revert:回退修改
This commit is contained in:
DawnARC
202
scripts/reproduce_maisaka_memory_growth.py
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202
scripts/reproduce_maisaka_memory_growth.py
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@@ -0,0 +1,202 @@
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"""
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使用方法
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python .\scripts\reproduce_maisaka_memory_growth.py --messages 100 --batch-size 50 --sessions 100 --session-batch-size 50 --payload-size 1024 --session-payload-size 1024
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"""
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from dataclasses import dataclass
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from pathlib import Path
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from types import SimpleNamespace
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from typing import Any
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import argparse
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import asyncio
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import gc
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import inspect
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import sys
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import time
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REPO_ROOT = Path(__file__).resolve().parents[1]
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if str(REPO_ROOT) not in sys.path:
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sys.path.insert(0, str(REPO_ROOT))
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class PayloadMessage:
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__slots__ = ("message_id", "timestamp", "payload")
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def __init__(self, message_id: str, payload_size: int) -> None:
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self.message_id = message_id
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self.timestamp = SimpleNamespace(timestamp=lambda: time.time())
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self.payload = bytearray(payload_size)
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@dataclass
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class FakeRuntime:
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payload: bytearray
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stopped: bool = False
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async def stop(self) -> None:
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self.stopped = True
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def prune_runtime_caches(self) -> None:
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return None
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def _bool_cn(value: bool) -> str:
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return "是" if value else "否"
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def _build_maisaka_runtime_stub(max_cache_size: int) -> Any:
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from src.learners.expression_learner import ExpressionLearner
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from src.maisaka.runtime import MaisakaHeartFlowChatting
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runtime = object.__new__(MaisakaHeartFlowChatting)
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runtime._running = False
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runtime._last_message_received_at = 0.0
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runtime._last_processed_index = 0
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runtime._message_cache_max_size = max_cache_size
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runtime.message_cache = []
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runtime._message_received_at_by_id = {}
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runtime._source_messages_by_id = {}
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runtime.history_loop = []
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runtime.log_prefix = "[memory-repro]"
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runtime._expression_learner = ExpressionLearner("memory-repro-session")
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runtime._enable_expression_learning = False
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runtime._enable_jargon_learning = False
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runtime._agent_state = "idle"
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runtime._STATE_RUNNING = "running"
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runtime._reply_latency_measurement_started_at = None
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runtime._message_debounce_required = False
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runtime._update_message_trigger_state = lambda message: None
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runtime._is_reply_effect_tracking_enabled = lambda: False
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return runtime
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def _mark_expression_learner_consumed(runtime: Any) -> None:
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learner = runtime._expression_learner
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if hasattr(learner, "set_processed_message_cache_index"):
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learner.set_processed_message_cache_index(len(runtime.message_cache))
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return
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if hasattr(learner, "_last_processed_index"):
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learner._last_processed_index = len(runtime.message_cache)
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async def _maybe_call_runtime_prune(runtime: Any) -> bool:
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prune_runtime_caches = getattr(runtime, "prune_runtime_caches", None)
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if not callable(prune_runtime_caches):
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return False
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result = prune_runtime_caches()
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if inspect.isawaitable(result):
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await result
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return True
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async def probe_maisaka_message_cache(args: argparse.Namespace) -> bool:
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from src.maisaka.runtime import MaisakaHeartFlowChatting
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runtime = _build_maisaka_runtime_stub(args.max_cache_size)
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print("[Maisaka 消息缓存]")
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print("批次,累计注册消息数,缓存消息数,原始消息映射数,已处理下标,MB")
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for index in range(args.messages):
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message = PayloadMessage(f"m{index}", args.payload_size)
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await MaisakaHeartFlowChatting.register_message(runtime, message)
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if (index + 1) % args.batch_size != 0:
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continue
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MaisakaHeartFlowChatting._collect_pending_messages(runtime)
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if args.call_prune:
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_mark_expression_learner_consumed(runtime)
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await _maybe_call_runtime_prune(runtime)
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gc.collect()
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retained_payload = sum(len(message.payload) for message in runtime.message_cache)
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print(
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f"{(index + 1) // args.batch_size},"
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f"{index + 1},"
