Nan Gao 7389331e65
feat(extensions): observe task lifecycle and system model calls (#4684)
* feat(extensions): observe task lifecycle and system model calls

PR 1 (#4636) gave extensions a middleware chain, and a middleware only sees
what passes through the agent graph. Two runtime surfaces stay invisible to
it: when a lead run or a subagent begins and ends, and the DeerFlow-owned
model calls made outside the graph. This slice adds both, with no new
Gateway surface -- routers, services, and the reference extension stay in
PR 3.

Contract (deerflow-extension-api 0.1.1)
---------------------------------------
Two contribution kinds join `middlewares` on the registry:
`task_lifecycle` (`on_task_start` / `on_task_stop`, receiving a `TaskInfo`
and a conservative `TaskOutcome` of completed / aborted / failed) and
`system_model_observer` (`on_system_model_call`, receiving a
`SystemOperationKind`, a `SystemModelRequest` snapshot, and a
`SystemModelResult` carrying either the response or the provider exception
plus a duration).

`SystemModelRequest.messages` normalizes to a tuple at construction. Goal
evaluation and memory extraction pass a message list while title generation
and summarization pass one prompt string, and a bare `str` already satisfies
`Sequence` -- without normalization an observer iterating `request.messages`
would silently walk characters. Copying also makes the frozen snapshot
immutable in fact rather than only by declaration, since observations may run
after the call site returns and keeps mutating its own list.

Registry marks and rollbacks become per-bucket and positional, so an
`install()` that fails after registering two different kinds cannot leave one
of them behind. `needs_task_store` now covers all three kinds: a deployment
that registers only lifecycle hooks still gets a task store.

Task lifecycle
--------------
The lead worker notifies start after the run has started and stop after
completion persistence and the completion hook, but before clearing the
finalizing barrier and publishing the stream end -- holding the barrier
across stop is what keeps a same-thread replacement run from overlapping this
task's lifecycle. Cancellation raised out of the stop notification is
deferred, not propagated in place, so a cancelled run still clears the
barrier and emits its end frame. A subagent with a parent `run_id` wraps its
execution in the same pair inside `finally`, reporting `parent_task_id` so a
delegation tree is reconstructable; a subagent without a `run_id` (embedded
client, standalone LangGraph Server) logs and skips rather than inventing a
parent. Contributors run in registration order inside one shared 3s budget
and every failure is logged and failed open.

System model calls
------------------
Four kinds cover the model calls the middleware chain cannot see: goal
evaluation, memory extraction, title generation, and summarization. Each site
reports both terminal paths without changing the provider exception the host
observes, short-circuits on `has_system_model_observers`, and passes the live
task store when the runtime has one (detached work gets an isolated store).
The sync summarization half stays unobserved on purpose -- it and its only
host caller are the sync side of an async-only runtime, so notifying there
would block a thread on a call site the host never reaches; the reason is
recorded at the call site.

The DeerMem backend must stay vendorable and cannot import the extension API,
so it reports through a new `MemoryCallbacks.on_memory_llm_result` host hook
that the DeerFlow-side callbacks translate into an observation.

Notification loop
-----------------
Extension resources must be touched on the loop that created them, but
subagents can execute on isolated loops and DeerMem runs on a worker thread.
The Gateway registers its serving loop before any runtime dependency starts
and resets it last through the exit stack, so every startup-failure and
cancellation path is covered. Awaited hooks raised on another loop are
dispatched across with `run_coroutine_threadsafe` and awaited under the same
budget; synchronous sites submit fire-and-forget work. Shutdown stops
accepting detached observations before the memory flush -- that flush runs on
a worker thread and can emit memory observations -- while keeping the loop
alive for awaited task hooks until run and subagent drain completes.

Tests
-----
`test_extension_task_lifecycle.py`, `test_extension_subagent_lifecycle.py`,
and `test_extension_system_model_calls.py` cover ordering, fail-open, budget
exhaustion, snapshot binding under a concurrent singleton replacement, the
loop-dispatch and shutdown-suspension paths, and both terminal paths at every
call site. `test_gateway_run_drain_shutdown.py` pins the stop-before-barrier
and drain ordering.

