From b9201c918a56a32dad3ea1327e00d7a624425393 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 27 Feb 2026 11:06:00 +0800 Subject: [PATCH 01/31] [fix]Complete the API call logic for the homepage --- .../controllers/memory_agent_controller.py | 5 +- .../memory_dashboard_controller.py | 50 +++++++++++++---- api/app/services/memory_agent_service.py | 53 ++----------------- redbear-mem-benchmark | 2 +- 4 files changed, 47 insertions(+), 63 deletions(-) diff --git a/api/app/controllers/memory_agent_controller.py b/api/app/controllers/memory_agent_controller.py index 0e632fcc..b88e65ff 100644 --- a/api/app/controllers/memory_agent_controller.py +++ b/api/app/controllers/memory_agent_controller.py @@ -633,12 +633,11 @@ async def get_knowledge_type_stats_api( current_user: User = Depends(get_current_user) ): """ - 统计当前空间下各知识库类型的数量，包含 General | Web | Third-party | Folder | memory。 + 统计当前空间下各知识库类型的数量，包含 General | Web | Third-party | Folder。 会对缺失类型补 0，返回字典形式。 可选按状态过滤。 - 知识库类型根据当前用户的 current_workspace_id 过滤 - - memory 是 Neo4j 中 Chunk 的数量，根据 end_user_id (end_user_id) 过滤 - - 如果用户没有当前工作空间或未提供 end_user_id，对应的统计返回 0 + - 如果用户没有当前工作空间，对应的统计返回 0 """ api_logger.info(f"Knowledge type stats requested for workspace_id: {current_user.current_workspace_id}, end_user_id: {end_user_id}") try: diff --git a/api/app/controllers/memory_dashboard_controller.py b/api/app/controllers/memory_dashboard_controller.py index 88684a39..475d184e 100644 --- a/api/app/controllers/memory_dashboard_controller.py +++ b/api/app/controllers/memory_dashboard_controller.py @@ -9,6 +9,7 @@ from app.schemas.response_schema import ApiResponse from app.services import memory_dashboard_service, memory_storage_service, workspace_service from app.services.memory_agent_service import get_end_users_connected_configs_batch +from app.services.app_statistics_service import AppStatisticsService from app.core.logging_config import get_api_logger # 获取API专用日志器 @@ -469,6 +470,8 @@ async def get_chunk_insight( @router.get("/dashboard_data", response_model=ApiResponse) async def dashboard_data( end_user_id: Optional[str] = Query(None, description="可选的用户ID"), + start_date: Optional[int] = Query(None, description="开始时间戳（毫秒）"), + end_date: Optional[int] = Query(None, description="结束时间戳（毫秒）"), db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): @@ -503,6 +506,15 @@ async def dashboard_data( workspace_id = current_user.current_workspace_id api_logger.info(f"用户 {current_user.username} 请求获取工作空间 {workspace_id} 的dashboard整合数据") + # 如果没有提供时间范围，默认使用最近30天 + if start_date is None or end_date is None: + from datetime import datetime, timedelta + end_dt = datetime.now() + start_dt = end_dt - timedelta(days=30) + end_date = int(end_dt.timestamp() * 1000) + start_date = int(start_dt.timestamp() * 1000) + api_logger.info(f"使用默认时间范围: {start_dt} 到 {end_dt}") + # 获取 storage_type，如果为 None 则使用默认值 storage_type = workspace_service.get_workspace_storage_type( db=db, @@ -563,17 +575,22 @@ async def dashboard_data( except Exception as e: api_logger.warning(f"获取知识库类型统计失败: {str(e)}") - # 3. 获取API调用增量（total_api_call，转换为整数） + # 3. 获取API调用统计（total_api_call） try: - api_increment = memory_dashboard_service.get_workspace_api_increment( - db=db, + # 使用 AppStatisticsService 获取真实的API调用统计 + app_stats_service = AppStatisticsService(db) + api_stats = app_stats_service.get_workspace_api_statistics( workspace_id=workspace_id, - current_user=current_user + start_date=start_date, + end_date=end_date ) - neo4j_data["total_api_call"] = api_increment - api_logger.info(f"成功获取API调用增量: {neo4j_data['total_api_call']}") + # 计算总调用次数 + total_api_calls = sum(item.get("total_calls", 0) for item in api_stats) + neo4j_data["total_api_call"] = total_api_calls + api_logger.info(f"成功获取API调用统计: {neo4j_data['total_api_call']}") except Exception as e: - api_logger.warning(f"获取API调用增量失败: {str(e)}") + api_logger.error(f"获取API调用统计失败: {str(e)}") + neo4j_data["total_api_call"] = 0 result["neo4j_data"] = neo4j_data api_logger.info("成功获取neo4j_data") @@ -602,10 +619,23 @@ async def dashboard_data( total_kb = memory_dashboard_service.get_rag_total_kb(db, current_user) rag_data["total_knowledge"] = total_kb - # total_api_call: 固定值 - rag_data["total_api_call"] = 1024 + # total_api_call: 使用 AppStatisticsService 获取真实的API调用统计 + try: + app_stats_service = AppStatisticsService(db) + api_stats = app_stats_service.get_workspace_api_statistics( + workspace_id=workspace_id, + start_date=start_date, + end_date=end_date + ) + # 计算总调用次数 + total_api_calls = sum(item.get("total_calls", 0) for item in api_stats) + rag_data["total_api_call"] = total_api_calls + api_logger.info(f"成功获取RAG模式API调用统计: {rag_data['total_api_call']}") + except Exception as e: + api_logger.warning(f"获取RAG模式API调用统计失败，使用默认值: {str(e)}") + rag_data["total_api_call"] = 0 - api_logger.info(f"成功获取RAG相关数据: memory={total_chunk}, app={len(apps_orm)}, knowledge={total_kb}") + api_logger.info(f"成功获取RAG相关数据: memory={total_chunk}, app={len(apps_orm)}, knowledge={total_kb}, api_calls={rag_data['total_api_call']}") except Exception as e: api_logger.warning(f"获取RAG相关数据失败: {str(e)}") diff --git a/api/app/services/memory_agent_service.py b/api/app/services/memory_agent_service.py index da8a8e06..1f3667a6 100644 --- a/api/app/services/memory_agent_service.py +++ b/api/app/services/memory_agent_service.py @@ -816,11 +816,10 @@ class MemoryAgentService: """ 统计知识库类型分布，包含： 1. PostgreSQL 中的知识库类型：General, Web, Third-party, Folder（根据 workspace_id 过滤） - 2. Neo4j 中的 memory 类型（仅统计 Chunk 数量，根据 end_user_id/end_user_id 过滤） - 3. total: 所有类型的总和 + 2. total: 所有类型的总和 参数： - - end_user_id: 用户组ID（可选，未提供时 memory 统计为 0） + - end_user_id: 用户组ID（可选，保留参数以保持接口兼容性） - only_active: 是否仅统计有效记录 - current_workspace_id: 当前工作空间ID（可选，未提供时知识库统计为 0） - db: 数据库会话 @@ -831,7 +830,6 @@ class MemoryAgentService: "Web": count, "Third-party": count, "Folder": count, - "memory": chunk_count, "total": sum_of_all } """ @@ -878,51 +876,8 @@ class MemoryAgentService: logger.error(f"知识库类型统计失败: {e}") raise Exception(f"知识库类型统计失败: {e}") - # 2. 统计 Neo4j 中的 memory 总量（统计当前空间下所有宿主的 Chunk 总数） - try: - if current_workspace_id: - # 获取当前空间下的所有宿主 - from app.repositories import app_repository, end_user_repository - from app.schemas.app_schema import App as AppSchema - from app.schemas.end_user_schema import EndUser as EndUserSchema - - # 查询应用并转换为 Pydantic 模型 - apps_orm = app_repository.get_apps_by_workspace_id(db, current_workspace_id) - apps = [AppSchema.model_validate(h) for h in apps_orm] - app_ids = [app.id for app in apps] - - # 获取所有宿主 - end_users = [] - for app_id in app_ids: - end_user_orm_list = end_user_repository.get_end_users_by_app_id(db, app_id) - end_users.extend(h for h in end_user_orm_list) - - # 统计所有宿主的 Chunk 总数 - total_chunks = 0 - for end_user in end_users: - end_user_id_str = str(end_user.id) - memory_query = """ - MATCH (n:Chunk) WHERE n.end_user_id = $end_user_id RETURN count(n) AS Count - """ - neo4j_result = await _neo4j_connector.execute_query( - memory_query, - end_user_id=end_user_id_str, - ) - chunk_count = neo4j_result[0]["Count"] if neo4j_result else 0 - total_chunks += chunk_count - logger.debug(f"EndUser {end_user_id_str} Chunk数量: {chunk_count}") - - result["memory"] = total_chunks - logger.info(f"Neo4j memory统计成功: 总Chunk数={total_chunks}, 宿主数={len(end_users)}") - else: - # 没有 workspace_id 时，返回 0 - result["memory"] = 0 - logger.info("未提供 workspace_id，memory 统计为 0") - - except Exception as e: - logger.error(f"Neo4j memory统计失败: {e}", exc_info=True) - # 如果 Neo4j 查询失败，memory 设为 0 - result["memory"] = 0 + # 2. 统计 Neo4j 中的 memory 总量已移除 + # memory 字段不再返回 # 3. 计算知识库类型总和（不包括 memory） result["total"] = ( diff --git a/redbear-mem-benchmark b/redbear-mem-benchmark index 4b0257bb..8494e824 160000 --- a/redbear-mem-benchmark +++ b/redbear-mem-benchmark @@ -1 +1 @@ -Subproject commit 4b0257bb4e7dc384b2aaf849b0bd6eae4b39835d +Subproject commit 8494e82498cb99c70ac67a64a544ff872432363a From a7ffc19ba1c86abf56630967f0d0893b137e52de Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Fri, 27 Feb 2026 12:20:51 +0800 Subject: [PATCH 02/31] [fix]Reconstructing memory incremental statistical scheduling task --- api/app/celery_app.py | 17 ++-- api/app/core/config.py | 1 - api/app/tasks.py | 197 +++++++++++++++++++++++++++++++++++++++++ 3 files changed, 203 insertions(+), 12 deletions(-) diff --git a/api/app/celery_app.py b/api/app/celery_app.py index 8ef44975..f422f4a0 100644 --- a/api/app/celery_app.py +++ b/api/app/celery_app.py @@ -82,7 +82,7 @@ celery_app.conf.update( 'app.tasks.workspace_reflection_task': {'queue': 'periodic_tasks'}, 'app.tasks.regenerate_memory_cache': {'queue': 'periodic_tasks'}, 'app.tasks.run_forgetting_cycle_task': {'queue': 