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fix:完善Maisaka记忆写回链路

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补齐聊天摘要自动写回、发送后同步与图存储清理逻辑，对齐 visual 新配置字段并补充相关回归测试，同时忽略 algorithm_redesign 设计目录。
This commit is contained in:
A-Dawn
2026-04-16 19:04:08 +08:00
parent 7ed5630583
commit 459927e7c0
13 changed files with 918 additions and 65 deletions
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3
src/A_memorix/core/runtime/sdk_memory_kernel.py
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@@ -802,6 +802,7 @@ class SDKMemoryKernel:
chat_id: str,
context_length: Optional[int] = None,
include_personality: Optional[bool] = None,
time_end: Optional[float] = None,
) -> Dict[str, Any]:
await self.initialize()
assert self.summary_importer
@@ -809,6 +810,7 @@ class SDKMemoryKernel:
stream_id=str(chat_id or "").strip(),
context_length=context_length,
include_personality=include_personality,
time_end=time_end,
)
if success:
await self.rebuild_episodes_for_sources([self._build_source("chat_summary", chat_id, [])])
@@ -851,6 +853,7 @@ class SDKMemoryKernel:
chat_id=chat_id,
context_length=self._optional_int(summary_meta.get("context_length")),
include_personality=summary_meta.get("include_personality"),
time_end=time_end,
)
result.setdefault("external_id", external_id)
result.setdefault("chat_id", chat_id)

19
src/A_memorix/core/storage/graph_store.py
View File

@@ -1190,11 +1190,14 @@ class GraphStore:
data_dir.mkdir(parents=True, exist_ok=True)
# 保存邻接矩阵
matrix_path = data_dir / "graph_adjacency.npz"
if self._adjacency is not None:
matrix_path = data_dir / "graph_adjacency.npz"
with atomic_write(matrix_path, "wb") as f:
save_npz(f, self._adjacency)
logger.debug(f"保存邻接矩阵: {matrix_path}")
elif matrix_path.exists():
matrix_path.unlink()
logger.debug(f"删除陈旧邻接矩阵: {matrix_path}")
# 保存元数据
metadata = {
@@ -1288,9 +1291,20 @@ class GraphStore:
if self._adjacency is not None:
adj_n = self._adjacency.shape[0]
current_n = len(self._nodes)
if current_n > adj_n:
if current_n == 0:
logger.warning("检测到空图元数据但邻接矩阵仍然存在，已重置为空图。")
self._adjacency = None
elif current_n > adj_n:
logger.warning(f"检测到图存储维度不匹配: 节点数={current_n}, 矩阵大小={adj_n}. 正在自动修复...")
self._expand_adjacency_matrix(current_n - adj_n)
elif current_n < adj_n:
logger.warning(
f"检测到过期邻接矩阵: 节点数={current_n}, 矩阵大小={adj_n}. 正在重置邻接矩阵..."
)
if self.matrix_format == "csc":
self._adjacency = csc_matrix((current_n, current_n), dtype=np.float32)
else:
self._adjacency = csr_matrix((current_n, current_n), dtype=np.float32)
self._adjacency_dirty = True
logger.info(
@@ -1445,4 +1459,3 @@ class GraphStore:
self._adjacency_dirty = True
logger.info(f"已从 {count} 条哈希重建边哈希映射，覆盖 {len(self._edge_hash_map)} 条边")
return count

22
src/A_memorix/core/utils/summary_importer.py
View File

@@ -5,12 +5,13 @@
导入到 A_memorix 的存储组件中。
"""
import time
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
import json
import re
import time
import traceback
from typing import List, Dict, Any, Tuple, Optional
from pathlib import Path
from src.common.logger import get_logger
from src.services import llm_service as llm_api
@@ -222,7 +223,8 @@ class SummaryImporter:
self,
stream_id: str,
context_length: Optional[int] = None,
include_personality: Optional[bool] = None
include_personality: Optional[bool] = None,
time_end: Optional[float] = None,
) -> Tuple[bool, str]:
"""
从指定的聊天流中提取记录并执行总结导入
@@ -231,6 +233,7 @@ class SummaryImporter:
stream_id: 聊天流 ID
context_length: 总结的历史消息条数
include_personality: 是否包含人设
time_end: 用于截取聊天记录的时间上界（闭区间）
Returns:
Tuple[bool, str]: (是否成功, 结果消息)
@@ -248,12 +251,13 @@ class SummaryImporter:
include_personality = self.plugin_config.get("summarization", {}).get("include_personality", True)
# 2. 获取历史消息
# 获取当前时间之前的消息
now = time.time()
messages = message_api.get_messages_before_time_in_chat(
query_time_end = time.time() if time_end is None else float(time_end)
messages = message_api.get_messages_by_time_in_chat(
chat_id=stream_id,
timestamp=now,
limit=context_length
start_time=0.0,
end_time=query_time_end,
limit=context_length,
limit_mode="latest",
)
if not messages:

