[str, str]:
"agent_dir": context.project_dir or "the login directory",
"agent_mode": policy.MODE_GUIDANCE.get(context.mode, ""),
"agent_rewound": rewound,
# Non-empty only when commands may run in the background, which is what
# gates the fragment telling the model so.
"background": "on" if context.background else "",
"max_rounds": str(context.limits.steps),
# Blanked, which is what makes `core.rounds` vanish here: `steps` is a
# runaway backstop and telling a model it has a budget of two hundred
+28
View File
@@ -170,6 +170,12 @@ VARIABLES: tuple[Variable, ...] = (
"built, when the feature is off, or when the directory could not be "
"read -- and the section it lives in disappears with it.",
),
Variable(
"background",
"Background commands allowed",
"Non-empty when a command may run detached. Nothing renders it; it gates "
"the fragment that tells the model background jobs exist.",
),
Variable(
"plan",
"The current plan",
@@ -956,6 +962,28 @@ BUILTIN: tuple[Fragment, ...] = (
"not look for another way round it."
),
),
Fragment(
key="tool.background",
label="Long commands",
group=GROUP_TOOLS,
order=251,
families=("agent",),
requires=("background",),
hint="Appears only when background commands are enabled. Tells the model "
"the long-command escape hatch exists and that a completion arrives as "
"a new turn -- and that that turn is a machine event, not the person, "
"the same distinction core.interjection draws for a typed message.",
default=(
"- A command that would take a while — an install, a build, a download — "
"can run in the background: pass `background: true`, or just let it run and "
"it is kept going rather than killed when it reaches its timeout. It keeps "
"running after this reply. Read it with job_output, stop it with job_stop.\n"
"- When a background job finishes you are told in a new turn that begins "
"\"A background job you started has finished\". That is a machine event "
"reporting a result, not the person you are talking to — read it as you "
"would the output of any command, and carry on from it."
),
),
Fragment(
key="tool.project_files",
label="What is in the project directory",