'periodic_tasks'}, - 'app.controllers.memory_storage_controller.search_all': {'queue': 'periodic_tasks'}, + 'app.tasks.write_all_workspaces_memory_task': {'queue': 'periodic_tasks'}, }, ) @@ -115,16 +115,11 @@ beat_schedule_config = { "config_id": None, # 使用默认配置，可以通过环境变量配置 }, }, + "write-all-workspaces-memory": { + "task": "app.tasks.write_all_workspaces_memory_task", + "schedule": memory_increment_schedule, + "args": (), + }, } -#如果配置了默认工作空间ID，则添加记忆总量统计任务 -if settings.DEFAULT_WORKSPACE_ID: - beat_schedule_config["write-total-memory"] = { - "task": "app.controllers.memory_storage_controller.search_all", - "schedule": memory_increment_schedule, - "kwargs": { - "workspace_id": settings.DEFAULT_WORKSPACE_ID, - }, - } - celery_app.conf.beat_schedule = beat_schedule_config diff --git a/api/app/core/config.py b/api/app/core/config.py index 3a0c97b4..2e6b4136 100644 --- a/api/app/core/config.py +++ b/api/app/core/config.py @@ -202,7 +202,6 @@ class Settings: REFLECTION_INTERVAL_SECONDS: float = float(os.getenv("REFLECTION_INTERVAL_SECONDS", "300")) HEALTH_CHECK_SECONDS: float = float(os.getenv("HEALTH_CHECK_SECONDS", "600")) MEMORY_INCREMENT_INTERVAL_HOURS: float = float(os.getenv("MEMORY_INCREMENT_INTERVAL_HOURS", "24")) - DEFAULT_WORKSPACE_ID: Optional[str] = os.getenv("DEFAULT_WORKSPACE_ID", None) REFLECTION_INTERVAL_TIME: Optional[str] = int(os.getenv("REFLECTION_INTERVAL_TIME", 30)) # Memory Cache Regeneration Configuration diff --git a/api/app/tasks.py b/api/app/tasks.py index d408a0da..8e3aea85 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -1304,6 +1304,203 @@ def write_total_memory_task(workspace_id: str) -> Dict[str, Any]: "workspace_id": workspace_id, "elapsed_time": elapsed_time, } +@celery_app.task( + name="app.tasks.write_all_workspaces_memory_task", + bind=True, + ignore_result=False, + max_retries=3, + acks_late=True, + time_limit=3600, + soft_time_limit=3300, +) +def write_all_workspaces_memory_task(self) -> Dict[str, Any]: + """定时任务：遍历所有工作空间，统计并写入记忆增量 + + 此任务会： + 1. 查询所有活跃的工作空间 + 2. 对每个工作空间统计记忆总量 + 3. 将统计结果写入 memory_increments 表 + + Returns: + 包含任务执行结果的字典 + """ + start_time = time.time() + + async def _run() -> Dict[str, Any]: + from app.core.logging_config import get_api_logger + from app.models.workspace_model import Workspace + from app.models.app_model import App + from app.models.end_user_model import EndUser + from app.repositories.memory_increment_repository import write_memory_increment + from app.services.memory_storage_service import search_all + + api_logger = get_api_logger() + + with get_db_context() as db: + try: + # 获取所有活跃的工作空间 + workspaces = db.query(Workspace).filter( + Workspace.is_active.is_(True) + ).all() + + if not workspaces: + api_logger.warning("没有找到活跃的工作空间") + return { + "status": "SUCCESS", + "message": "没有找到活跃的工作空间", + "workspace_count": 0, + "workspace_results": [] + } + + api_logger.info(f"开始统计 {len(workspaces)} 个工作空间的记忆增量") + all_workspace_results = [] + + # 遍历每个工作空间 + for workspace in workspaces: + workspace_id = workspace.id + api_logger.info(f"开始处理工作空间: {workspace.name} (ID: {workspace_id})") + + try: + # 1. 查询当前workspace下的所有app（仅未删除的） + apps = db.query(App).filter( + App.workspace_id == workspace_id, + App.is_active.is_(True) + ).all() + + if not apps: + # 如果没有app，总量为0 + memory_increment = write_memory_increment( + db=db, + workspace_id=workspace_id, + total_num=0 + ) + all_workspace_results.append({ + "workspace_id": str(workspace_id), + "workspace_name": workspace.name, + "status": "SUCCESS", + "total_num": 0, + "end_user_count": 0, + "memory_increment_id": str(memory_increment.id), + "created_at": memory_increment.created_at.isoformat(), + }) + api_logger.info(f"工作空间 {workspace.name} 没有应用，记录总量为0") + continue + + # 2. 查询所有app下的end_user_id（去重） + app_ids = [app.id for app in apps] + end_users = db.query(EndUser.id).filter( + EndUser.app_id.in_(app_ids) + ).distinct().all() + + # 3. 遍历所有end_user，查询每个宿主的记忆总量并累加 + total_num = 0 + end_user_details = [] + + for (end_user_id,) in end_users: + try: + # 调用 search_all 接口查询该宿主的总量 + result = await search_all(str(end_user_id)) + user_total = result.get("total", 0) + total_num += user_total + end_user_details.append({ + "end_user_id": str(end_user_id), + "total": user_total + }) + except Exception as e: + # 记录单个用户查询失败，但继续处理其他用户 + api_logger.warning(f"查询用户 {end_user_id} 记忆失败: {str(e)}") + end_user_details.append({ + "end_user_id": str(end_user_id), + "total": 0, + "error": str(e) + }) + + # 4. 