13
src/config/legacy_migration.py
View File

@@ -282,6 +282,10 @@ def try_migrate_legacy_bot_config_dict(data: dict[str, Any]) -> MigrationResult:
personality = _as_dict(data.get("personality"))
visual = _as_dict(data.get("visual"))
if visual is None and personality is not None and "visual_style" in personality:
visual = {}
data["visual"] = visual
if visual is not None and personality is not None and "visual_style" in personality:
if "visual_style" not in visual:
visual["visual_style"] = personality["visual_style"]
@@ -289,15 +293,6 @@ def try_migrate_legacy_bot_config_dict(data: dict[str, Any]) -> MigrationResult:
migrated_any = True
reasons.append("personality.visual_style_moved_to_visual.visual_style")
if visual is not None and "multimodal_planner" in visual and "planner_mode" not in visual:
multimodal_planner = visual.pop("multimodal_planner")
if isinstance(multimodal_planner, bool):
visual["planner_mode"] = "multimodal" if multimodal_planner else "text"
migrated_any = True
reasons.append("visual.multimodal_planner_moved_to_visual.planner_mode")
else:
visual["multimodal_planner"] = multimodal_planner
memory = _as_dict(data.get("memory"))
if memory is not None and _migrate_target_item_list(memory, "global_memory_blacklist"):
migrated_any = True

46
src/config/official_configs.py
View File

@@ -145,23 +145,23 @@ class VisualConfig(ConfigBase):
__ui_label__ = "视觉"
__ui_icon__ = "image"
multimodal_planner: bool = Field(
default=True,
planner_mode: Literal["text", "multimodal", "auto"] = Field(
default="text",
json_schema_extra={
"x-widget": "switch",
"x-widget": "select",
"x-icon": "image",
},
)
"""是否直接输入图片"""
"""Planner 视觉模式：text 仅文本，multimodal 强制多模态，auto 按模型能力自动选择"""
multimodal_replyer: bool = Field(
default=False,
replyer_mode: Literal["text", "multimodal", "auto"] = Field(
default="text",
json_schema_extra={
"x-widget": "switch",
"x-widget": "select",
"x-icon": "git-branch",
},
)
"""是否启用 Maisaka 多模态 replyer 生成器"""
"""Replyer 视觉模式：text 仅文本，multimodal 强制多模态，auto 按模型能力自动选择"""
visual_style: str = Field(
default="请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多30字，请注意不要分点，就输出一段文本",
@@ -424,6 +424,36 @@ class MemoryConfig(ConfigBase):
)
"""是否在发送回复后自动提取并写回人物事实到长期记忆"""
chat_summary_writeback_enabled: bool = Field(
default=True,
json_schema_extra={
"x-widget": "switch",
"x-icon": "scroll-text",
},
)
"""是否在 Maisaka 聊天过程中按消息窗口自动写回聊天摘要到长期记忆"""
chat_summary_writeback_message_threshold: int = Field(
default=12,
ge=1,
json_schema_extra={
"x-widget": "input",
"x-icon": "messages-square",
},
)
"""自动写回聊天摘要的消息窗口阈值"""
chat_summary_writeback_context_length: int = Field(
default=50,
ge=1,
le=500,
json_schema_extra={
"x-widget": "input",
"x-icon": "rows-3",
},
)
"""自动写回聊天摘要时，从聊天流中回看的消息条数"""
feedback_correction_enabled: bool = Field(
default=False,
json_schema_extra={

