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[changes] The user's personal configuration and the clustering trigger boundary are clearly defined

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lanceyq
2026-03-13 18:02:23 +08:00
parent 5141a91041
commit 382e4c5377
2 changed files with 52 additions and 41 deletions
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57
api/app/tasks.py
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@@ -2707,32 +2707,26 @@ def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[s
try:
repo = CommunityRepository(connector)
# 获取 llm_model_id（从第一个用户的配置中读取，作为全局兜底）
llm_model_id = None
# 批量预取所有用户的配置（内置兜底：用户配置不可用时自动回退到工作空间默认配置）
user_llm_map: Dict[str, Optional[str]] = {}
try:
with get_db_context() as db:
from app.services.memory_agent_service import get_end_user_connected_config
from app.services.memory_agent_service import get_end_users_connected_configs_batch
from app.services.memory_config_service import MemoryConfigService
for uid in end_user_ids:
try:
connected = get_end_user_connected_config(uid, db)
config_id = connected.get("memory_config_id")
workspace_id = connected.get("workspace_id")
if config_id or workspace_id:
cfg = MemoryConfigService(db).load_memory_config(
config_id=config_id, workspace_id=workspace_id
)
llm_model_id = str(cfg.llm_model_id)
break
except Exception:
continue
batch_configs = get_end_users_connected_configs_batch(end_user_ids, db)
for uid, cfg_info in batch_configs.items():
config_id = cfg_info.get("memory_config_id")
if config_id:
try:
cfg = MemoryConfigService(db).load_memory_config(config_id=config_id)
user_llm_map[uid] = str(cfg.llm_model_id) if cfg.llm_model_id else None
except Exception as e:
logger.warning(f"[CommunityCluster] 用户 {uid} 加载 LLM 配置失败，将使用 None: {e}")
user_llm_map[uid] = None
else:
user_llm_map[uid] = None
except Exception as e:
logger.warning(f"[CommunityCluster] 获取 LLM 配置失败，将使用兜底值: {e}")
engine = LabelPropagationEngine(
connector=connector,
llm_model_id=llm_model_id,
)
logger.warning(f"[CommunityCluster] 批量获取 LLM 配置失败，所有用户将使用 None: {e}")
for end_user_id in end_user_ids:
try:
@@ -2750,7 +2744,14 @@ def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[s
logger.debug(f"[CommunityCluster] 用户 {end_user_id} 无实体节点，跳过")
continue
logger.info(f"[CommunityCluster] 用户 {end_user_id} 有 {len(entities)} 个实体，开始全量聚类")
# 每个用户使用自己的 llm_model_id
llm_model_id = user_llm_map.get(end_user_id)
engine = LabelPropagationEngine(
connector=connector,
llm_model_id=llm_model_id,
)
logger.info(f"[CommunityCluster] 用户 {end_user_id} 有 {len(entities)} 个实体，开始全量聚类，llm_model_id={llm_model_id}")
await engine.full_clustering(end_user_id)
initialized += 1
logger.info(f"[CommunityCluster] 用户 {end_user_id} 聚类完成")
@@ -2779,15 +2780,7 @@ def init_community_clustering_for_users(self, end_user_ids: List[str]) -> Dict[s
except ImportError:
pass
try:
loop = asyncio.get_event_loop()
if loop.is_closed():
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
loop = set_asyncio_event_loop()
result = loop.run_until_complete(_run())
result["elapsed_time"] = time.time() - start_time
result["task_id"] = self.request.id