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fix(memory): replace short-lived asyncio.run() with persistent event loop (#2627)

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* fix(memory): replace short-lived asyncio.run() with persistent event loop to prevent zombie httpx connections

  The memory updater used asyncio.run() inside daemon threads, creating
  and destroying short-lived event loops on every update. Langchain
  providers (e.g. langchain-anthropic) cache httpx AsyncClient instances
  globally via @lru_cache, so SSL connections created on a loop that is
  subsequently destroyed become zombie connections in the shared pool.
  When the main agent's lead run later reuses one of these connections,
  httpx/anyio triggers RuntimeError: Event loop is closed during
  connection cleanup.

  Replace the ThreadPoolExecutor + asyncio.run() pattern with a
  _MemoryLoopRunner that maintains a single persistent event loop in a
  daemon thread for the process lifetime. Since the loop never closes,
  connections bound to it never become invalid. The _run_async_update_sync
  function now submits coroutines to this persistent loop via
  run_coroutine_threadsafe instead of creating throwaway loops.

* update the code to address the review comments

* Fix the review comments of 2615

 P1 — user_id forwarded through sync path: Added user_id parameter to _prepare_update_prompt, _finalize_update, and _do_update_memory_sync, and forwarded it to get_memory_data(agent_name, user_id=user_id) and
  save(..., user_id=user_id). The update_memory() entry point now passes user_id through both the executor.submit path and the direct call path. Added TestUserIdForwarding with two regression tests (sync + async)
   verifying get_memory_data and save receive the correct user_id.

  P2 — aupdate_memory() delegates to sync: Replaced the model.ainvoke() call with asyncio.to_thread(self._do_update_memory_sync, ...). This eliminates the unsafe async provider client path entirely — all memory
  updater entry points now use the isolated sync model.invoke() path. Updated the test from asserting ainvoke is awaited to asserting invoke is called and ainvoke is not.

  Nit — duplicate comment removed: Removed the duplicated # Matches sentences... comment on line 230.