174
src/services/memory_flow_service.py
View File

@@ -1,16 +1,21 @@
from __future__ import annotations
from dataclasses import dataclass
from datetime import datetime
from typing import Any, List, Optional
import asyncio
import json
from typing import Any, List, Optional
import time
from json_repair import repair_json
from src.chat.utils.utils import is_bot_self
from src.common.logger import get_logger
from src.common.message_repository import find_messages
from src.common.message_repository import count_messages, find_messages
from src.config.config import global_config
from src.person_info.person_info import Person, get_person_id, store_person_memory_from_answer
from src.services.memory_service import memory_service
from src.services.llm_service import LLMServiceClient
logger = get_logger("memory_flow_service")
@@ -210,27 +215,192 @@ class PersonFactWritebackService:
return False
@dataclass
class ChatSummaryWritebackState:
last_trigger_message_count: int = 0
last_trigger_time: float = 0.0
class ChatSummaryWritebackService:
def __init__(self) -> None:
self._queue: asyncio.Queue[Any] = asyncio.Queue(maxsize=256)
self._worker_task: Optional[asyncio.Task] = None
self._stopping = False
self._states: dict[str, ChatSummaryWritebackState] = {}
async def start(self) -> None:
if self._worker_task is not None and not self._worker_task.done():
return
self._stopping = False
self._worker_task = asyncio.create_task(self._worker_loop(), name="memory_chat_summary_writeback")
async def shutdown(self) -> None:
self._stopping = True
worker = self._worker_task
self._worker_task = None
if worker is None:
return
worker.cancel()
try:
await worker
except asyncio.CancelledError:
pass
except Exception as exc:
logger.warning("关闭聊天摘要写回 worker 失败: %s", exc)
async def enqueue(self, message: Any) -> None:
if not bool(getattr(global_config.memory, "chat_summary_writeback_enabled", True)):
return
if self._stopping:
return
try:
self._queue.put_nowait(message)
except asyncio.QueueFull:
logger.warning("聊天摘要写回队列已满，跳过本次触发")
async def _worker_loop(self) -> None:
try:
while not self._stopping:
message = await self._queue.get()
try:
await self._handle_message(message)
except Exception as exc:
logger.warning("聊天摘要写回处理失败: %s", exc, exc_info=True)
finally:
self._queue.task_done()
except asyncio.CancelledError:
raise
async def _handle_message(self, message: Any) -> None:
session_id = self._resolve_session_id(message)
if not session_id:
return
total_message_count = count_messages(session_id=session_id)
if total_message_count <= 0:
return
threshold = self._message_threshold()
state = self._states.setdefault(session_id, ChatSummaryWritebackState())
pending_message_count = max(0, total_message_count - state.last_trigger_message_count)
if pending_message_count < threshold:
return
context_length = self._context_length()
message_time = self._extract_message_timestamp(message)
result = await memory_service.ingest_summary(
external_id=f"chat_auto_summary:{session_id}:{total_message_count}",
chat_id=session_id,
text="",
participants=[],
time_end=message_time,
metadata={
"generate_from_chat": True,
"context_length": context_length,
"writeback_source": "memory_flow_service",
"trigger": "message_threshold",
"trigger_message_count": total_message_count,
},
respect_filter=True,
user_id=self._extract_session_user_id(message),
group_id=self._extract_session_group_id(message),
)
if not getattr(result, "success", False):
logger.warning(
"聊天摘要自动写回失败: session_id=%s detail=%s",
session_id,
getattr(result, "detail", ""),
)
return
state.last_trigger_message_count = total_message_count
state.last_trigger_time = time.time()
logger.info(
"聊天摘要自动写回成功: session_id=%s trigger=%s total_messages=%s context_length=%s detail=%s",
session_id,
"message_threshold",
total_message_count,
context_length,
getattr(result, "detail", ""),
)
@staticmethod
def _resolve_session_id(message: Any) -> str:
return str(
getattr(message, "session_id", "")
or getattr(getattr(message, "session", None), "session_id", "")
or ""
).strip()
@staticmethod
def _extract_session_user_id(message: Any) -> str:
return str(
getattr(getattr(message, "session", None), "user_id", "")
or getattr(message, "user_id", "")
or ""
).strip()
@staticmethod
def _extract_session_group_id(message: Any) -> str:
return str(
getattr(getattr(message, "session", None), "group_id", "")
or getattr(message, "group_id", "")
or ""
).strip()
@staticmethod
def _extract_message_timestamp(message: Any) -> float | None:
raw_timestamp = getattr(message, "timestamp", None)
if isinstance(raw_timestamp, datetime):
return raw_timestamp.timestamp()
if hasattr(raw_timestamp, "timestamp") and callable(raw_timestamp.timestamp):
try:
return float(raw_timestamp.timestamp())
except Exception:
return None
if isinstance(raw_timestamp, (int, float)):
return float(raw_timestamp)
return None
@staticmethod
def _message_threshold() -> int:
return max(1, int(getattr(global_config.memory, "chat_summary_writeback_message_threshold", 12) or 12))
@staticmethod
def _context_length() -> int:
return max(1, int(getattr(global_config.memory, "chat_summary_writeback_context_length", 50) or 50))
class MemoryAutomationService:
def __init__(self) -> None:
self.fact_writeback = PersonFactWritebackService()
self.chat_summary_writeback = ChatSummaryWritebackService()
self._started = False
async def start(self) -> None:
if self._started:
return
await self.fact_writeback.start()
await self.chat_summary_writeback.start()
self._started = True
async def shutdown(self) -> None:
if not self._started:
return
await self.chat_summary_writeback.shutdown()
await self.fact_writeback.shutdown()
self._started = False
async def on_incoming_message(self, message: Any) -> None:
del message
if not self._started:
await self.start()
async def on_message_sent(self, message: Any) -> None:
if not self._started:
await self.start()
await self.fact_writeback.enqueue(message)
await self.chat_summary_writeback.enqueue(message)
memory_automation_service = MemoryAutomationService()