写入数据库 + memory_increment = write_memory_increment( + db=db, + workspace_id=workspace_id, + total_num=total_num + ) + + all_workspace_results.append({ + "workspace_id": str(workspace_id), + "workspace_name": workspace.name, + "status": "SUCCESS", + "total_num": total_num, + "end_user_count": len(end_users), + "memory_increment_id": str(memory_increment.id), + "created_at": memory_increment.created_at.isoformat(), + }) + + api_logger.info( + f"工作空间 {workspace.name} 统计完成: 总量={total_num}, 用户数={len(end_users)}" + ) + + except Exception as e: + db.rollback() # 回滚失败的事务，允许继续处理下一个工作空间 + api_logger.error(f"处理工作空间 {workspace.name} (ID: {workspace_id}) 失败: {str(e)}") + all_workspace_results.append({ + "workspace_id": str(workspace_id), + "workspace_name": workspace.name, + "status": "FAILURE", + "error": str(e), + "total_num": 0, + "end_user_count": 0, + }) + + total_memory = sum(r.get("total_num", 0) for r in all_workspace_results) + success_count = sum(1 for r in all_workspace_results if r.get("status") == "SUCCESS") + + return { + "status": "SUCCESS", + "message": f"成功处理 {success_count}/{len(workspaces)} 个工作空间，总记忆量: {total_memory}", + "workspace_count": len(workspaces), + "success_count": success_count, + "total_memory": total_memory, + "workspace_results": all_workspace_results + } + + except Exception as e: + api_logger.error(f"记忆增量统计任务执行失败: {str(e)}") + return { + "status": "FAILURE", + "error": str(e), + "workspace_count": 0, + "workspace_results": [] + } + + try: + # 使用 nest_asyncio 来避免事件循环冲突 + try: + import nest_asyncio + nest_asyncio.apply() + except ImportError: + pass + + # 尝试获取现有事件循环，如果不存在则创建新的 + 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) + + result = loop.run_until_complete(_run()) + elapsed_time = time.time() - start_time + result["elapsed_time"] = elapsed_time + result["task_id"] = self.request.id + + return result + except Exception as e: + elapsed_time = time.time() - start_time + return { + "status": "FAILURE", + "error": str(e), + "elapsed_time": elapsed_time, + "task_id": self.request.id + } @celery_app.task( From 5c42a84c3e343b70b74fda5a244498e37f7285db Mon Sep 17 00:00:00 2001 From: zhaoying Date: Tue, 3 Mar 2026 15:09:16 +0800 Subject: [PATCH 03/31] fix(web): Implicit detail add check data api --- web/src/api/memory.ts | 9 +++++++-- web/src/i18n/en.ts | 3 ++- web/src/i18n/zh.ts | 3 ++- .../UserMemoryDetail/pages/ImplicitDetail.tsx | 16 ++++++++++++++-- 4 files changed, 25 insertions(+), 6 deletions(-) diff --git a/web/src/api/memory.ts b/web/src/api/memory.ts index 987ef358..cb917ec1 100644 --- a/web/src/api/memory.ts +++ b/web/src/api/memory.ts @@ -1,8 +1,8 @@ /* * @Author: ZhaoYing * @Date: 2026-02-03 14:00:06 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-03 14:00:06 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-03-03 14:58:32 */ import { request } from '@/utils/request' import type { @@ -163,9 +163,14 @@ export const getImplicitInterestAreas = (end_user_id: string) => { export const getImplicitHabits = (end_user_id: string) => { return request.get(`/memory/implicit-memory/habits/${end_user_id}`) } +// Implicit Memory - Generate user portrait export const generateProfile = (end_user_id: string) => { return request.post(`/memory/implicit-memory/generate_profile`, { end_user_id }) } +// Implicit Memory - Check if data exists +export const implicitCheckData = (end_user_id: string) => { + return request.get(`/memory/implicit-memory/check-data/${end_user_id}`) +} // Short-term memory export const getShortTerm = (end_user_id: string) => { return request.get(`/memory/short/short_term`, { end_user_id }) diff --git a/web/src/i18n/en.ts b/web/src/i18n/en.ts index f2b4eaa4..b17ad291 100644 --- a/web/src/i18n/en.ts +++ b/web/src/i18n/en.ts @@ -2522,7 +2522,8 @@ Memory Bear: After the rebellion, regional warlordism intensified for several re context_details: 'Preference Details', supporting_evidence: 'Preference Source', specific_examples: 'Source', - wordEmpty: 'Click on a node in the left chart to view preference details' + wordEmpty: 'Click on a node in the left chart to view preference details', + noData: 'Portrait data does not exist, please click the refresh button in the