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f"{len(runtime.message_cache)},"
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f"{len(runtime._source_messages_by_id)},"
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f"{runtime._last_processed_index},"
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f"{retained_payload / 1024 / 1024:.2f}"
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)
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issue_observed = len(runtime.message_cache) > args.max_cache_size
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print(f"是否观察到无界增长={_bool_cn(issue_observed)}")
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return issue_observed
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async def probe_heartflow_session_registry(args: argparse.Namespace) -> bool:
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from src.chat.heart_flow.heartflow_manager import HeartflowManager
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manager = HeartflowManager()
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print("\n[Heartflow 会话注册表]")
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print("批次,累计会话数,注册表长度,锁数量,MB")
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for index in range(args.sessions):
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session_id = f"session-{index}"
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runtime = FakeRuntime(bytearray(args.session_payload_size))
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manager.heartflow_chat_list[session_id] = runtime
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manager._chat_create_locks[session_id] = None
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if hasattr(manager, "_last_access_at"):
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manager._last_access_at[session_id] = 100.0
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if (index + 1) % args.session_batch_size != 0:
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continue
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retained_payload = sum(len(runtime.payload) for runtime in manager.heartflow_chat_list.values())
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print(
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f"{(index + 1) // args.session_batch_size},"
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f"{index + 1},"
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f"{len(manager.heartflow_chat_list)},"
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f"{len(manager._chat_create_locks)},"
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f"{retained_payload / 1024 / 1024:.2f}"
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)
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if args.call_cleanup:
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cleanup_idle_chats = getattr(manager, "cleanup_idle_chats", None)
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if callable(cleanup_idle_chats):
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cleanup_now = 100.0 + (6 * 60 * 60) + 1.0
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await cleanup_idle_chats(now=cleanup_now)
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issue_observed = len(manager.heartflow_chat_list) == args.sessions
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print(f"剩余会话数={len(manager.heartflow_chat_list)}")
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print(f"是否观察到会话未释放={_bool_cn(issue_observed)}")
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return issue_observed
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="复现")
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parser.add_argument("--messages", type=int, default=6000)
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parser.add_argument("--batch-size", type=int, default=1000)
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parser.add_argument("--payload-size", type=int, default=16 * 1024)
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parser.add_argument("--max-cache-size", type=int, default=200)
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parser.add_argument("--sessions", type=int, default=3000)
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parser.add_argument("--session-batch-size", type=int, default=500)
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parser.add_argument("--session-payload-size", type=int, default=32 * 1024)
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parser.add_argument(
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"--call-prune",
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action="store_true",
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help="每个消息批次结束后，如运行时提供裁剪hook则主动调用",
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)
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parser.add_argument(
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"--call-cleanup",
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action="store_true",
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help="填充会话注册表后，如 HeartflowManager 提供清理方法则主动调用",
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)
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return parser.parse_args()
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async def main() -> None:
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args = parse_args()
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message_issue = await probe_maisaka_message_cache(args)
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session_issue = await probe_heartflow_session_registry(args)
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print("\n[汇总]")
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print(f"消息缓存问题是否复现={_bool_cn(message_issue)}")
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print(f"会话注册表问题是否复现={_bool_cn(session_issue)}")
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -1,5 +1,4 @@
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import asyncio
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import time
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import traceback
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from typing import Dict
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@@ -10,10 +9,6 @@ from src.maisaka.runtime import MaisakaHeartFlowChatting
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logger = get_logger("heartflow")
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HEARTFLOW_RUNTIME_IDLE_TTL_SECONDS = 6 * 60 * 60
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HEARTFLOW_RUNTIME_MAX_SESSIONS = 512
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HEARTFLOW_RUNTIME_CLEANUP_INTERVAL_SECONDS = 5 * 60
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class HeartflowManager:
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"""管理 session 级别的 Maisaka 心流实例。"""
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@@ -21,91 +16,25 @@ class HeartflowManager:
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def __init__(self) -> None:
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self.heartflow_chat_list: Dict[str, MaisakaHeartFlowChatting] = {}
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self._chat_create_locks: Dict[str, asyncio.Lock] = {}
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self._last_access_at: Dict[str, float] = {}
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self._last_cleanup_at = 0.0
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async def _stop_runtime(self, session_id: str, chat: MaisakaHeartFlowChatting) -> None:
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try:
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await chat.stop()
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except Exception as exc:
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logger.warning(f"清理心流聊天 {session_id} 时停止 runtime 失败: {exc}", exc_info=True)
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def _prune_runtime_caches(self, chat: MaisakaHeartFlowChatting) -> None:
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prune_runtime_caches = getattr(chat, "prune_runtime_caches", None)
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if callable(prune_runtime_caches):
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prune_runtime_caches()