* Chore(test): update the code of test_memory_updater

---------

Co-authored-by: rayhpeng <rayhpeng@gmail.com>
This commit is contained in:
Willem Jiang
2026-04-30 17:59:57 +08:00
committed by GitHub
parent 7dea1666ce
commit c0da278269
2 changed files with 240 additions and 88 deletions
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backend/packages/harness/deerflow/agents/memory/updater.py
+89 -51
View File
@@ -9,7 +9,6 @@ import logging
import math
import re
import uuid
from collections.abc import Awaitable
from typing import Any
from deerflow.agents.memory.prompt import (
@@ -26,6 +25,12 @@ from deerflow.models import create_chat_model
logger = logging.getLogger(__name__)
# Thread pool for offloading sync memory updates when called from an async
# context. Unlike the previous asyncio.run() approach, this runs *sync*
# model.invoke() calls — no event loop is created, so the langchain async
# httpx client pool (globally cached via @lru_cache) is never touched and
# cross-loop connection reuse is impossible.
_SYNC_MEMORY_UPDATER_EXECUTOR = concurrent.futures.ThreadPoolExecutor(
max_workers=4,
thread_name_prefix="memory-updater-sync",
@@ -222,39 +227,6 @@ def _extract_text(content: Any) -> str:
return str(content)
def _run_async_update_sync(coro: Awaitable[bool]) -> bool:
"""Run an async memory update from sync code, including nested-loop contexts."""
handed_off = False
try:
try:
loop = asyncio.get_running_loop()
except RuntimeError:
loop = None
if loop is not None and loop.is_running():
future = _SYNC_MEMORY_UPDATER_EXECUTOR.submit(asyncio.run, coro)
handed_off = True
return future.result()
handed_off = True
return asyncio.run(coro)
except Exception:
if not handed_off:
close = getattr(coro, "close", None)
if callable(close):
try:
close()
except Exception:
logger.debug(
"Failed to close un-awaited memory update coroutine",
exc_info=True,
)
logger.exception("Failed to run async memory update from sync context")
return False
# Matches sentences that describe a file-upload *event* rather than general
# file-related work. Deliberately narrow to avoid removing legitimate facts
# such as "User works with CSV files" or "prefers PDF export".
@@ -349,13 +321,14 @@ class MemoryUpdater:
agent_name: str | None,
correction_detected: bool,
reinforcement_detected: bool,
user_id: str | None = None,
) -> tuple[dict[str, Any], str] | None:
"""Load memory and build the update prompt for a conversation."""
config = get_memory_config()
if not config.enabled or not messages:
return None
current_memory = get_memory_data(agent_name)
current_memory = get_memory_data(agent_name, user_id=user_id)
conversation_text = format_conversation_for_update(messages)
if not conversation_text.strip():
return None
@@ -377,6 +350,7 @@ class MemoryUpdater:
response_content: Any,
thread_id: str | None,
agent_name: str | None,
user_id: str | None = None,
) -> bool:
"""Parse the model response, apply updates, and persist memory."""
response_text = _extract_text(response_content).strip()
@@ -390,7 +364,7 @@ class MemoryUpdater:
# cannot corrupt the still-cached original object reference.
updated_memory = self._apply_updates(copy.deepcopy(current_memory), update_data, thread_id)
updated_memory = _strip_upload_mentions_from_memory(updated_memory)
return get_memory_storage().save(updated_memory, agent_name)
return get_memory_storage().save(updated_memory, agent_name, user_id=user_id)
async def aupdate_memory(
self,
@@ -399,28 +373,63 @@ class MemoryUpdater:
agent_name: str | None = None,
correction_detected: bool = False,
reinforcement_detected: bool = False,
user_id: str | None = None,
) -> bool:
"""Update memory asynchronously based on conversation messages."""
"""Update memory asynchronously by delegating to the sync path.
Uses ``asyncio.to_thread`` to run the *sync* ``model.invoke()`` path
in a worker thread so no second event loop is created and the
langchain async httpx client pool (shared with the lead agent) is
never touched. This eliminates the cross-loop connection-reuse bug
described in issue #2615.
"""
return await asyncio.to_thread(
self._do_update_memory_sync,
messages=messages,
thread_id=thread_id,
agent_name=agent_name,
correction_detected=correction_detected,
reinforcement_detected=reinforcement_detected,
user_id=user_id,
)
def _do_update_memory_sync(
self,
messages: list[Any],
thread_id: str | None = None,
agent_name: str | None = None,
correction_detected: bool = False,
reinforcement_detected: bool = False,
user_id: str | None = None,
) -> bool:
"""Pure-sync memory update using ``model.invoke()``.
Uses the *sync* LLM call path so no event loop is created. This
guarantees that the langchain provider's globally cached async
httpx ``AsyncClient`` / connection pool (the one shared with the
lead agent) is never touched — no cross-loop connection reuse is
possible.
"""
try:
prepared = await asyncio.to_thread(
self._prepare_update_prompt,
prepared = self._prepare_update_prompt(
messages=messages,
agent_name=agent_name,
correction_detected=correction_detected,
reinforcement_detected=reinforcement_detected,
user_id=user_id,
)
if prepared is None:
return False
current_memory, prompt = prepared
model = self._get_model()
response = await model.ainvoke(prompt, config={"run_name": "memory_agent"})
return await asyncio.to_thread(
self._finalize_update,
response = model.invoke(prompt, config={"run_name": "memory_agent"})
return self._finalize_update(
current_memory=current_memory,
response_content=response.content,
thread_id=thread_id,
agent_name=agent_name,
user_id=user_id,
)
except json.JSONDecodeError as e:
logger.warning("Failed to parse LLM response for memory update: %s", e)
@@ -438,7 +447,16 @@ class MemoryUpdater:
reinforcement_detected: bool = False,
user_id: str | None = None,
) -> bool:
"""Synchronously update memory via the async updater path.
"""Synchronously update memory using the sync LLM path.
Uses ``model.invoke()`` (sync HTTP) which operates on a completely
separate connection pool from the async ``AsyncClient`` shared by
the lead agent. This eliminates the cross-loop connection-reuse
bug described in issue #2615.
When called from within a running event loop (e.g. from a LangGraph
node), the blocking sync call is offloaded to a thread pool so the
caller's loop is not blocked.
Args:
messages: List of conversation messages.
@@ -451,14 +469,34 @@ class MemoryUpdater:
Returns:
True if update was successful, False otherwise.
"""
return _run_async_update_sync(
self.aupdate_memory(
messages=messages,
thread_id=thread_id,
agent_name=agent_name,
correction_detected=correction_detected,
reinforcement_detected=reinforcement_detected,
)
try:
loop = asyncio.get_running_loop()
except RuntimeError:
loop = None
if loop is not None and loop.is_running():
try:
future = _SYNC_MEMORY_UPDATER_EXECUTOR.submit(
self._do_update_memory_sync,
messages=messages,
thread_id=thread_id,
agent_name=agent_name,
correction_detected=correction_detected,
reinforcement_detected=reinforcement_detected,
user_id=user_id,
)
return future.result()
except Exception:
logger.exception("Failed to offload memory update to executor")
return False
return self._do_update_memory_sync(
messages=messages,
thread_id=thread_id,
agent_name=agent_name,
correction_detected=correction_detected,
reinforcement_detected=reinforcement_detected,
user_id=user_id,
)
def _apply_updates(