* fix(extensions): decide notification fail-open by origin, observe cancellation

`_notify_each` only guarded `Exception`, so a contributor letting a
`CancelledError` escape — an extension implementing an internal timeout with
cancellation, say — skipped its successors and reached the worker's
deferred-interrupt path, ending an otherwise successful run as cancelled.
Fail-open is about where a failure came from, not its base class: only a
genuine cancellation of the host task increments `Task.cancelling()`, so
propagate on that and contain everything else. `KeyboardInterrupt` /
`SystemExit` still propagate.

`observe_system_model_call` skipped observers on cancellation for the same
base-class reason, leaving goal / title / summarization silent on a terminal
path that is routine — interrupt/rollback admission and shutdown both cancel
the run task, with the provider tokens already spent. Awaiting observers there
is unreliable (a repeated cancel interrupts that await before any of them
runs), so report through the same non-blocking submission the synchronous
memory bridge uses, then propagate the cancellation untouched.

DeerMem keeps `BaseException` around its provider call, now with the reason
recorded: that path runs on a worker thread, where cancelling the awaiting
side never interrupts the running thread, so `CancelledError` cannot arrive
at all. Its host-hook wrapper narrows to `Exception` — only the hook's own
failures are non-fatal, and an observability path must not swallow a process
teardown signal.

* fix(extensions): warn on budget exhaustion, scope observer logs by task, propagate teardown

Review response on #4684:

- The memory observation bridge caught BaseException, which would swallow
  a teardown signal raised while dispatching; it now catches Exception,
  matching the boundary the DeerMem-side call site documents and tests.
- A notification-budget timeout raised mid-hook fell into the generic
  hook-failure path and logged an asyncio-internal traceback; it now logs
  a warning like the pre-hook budget skip, while a TimeoutError a
  contributor raises on its own stays classified as a hook failure.
- System model observer logs passed the operation kind as the task id,
  so log lines said "task goal/title/..."; they now carry the task
  scope id alongside the kind.
2026-08-11 16:33:22 +08:00