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async def cleanup_idle_chats(self, *, now: float | None = None, exclude_session_ids: set[str] | None = None) -> None:
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"""清理长期空闲或超过容量的 Maisaka runtime。"""
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current_time = time.time() if now is None else now
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excluded_session_ids = exclude_session_ids or set()
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expire_before = current_time - HEARTFLOW_RUNTIME_IDLE_TTL_SECONDS
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session_ids_to_remove = [
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session_id
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for session_id, accessed_at in self._last_access_at.items()
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if accessed_at < expire_before and session_id not in excluded_session_ids
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]
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active_count_after_idle = len(self.heartflow_chat_list) - len(set(session_ids_to_remove))
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if active_count_after_idle > HEARTFLOW_RUNTIME_MAX_SESSIONS:
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overflow_count = active_count_after_idle - HEARTFLOW_RUNTIME_MAX_SESSIONS
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active_session_ids = [
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session_id
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for session_id in self.heartflow_chat_list
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if session_id not in session_ids_to_remove
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and session_id not in excluded_session_ids
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]
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active_session_ids.sort(key=lambda session_id: self._last_access_at.get(session_id, 0.0))
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session_ids_to_remove.extend(active_session_ids[:overflow_count])
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self._last_cleanup_at = current_time
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removed_count = 0
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for session_id in dict.fromkeys(session_ids_to_remove):
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chat = self.heartflow_chat_list.pop(session_id, None)
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self._chat_create_locks.pop(session_id, None)
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self._last_access_at.pop(session_id, None)
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if chat is None:
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continue
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await self._stop_runtime(session_id, chat)
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removed_count += 1
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if removed_count > 0:
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logger.info(f"已清理空闲心流聊天: 数量={removed_count} 剩余={len(self.heartflow_chat_list)}")
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async def _cleanup_idle_chats_if_due(self, *, now: float, exclude_session_id: str) -> None:
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cleanup_due = now - self._last_cleanup_at >= HEARTFLOW_RUNTIME_CLEANUP_INTERVAL_SECONDS
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capacity_exceeded = len(self.heartflow_chat_list) >= HEARTFLOW_RUNTIME_MAX_SESSIONS
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if not cleanup_due and not capacity_exceeded:
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return
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await self.cleanup_idle_chats(now=now, exclude_session_ids={exclude_session_id})
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async def get_or_create_heartflow_chat(self, session_id: str) -> MaisakaHeartFlowChatting:
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"""获取或创建指定会话对应的 Maisaka runtime。"""
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try:
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current_time = time.time()
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if chat := self.heartflow_chat_list.get(session_id):
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self._last_access_at[session_id] = current_time
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self._prune_runtime_caches(chat)
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await self._cleanup_idle_chats_if_due(now=current_time, exclude_session_id=session_id)
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return chat
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create_lock = self._chat_create_locks.setdefault(session_id, asyncio.Lock())
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async with create_lock:
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current_time = time.time()
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if chat := self.heartflow_chat_list.get(session_id):
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self._last_access_at[session_id] = current_time
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self._prune_runtime_caches(chat)
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await self._cleanup_idle_chats_if_due(now=current_time, exclude_session_id=session_id)
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return chat
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chat_session = chat_manager.get_session_by_session_id(session_id)
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if not chat_session:
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raise ValueError(f"未找到 session_id={session_id} 对应的聊天流")
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await self._cleanup_idle_chats_if_due(now=current_time, exclude_session_id=session_id)
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new_chat = MaisakaHeartFlowChatting(session_id=session_id)
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await new_chat.start()
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self.heartflow_chat_list[session_id] = new_chat
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self._last_access_at[session_id] = current_time
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return new_chat
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except Exception as exc:
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logger.error(f"创建心流聊天 {session_id} 失败: {exc}", exc_info=True)
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@@ -941,7 +941,6 @@ class MaisakaReasoningEngine:
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"""结束并记录一轮 Maisaka 思考循环。"""
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cycle_detail.end_time = time.time()
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self._runtime.history_loop.append(cycle_detail)
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self._runtime.prune_runtime_caches()
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self._post_process_chat_history_after_cycle()
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timer_strings = [
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@@ -56,9 +56,6 @@ from .tool_provider import MaisakaBuiltinToolProvider
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logger = get_logger("maisaka_runtime")
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MAX_INTERNAL_ROUNDS = 10
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MESSAGE_CACHE_MIN_RETAINED = 200
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MESSAGE_CACHE_CONTEXT_MULTIPLIER = 4
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HISTORY_LOOP_MAX_RETAINED = 256
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class MaisakaHeartFlowChatting:
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@@ -85,7 +82,7 @@ class MaisakaHeartFlowChatting:
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self._chat_history: list[LLMContextMessage] = []
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self.history_loop: list[CycleDetail] = []
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# Keep recent original messages for batching, tools, and later learning.