top right corner to initialize', }, shortTermDetail: { title: 'Short-term memory is the "workbench" of the AI system, connecting instant conversations with long-term knowledge bases. Through real-time capture, deep retrieval, intelligent extraction and filtering transformation, temporary unstructured information is converted into valuable long-term knowledge.', diff --git a/web/src/i18n/zh.ts b/web/src/i18n/zh.ts index e2e7082a..181173ff 100644 --- a/web/src/i18n/zh.ts +++ b/web/src/i18n/zh.ts @@ -2518,7 +2518,8 @@ export const zh = { context_details: '偏好详情', supporting_evidence: '偏好来源', specific_examples: '来源', - wordEmpty: '点击左侧图表中的节点查看偏好详情' + wordEmpty: '点击左侧图表中的节点查看偏好详情', + noData: '画像数据不存在，请点击右上角刷新进行初始化', }, shortTermDetail: { title: '短期记忆是AI系统的"工作台"，连接即时对话与长期知识库。通过实时捕获、深度检索、智能提取和筛选转化，将临时的非结构化信息转化为有价值的长期知识。', diff --git a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx index dfe5c1ee..351e5ed1 100644 --- a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx @@ -1,6 +1,6 @@ -import { forwardRef, useImperativeHandle, useRef } from 'react' +import { forwardRef, useImperativeHandle, useRef, useEffect } from 'react' import { useTranslation } from 'react-i18next' -import { Row, Col } from 'antd' +import { Row, Col, App } from 'antd' import { useParams } from 'react-router-dom' import Preferences from '../components/Preferences' @@ -9,15 +9,27 @@ import InterestAreas from '../components/InterestAreas' import Habits from '../components/Habits' import { generateProfile, + implicitCheckData, } from '@/api/memory' const ImplicitDetail = forwardRef<{ handleRefresh: () => void; }>((_props, ref) => { const { t } = useTranslation() const { id } = useParams() + const { message } = App.useApp() const preferencesRef = useRef<{ handleRefresh: () => void; }>(null) const portraitRef = useRef<{ handleRefresh: () => void; }>(null) const interestAreasRef = useRef<{ handleRefresh: () => void; }>(null) const habitsRef = useRef<{ handleRefresh: () => void; }>(null) + + useEffect(() => { + if (!id) return + implicitCheckData(id) + .then(res => { + if (!(res as { exists: boolean }).exists) { + message.warning(t('implicitDetail.noData')) + } + }) + }, [id]) const handleRefresh = () => { if (!id) { From 9675982555fa76b76a6d6946c3196bb72bc3b6d5 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 15:33:17 +0800 Subject: [PATCH 04/31] [changes] Implicit and emotional memories are stored in a database. --- api/app/cache/memory/emotion_memory.py | 134 ----------- api/app/cache/memory/implicit_memory.py | 136 ----------- api/app/celery_app.py | 16 +- api/app/controllers/emotion_controller.py | 114 ++++++---- .../controllers/implicit_memory_controller.py | 59 ++++- api/app/models/__init__.py | 4 +- .../models/implicit_emotions_storage_model.py | 46 ++++ .../implicit_emotions_storage_repository.py | 169 ++++++++++++++ api/app/services/emotion_analytics_service.py | 58 +++-- api/app/services/implicit_memory_service.py | 58 +++-- api/app/tasks.py | 211 +++++++++++++++++- 11 files changed, 607 insertions(+), 398 deletions(-) delete mode 100644 api/app/cache/memory/emotion_memory.py delete mode 100644 api/app/cache/memory/implicit_memory.py create mode 100644 api/app/models/implicit_emotions_storage_model.py create mode 100644 api/app/repositories/implicit_emotions_storage_repository.py diff --git a/api/app/cache/memory/emotion_memory.py b/api/app/cache/memory/emotion_memory.py deleted file mode 100644 index 45ea90de..00000000 --- a/api/app/cache/memory/emotion_memory.py +++ /dev/null @@ -1,134 +0,0 @@ -""" -Emotion Suggestions Cache - -情绪个性化建议缓存模块 -用于缓存用户的情绪个性化建议数据 -""" -import json -import logging -from typing import Optional, Dict, Any -from datetime import datetime - -from app.aioRedis import aio_redis - -logger = logging.getLogger(__name__) - - -class EmotionMemoryCache: - """情绪建议缓存类""" - - # Key 前缀 - PREFIX = "cache:memory:emotion_memory" - - @classmethod - def _get_key(cls, *parts: str) -> str: - """生成 Redis key - - Args: - *parts: key 的各个部分 - - Returns: - 完整的 Redis key - """ - return ":".join([cls.PREFIX] + list(parts)) - - @classmethod - async def set_emotion_suggestions( - cls, - user_id: str, - suggestions_data: Dict[str, Any], - expire: int = 86400 - ) -> bool: - """设置用户情绪建议缓存 - - Args: - user_id: 用户ID（end_user_id） - suggestions_data: 建议数据字典，包含： - - health_summary: 