419 lines
13 KiB
Python

"""Fail-open notification helpers for extension runtime hooks."""
from __future__ import annotations
import asyncio
import logging
import time
from collections.abc import Awaitable, Callable, Coroutine, Mapping
from typing import Any
from deerflow_extension_api import (
EXTENSION_TASK_STORE_KEY,
ExtensionData,
SystemModelRequest,
SystemModelResult,
SystemOperationKind,
TaskInfo,
TaskOutcome,
)
from deerflow.extensions.registry import LoadedExtensions
logger = logging.getLogger(__name__)
def lead_task_id(run_id: str) -> str:
"""Return the stable task id for a lead run, including continuations."""
return run_id
def lead_task_outcome(*, aborted: bool, succeeded: bool) -> TaskOutcome:
"""Classify a lead run conservatively from its terminal state."""
if aborted:
return TaskOutcome.ABORTED
if succeeded:
return TaskOutcome.COMPLETED
return TaskOutcome.FAILED
def subagent_task_outcome(*, cancelled: bool, succeeded: bool) -> TaskOutcome:
"""Classify a subagent execution conservatively from its terminal state."""
if cancelled:
return TaskOutcome.ABORTED
if succeeded:
return TaskOutcome.COMPLETED
return TaskOutcome.FAILED
def _host_is_cancelling() -> bool:
"""Whether the host task itself is being cancelled.
Fail-open has to be decided by the *origin* of a failure, not by its base
class. ``CancelledError`` reaches a contributor's ``except`` for two very
different reasons: the host task was cancelled (must propagate), or the
contributor raised it on its own — an extension implementing an internal
timeout with cancellation, for instance (must stay contained). Only the
first increments the task's cancellation counter, so it is what tells the
two apart.
"""
task = asyncio.current_task()
return task is not None and task.cancelling() > 0
async def _notify_each(
contributors: tuple[tuple[str, Any], ...],
hook: str,
invoke: Callable[[Any], Any],
task_id: str,
timeout: float | None,
) -> None:
"""Invoke contributors in order, fail-open, within one shared budget."""
loop = asyncio.get_running_loop()
deadline = None if timeout is None else loop.time() + timeout
for source, contributor in contributors:
try:
call = invoke(contributor)
if deadline is None:
await call
continue
remaining = deadline - loop.time()
if remaining <= 0:
close = getattr(call, "close", None)
if callable(close):
close()
logger.warning(
"Extension %s: %s skipped for task %s; the %.1fs notification budget was spent",
source,
hook,
task_id,
timeout,
)
continue
await asyncio.wait_for(call, remaining)
except TimeoutError:
if deadline is not None and loop.time() >= deadline:
# Budget exhaustion mid-hook is the same expected operational
# condition as the skip above, so it stays a warning rather
# than a hook failure with an asyncio-internal traceback.
logger.warning(
"Extension %s: %s timed out for task %s; the %.1fs notification budget was spent",
source,
hook,
task_id,
timeout,
)
else:
# A TimeoutError the contributor raised on its own is a hook
# failure like any other.
logger.exception(
"Extension %s: %s failed for task %s",
source,
hook,
task_id,
)
except asyncio.CancelledError:
if _host_is_cancelling():
raise
# The contributor raised it, so containing it keeps one broken
# extension from skipping its successors — and, at the task-stop
# site, from turning a run's cleanup into a deferred interrupt.
logger.exception(
"Extension %s: %s raised CancelledError for task %s",
source,
hook,
task_id,
)
except Exception:
logger.exception(
"Extension %s: %s failed for task %s",
source,
hook,
task_id,
)
# Gateway registers its serving loop here. Subagents can run on isolated event
# loops, but extension resources must always be touched on the loop where they
# were started.
_notify_loop: asyncio.AbstractEventLoop | None = None
_pending_dispatches: set[asyncio.Future[Any]] = set()
_warned_no_loop = False
_system_observations_enabled = True
def set_extension_notify_loop(loop: asyncio.AbstractEventLoop | None) -> None:
"""Bind extension notifications to the loop that owns extension resources."""
global _notify_loop, _system_observations_enabled, _warned_no_loop
_notify_loop = loop
_system_observations_enabled = True
_warned_no_loop = False
def reset_extension_notify_loop() -> None:
"""Remove the process-wide loop binding during host shutdown or tests."""
global _notify_loop, _system_observations_enabled, _warned_no_loop
_notify_loop = None
_system_observations_enabled = True
_warned_no_loop = False
_pending_dispatches.clear()
def suspend_extension_system_observations() -> None:
"""Drop new fire-and-forget observations while awaited hooks still drain."""
global _system_observations_enabled
if _notify_loop is not None:
_system_observations_enabled = False
async def _notify_each_on_extension_loop(
contributors: tuple[tuple[str, Any], ...],
hook: str,
invoke: Callable[[Any], Any],
task_id: str,
timeout: float | None,
) -> None:
loop = _notify_loop
current_loop = asyncio.get_running_loop()
if loop is None or loop is current_loop:
await _notify_each(contributors, hook, invoke, task_id, timeout)
return
if not loop.is_running():
logger.warning(
"No running loop registered for awaited extension hook; %s for %s was dropped",
hook,
task_id,
)
return