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# Keep all original messages for batching and later learning.
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self.message_cache: list[SessionMessage] = []
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self._last_processed_index = 0
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self._internal_turn_queue: asyncio.Queue[Literal["message", "timeout"]] = asyncio.Queue()
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@@ -114,10 +111,6 @@ class MaisakaHeartFlowChatting:
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else global_config.chat.max_private_context_size
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)
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self._max_context_size = max(1, int(configured_context_size))
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self._message_cache_max_size = max(
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MESSAGE_CACHE_MIN_RETAINED,
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self._max_context_size * MESSAGE_CACHE_CONTEXT_MULTIPLIER,
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)
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self._agent_state: Literal["running", "wait", "stop"] = self._STATE_STOP
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self._pending_wait_tool_call_id: Optional[str] = None
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self._force_next_timing_continue = False
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@@ -947,54 +940,6 @@ class MaisakaHeartFlowChatting:
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def _has_pending_messages(self) -> bool:
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return self._last_processed_index < len(self.message_cache)
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def _get_expression_learner_processed_index(self) -> int:
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learner_index = getattr(self._expression_learner, "_last_processed_index", self._last_processed_index)
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try:
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return max(0, int(learner_index))
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except (TypeError, ValueError):
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return self._last_processed_index
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def _adjust_expression_learner_processed_index(self, removed_count: int) -> None:
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if not hasattr(self._expression_learner, "_last_processed_index"):
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return
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learner_index = self._get_expression_learner_processed_index()
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setattr(self._expression_learner, "_last_processed_index", max(0, learner_index - removed_count))
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def _prune_processed_message_cache(self) -> None:
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"""Trim old processed messages while preserving pending and learning windows."""
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max_size = max(1, int(getattr(self, "_message_cache_max_size", MESSAGE_CACHE_MIN_RETAINED)))
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overflow_count = len(self.message_cache) - max_size
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if overflow_count <= 0:
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return
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processed_boundary = self._last_processed_index
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removable_count = min(overflow_count, processed_boundary)
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if removable_count <= 0:
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return
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removed_messages = self.message_cache[:removable_count]
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removed_message_ids = {message.message_id for message in removed_messages}
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del self.message_cache[:removable_count]
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self._last_processed_index = max(0, self._last_processed_index - removable_count)
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self._adjust_expression_learner_processed_index(removable_count)
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retained_message_ids = {message.message_id for message in self.message_cache}
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for message_id in removed_message_ids:
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if message_id not in retained_message_ids:
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self._message_received_at_by_id.pop(message_id, None)
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self._source_messages_by_id.pop(message_id, None)
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||||
logger.debug(
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||||
f"{self.log_prefix} 已裁剪 Maisaka 消息缓存: "
|
||||
f"移除={removable_count} 剩余={len(self.message_cache)} 上限={max_size}"
|
||||
)
|
||||
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||||
def prune_runtime_caches(self) -> None:
|
||||
"""Apply bounded retention to runtime-only in-memory histories."""
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||||
self._prune_processed_message_cache()
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||||
if len(self.history_loop) > HISTORY_LOOP_MAX_RETAINED:
|
||||
del self.history_loop[: len(self.history_loop) - HISTORY_LOOP_MAX_RETAINED]
|
||||
|
||||
def _schedule_message_turn(self) -> None:
|
||||
"""为当前待处理消息安排一次内部 turn。"""
|
||||
if self._agent_state == self._STATE_WAIT:
|
||||
|
||||
Reference in New Issue
Block a user