notification = _notify_each(contributors, hook, invoke, task_id, timeout)
try:
future = asyncio.run_coroutine_threadsafe(notification, loop)
except Exception:
notification.close()
logger.exception(
"Could not dispatch extension %s for task %s to the registered loop",
hook,
task_id,
)
return
try:
wrapped = asyncio.wrap_future(future)
if timeout is None:
await wrapped
else:
await asyncio.wait_for(wrapped, timeout)
except TimeoutError:
future.cancel()
logger.warning(
"Extension %s dispatch timed out for task %s after %.1fs",
hook,
task_id,
timeout,
)
except asyncio.CancelledError:
future.cancel()
raise
except Exception:
logger.exception(
"Extension %s dispatch failed for task %s",
hook,
task_id,
)
async def notify_task_start(
extensions: LoadedExtensions,
task_store: ExtensionData,
info: TaskInfo,
*,
timeout: float | None = None,
) -> None:
await _notify_each_on_extension_loop(
extensions.task_lifecycle,
"on_task_start",
lambda contributor: contributor.on_task_start(
extensions.app_store,
task_store,
info,
),
info.task_id,
timeout,
)
async def notify_task_stop(
extensions: LoadedExtensions,
task_store: ExtensionData,
info: TaskInfo,
outcome: TaskOutcome,
*,
timeout: float | None = None,
) -> None:
await _notify_each_on_extension_loop(
extensions.task_lifecycle,
"on_task_stop",
lambda contributor: contributor.on_task_stop(
extensions.app_store,
task_store,
info,
outcome,
),
info.task_id,
timeout,
)
async def notify_system_model_call(
extensions: LoadedExtensions,
task_store: ExtensionData | None,
kind: SystemOperationKind,
request: SystemModelRequest,
result: SystemModelResult,
*,
timeout: float | None = None,
) -> None:
"""Notify the observers from one immutable extension snapshot."""
if not extensions.system_model_observers:
return
store = task_store if task_store is not None else ExtensionData("detached")
await _notify_each_on_extension_loop(
extensions.system_model_observers,
"on_system_model_call",
lambda observer: observer.on_system_model_call(
extensions.app_store,
store,
kind,
request,
result,
),
f"{store.scope_id} ({kind.value})",
timeout,
)
def task_store_for_system_call(invoke_config: object) -> ExtensionData | None:
"""Recover the live task store from a legacy top-level runtime context."""
if not isinstance(invoke_config, Mapping):
return None
context = invoke_config.get("context")
if not isinstance(context, Mapping):
return None
store = context.get(EXTENSION_TASK_STORE_KEY)
return store if isinstance(store, ExtensionData) else None
async def observe_system_model_call(
extensions: LoadedExtensions,
kind: SystemOperationKind,
*,
messages: Any,
model_name: str | None,
invoke_config: Any,
invoke: Callable[[], Awaitable[Any]],
task_store: ExtensionData | None = None,
timeout: float | None = None,
) -> Any:
"""Invoke a system-owned model call and report either terminal path."""
if not extensions.has_system_model_observers:
return await invoke()
store = task_store if task_store is not None else task_store_for_system_call(invoke_config)
request = SystemModelRequest(
messages=messages,
model_name=model_name,
invoke_config=(invoke_config if isinstance(invoke_config, Mapping) else None),
)
started = time.monotonic()
try:
response = await invoke()
except asyncio.CancelledError as exc:
# Cancellation is a terminal path as well: interrupt/rollback admission
# and shutdown both cancel the run task, so a user sending a follow-up
# mid-run routinely ends a goal or summarization call here, with the
# provider tokens already spent. Awaiting observers would be unreliable
# — a repeated cancel interrupts that await before any of them runs — so
# this reports through the same non-blocking submission the synchronous
# memory bridge uses, then propagates the cancellation untouched. A
# deployment with no registered notify loop drops it, exactly as that
# bridge does.
dispatch_system_model_observation(
notify_system_model_call(
extensions,
store,
kind,
request,
SystemModelResult(
error=exc,
duration_ms=(time.monotonic() - started) * 1000,
),
),
kind.value,
)
raise
except Exception as exc:
await notify_system_model_call(
extensions,
store,
kind,
request,
SystemModelResult(
error=exc,
duration_ms=(time.monotonic() - started) * 1000,
),
timeout=timeout,
)
raise
await notify_system_model_call(
extensions,
store,
kind,
request,
SystemModelResult(
response=response,
duration_ms=(time.monotonic() - started) * 1000,
),
timeout=timeout,
)
return response
def dispatch_system_model_observation(
coro: Coroutine[Any, Any, None],
what: str,
) -> bool:
"""Submit a synchronous call site's observation to the registered loop."""
global _warned_no_loop
loop = _notify_loop
submitted = False
try:
if not _system_observations_enabled:
return False
if loop is None or not loop.is_running():
if not _warned_no_loop:
_warned_no_loop = True
logger.warning(
"No running loop registered for extension observations; %s and later ones are dropped",
what,
)
return False
try:
future = asyncio.run_coroutine_threadsafe(coro, loop)
except Exception:
logger.debug(
"Could not dispatch %s to the extension notify loop",
what,
exc_info=True,
)
return False
_pending_dispatches.add(future)
future.add_done_callback(_pending_dispatches.discard)
submitted = True
return True
finally:
if not submitted:
coro.close()