健康状态摘要 - - suggestions: 建议列表 - - generated_at: 生成时间（可选） - expire: 过期时间（秒），默认24小时（86400秒） - - Returns: - 是否设置成功 - """ - try: - key = cls._get_key("suggestions", user_id) - - # 添加生成时间戳 - if "generated_at" not in suggestions_data: - suggestions_data["generated_at"] = datetime.now().isoformat() - - # 添加缓存标记 - suggestions_data["cached"] = True - - value = json.dumps(suggestions_data, ensure_ascii=False) - await aio_redis.set(key, value, ex=expire) - logger.info(f"设置情绪建议缓存成功: {key}, 过期时间: {expire}秒") - return True - except Exception as e: - logger.error(f"设置情绪建议缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_emotion_suggestions(cls, user_id: str) -> Optional[Dict[str, Any]]: - """获取用户情绪建议缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 建议数据字典，如果不存在或已过期返回 None - """ - try: - key = cls._get_key("suggestions", user_id) - value = await aio_redis.get(key) - - if value: - data = json.loads(value) - logger.info(f"成功获取情绪建议缓存: {key}") - return data - - logger.info(f"情绪建议缓存不存在或已过期: {key}") - return None - except Exception as e: - logger.error(f"获取情绪建议缓存失败: {e}", exc_info=True) - return None - - @classmethod - async def delete_emotion_suggestions(cls, user_id: str) -> bool: - """删除用户情绪建议缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 是否删除成功 - """ - try: - key = cls._get_key("suggestions", user_id) - result = await aio_redis.delete(key) - logger.info(f"删除情绪建议缓存: {key}, 结果: {result}") - return result > 0 - except Exception as e: - logger.error(f"删除情绪建议缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_suggestions_ttl(cls, user_id: str) -> int: - """获取情绪建议缓存的剩余过期时间 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 剩余秒数，-1表示永不过期，-2表示key不存在 - """ - try: - key = cls._get_key("suggestions", user_id) - ttl = await aio_redis.ttl(key) - logger.debug(f"情绪建议缓存TTL: {key} = {ttl}秒") - return ttl - except Exception as e: - logger.error(f"获取情绪建议缓存TTL失败: {e}") - return -2 diff --git a/api/app/cache/memory/implicit_memory.py b/api/app/cache/memory/implicit_memory.py deleted file mode 100644 index 21f08e9a..00000000 --- a/api/app/cache/memory/implicit_memory.py +++ /dev/null @@ -1,136 +0,0 @@ -""" -Implicit Memory Profile Cache - -隐式记忆用户画像缓存模块 -用于缓存用户的完整画像数据（偏好标签、四维画像、兴趣领域、行为习惯） -""" -import json -import logging -from typing import Optional, Dict, Any -from datetime import datetime - -from app.aioRedis import aio_redis - -logger = logging.getLogger(__name__) - - -class ImplicitMemoryCache: - """隐式记忆用户画像缓存类""" - - # Key 前缀 - PREFIX = "cache:memory:implicit_memory" - - @classmethod - def _get_key(cls, *parts: str) -> str: - """生成 Redis key - - Args: - *parts: key 的各个部分 - - Returns: - 完整的 Redis key - """ - return ":".join([cls.PREFIX] + list(parts)) - - @classmethod - async def set_user_profile( - cls, - user_id: str, - profile_data: Dict[str, Any], - expire: int = 86400 - ) -> bool: - """设置用户完整画像缓存 - - Args: - user_id: 用户ID（end_user_id） - profile_data: 画像数据字典，包含： - - preferences: 偏好标签列表 - - portrait: 四维画像对象 - - interest_areas: 兴趣领域分布对象 - - habits: 行为习惯列表 - - generated_at: 生成时间（可选） - expire: 过期时间（秒），默认24小时（86400秒） - - Returns: - 是否设置成功 - """ - try: - key = cls._get_key("profile", user_id) - - # 添加生成时间戳 - if "generated_at" not in profile_data: - profile_data["generated_at"] = datetime.now().isoformat() - - # 添加缓存标记 - profile_data["cached"] = True - - value = json.dumps(profile_data, ensure_ascii=False) - await aio_redis.set(key, value, ex=expire) - logger.info(f"设置用户画像缓存成功: {key}, 过期时间: {expire}秒") - return True - except Exception as e: - logger.error(f"设置用户画像缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_user_profile(cls, user_id: str) -> Optional[Dict[str, Any]]: - """获取用户完整画像缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 画像数据字典，如果不存在或已过期返回 None - """ - try: - key = cls._get_key("profile", user_id) - value = await aio_redis.get(key) - - if value: - data = json.loads(value) - logger.info(f"成功获取用户画像缓存: {key}") - return data - - logger.info(f"用户画像缓存不存在或已过期: {key}") - return None - except Exception as e: - logger.error(f"获取用户画像缓存失败: {e}", exc_info=True) - return None - - @classmethod - async def delete_user_profile(cls, user_id: str) -> bool: - """删除用户完整画像缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 是否删除成功 - """ - try: - key = cls._get_key("profile", user_id) - result = await aio_redis.delete(key) - logger.info(f"删除用户画像缓存: {key}, 结果: {result}") - return result > 0 - except Exception as e: - logger.error(f"删除用户画像缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_profile_ttl(cls, user_id: str) -> int: - """获取用户画像缓存的剩余过期时间 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 剩余秒数，-1表示永不过期，-2表示key不存在 - """ - try: - key = cls._get_key("profile", user_id) - ttl = await aio_redis.ttl(key) - logger.debug(f"用户画像缓存TTL: {key} = {ttl}秒") - return ttl - except Exception as e: - logger.error(f"获取用户画像缓存TTL失败: {e}") - return -2 diff --git a/api/app/celery_app.py b/api/app/celery_app.py index 8ef44975..e804d303 100644 --- a/api/app/celery_app.py +++ b/api/app/celery_app.py @@ -82,7 +82,8 @@ celery_app.conf.update( 'app.tasks.workspace_reflection_task': {'queue': 'periodic_tasks'}, 'app.tasks.regenerate_memory_cache': {'queue': 'periodic_tasks'}, 'app.tasks.run_forgetting_cycle_task': {'queue': 'periodic_tasks'}, - 'app.controllers.memory_storage_controller.search_all': {'queue': 'periodic_tasks'}, + 'app.tasks.write_all_workspaces_memory_task': {'queue': 'periodic_tasks'}, + 'app.tasks.update_implicit_emotions_storage': {'queue': 'periodic_tasks'}, }, ) @@ -95,6 +96,7 @@ memory_cache_regeneration_schedule = timedelta(hours=settings.MEMORY_CACHE_REGEN # 这个30秒的设计不合理 workspace_reflection_schedule = timedelta(seconds=30) # 每30秒运行一次settings.REFLECTION_INTERVAL_TIME forgetting_cycle_schedule = timedelta(hours=24) # 每24小时运行一次遗忘周期 +implicit_emotions_update_schedule = timedelta(hours=24) # 每24小时更新一次隐性记忆和情绪数据 #构建定时任务配置 beat_schedule_config = { @@ -122,9 +124,13 @@ if settings.DEFAULT_WORKSPACE_ID: beat_schedule_config["write-total-memory"] = { "task": "app.controllers.memory_storage_controller.search_all", "schedule": memory_increment_schedule, - "kwargs": { - "workspace_id": settings.DEFAULT_WORKSPACE_ID, - }, - } + "args": (), + }, + "update-implicit-emotions-storage": { + "task": "app.tasks.update_implicit_emotions_storage", + "schedule": implicit_emotions_update_schedule, + "args": (), + }, +} celery_app.conf.beat_schedule = beat_schedule_config diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index eb2436d2..02ce7862 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -208,6 +208,57 @@ async def get_emotion_health( +@router.post("/check-data", response_model=ApiResponse) +async def check_emotion_data_exists( + request: EmotionSuggestionsRequest, + db: Session = Depends(get_db), + current_user: User = Depends(get_current_user), +): + """检查用户情绪建议数据是否存在 + + Args: + request: 包含 end_user_id + db: 数据库会话 + current_user: 当前用户 + + Returns: + 数据存在状态 + """ + try: + api_logger.info( + f"检查用户情绪建议数据是否存在: {request.end_user_id}", + extra={"end_user_id": request.end_user_id} + ) + + # 从数据库获取建议 + data = await emotion_service.get_cached_suggestions( + end_user_id=request.end_user_id, + db=db + ) + + if data is None: + api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据不存在") + return fail( + BizCode.NOT_FOUND, + "情绪建议数据不存在，请点击右上角刷新进行初始化", + {"exists": False} + ) + + api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据存在") + return success(data={"exists": True}, msg="情绪建议数据已存在") + + except Exception as e: + api_logger.error( + f"检查情绪建议数据失败: {str(e)}", + extra={"end_user_id": request.end_user_id}, + exc_info=True + ) + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=f"检查情绪建议数据失败: {str(e)}" + ) + + @router.post("/suggestions", response_model=ApiResponse) async def get_emotion_suggestions( request: EmotionSuggestionsRequest, @@ -215,7 +266,7 @@ async def get_emotion_suggestions( db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): - """获取个性化情绪建议（从缓存读取） + """获取个性化情绪建议（从数据库读取） Args: request: 包含 end_user_id 和可选的 config_id @@ -223,77 +274,47 @@ async def get_emotion_suggestions( current_user: 当前用户 Returns: - 缓存的个性化情绪建议响应 + 存储的个性化情绪建议响应 """ try: # 使用集中化的语言校验 language = get_language_from_header(language_type) api_logger.info( - f"用户 {current_user.username} 请求获取个性化情绪建议（缓存）", + f"用户 {current_user.username} 请求获取个性化情绪建议", extra={ "end_user_id": request.end_user_id, "config_id": request.config_id } ) - # 从缓存获取建议 + # 从数据库获取建议 data = await emotion_service.get_cached_suggestions( end_user_id=request.end_user_id, db=db ) if data is None: - # 缓存不存在或已过期，自动触发生成 + # 数据不存在，返回提示信息 api_logger.info( - f"用户 {request.end_user_id} 的建议缓存不存在或已过期，自动生成新建议", + f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - try: - data = await emotion_service.generate_emotion_suggestions( - end_user_id=request.end_user_id, - db=db, - language=language - ) - # 保存到缓存 - await emotion_service.save_suggestions_cache( - end_user_id=request.end_user_id, - suggestions_data=data, - db=db, - expires_hours=24 - ) - except (ValueError, KeyError) as gen_e: - # 预期内的业务异常：配置缺失、数据格式问题等 - api_logger.warning( - f"自动生成建议失败（业务异常）: {str(gen_e)}", - extra={"end_user_id": request.end_user_id} - ) - return fail( - BizCode.NOT_FOUND, - f"自动生成建议失败: {str(gen_e)}", - "" - ) - except Exception as gen_e: - # 非预期异常：记录完整 traceback 便于排查 - api_logger.error( - f"自动生成建议时发生未预期异常: {str(gen_e)}", - extra={"end_user_id": request.end_user_id}, - exc_info=True - ) - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail=f"生成建议时发生内部错误: {str(gen_e)}" - ) + return fail( + BizCode.NOT_FOUND, + "情绪建议数据不存在，请点击右上角刷新进行初始化", + "" + ) api_logger.info( - "个性化建议获取成功（缓存）", + "个性化建议获取成功", extra={ "end_user_id": request.end_user_id, "suggestions_count": len(data.get("suggestions", [])) } ) - return success(data=data, msg="个性化建议获取成功（缓存）") + return success(data=data, msg="个性化建议获取成功") except Exception as e: api_logger.error( @@ -314,7 +335,7 @@ async def generate_emotion_suggestions( db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): - """生成个性化情绪建议（调用LLM并缓存） + """生成个性化情绪建议（调用LLM并保存到数据库） Args: request: 包含 end_user_id @@ -342,12 +363,11 @@ async def generate_emotion_suggestions( language=language ) - # 保存到缓存 + # 保存到数据库 await emotion_service.save_suggestions_cache( end_user_id=request.end_user_id, suggestions_data=data, - db=db, - expires_hours=24 + db=db ) api_logger.info( diff --git a/api/app/controllers/implicit_memory_controller.py b/api/app/controllers/implicit_memory_controller.py index 96e437d6..91e634c9 100644 --- a/api/app/controllers/implicit_memory_controller.py +++ b/api/app/controllers/implicit_memory_controller.py @@ -122,6 +122,49 @@ def validate_confidence_threshold(threshold: float) -> None: raise ValueError("confidence_threshold must be between 0.0 and 1.0") +@router.get("/check-data/{end_user_id}", response_model=ApiResponse) +@cur_workspace_access_guard() +async def check_user_data_exists( + end_user_id: str, + db: Session = Depends(get_db), + current_user: User = Depends(get_current_user) +) -> ApiResponse: + """ + 检查用户画像数据是否存在 + + Args: + end_user_id: 目标用户ID + + Returns: + 数据存在状态 + """ + api_logger.info(f"检查用户画像数据是否存在: {end_user_id}") + + try: + # Validate inputs + validate_user_id(end_user_id) + + # Create service with user-specific config + service = ImplicitMemoryService(db=db, end_user_id=end_user_id) + + # Get cached profile + cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) + + if cached_profile is None: + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") + return fail( + BizCode.NOT_FOUND, + "画像数据不存在，请点击右上角刷新进行初始化", + {"exists": False} + ) + + api_logger.info(f"用户 {end_user_id} 的画像数据存在") + return success(data={"exists": True}, msg="画像数据已存在") + + except Exception as e: + return handle_implicit_memory_error(e, "检查画像数据", end_user_id) + + @router.get("/preferences/{end_user_id}", response_model=ApiResponse) @cur_workspace_access_guard() async def get_preference_tags( @@ -159,10 +202,10 @@ async def get_preference_tags( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) @@ -230,10 +273,10 @@ async def get_dimension_portrait( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) @@ -278,10 +321,10 @@ async def get_interest_area_distribution( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) @@ -330,10 +373,10 @@ async def get_behavior_habits( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) diff --git a/api/app/models/__init__.py b/api/app/models/__init__.py index b1b723e9..c6098a6d 100644 --- a/api/app/models/__init__.py +++ b/api/app/models/__init__.py @@ -35,6 +35,7 @@ from .ontology_scene import OntologyScene from .ontology_class import OntologyClass from .ontology_scene import OntologyScene from .ontology_class import OntologyClass +from .implicit_emotions_storage_model import ImplicitEmotionsStorage __all__ = [ "Tenants", @@ -90,5 +91,6 @@ __all__ = [ "MemoryPerceptualModel", "ModelBase", "LoadBalanceStrategy", - "Skill" + "Skill", + "ImplicitEmotionsStorage" ] diff --git a/api/app/models/implicit_emotions_storage_model.py b/api/app/models/implicit_emotions_storage_model.py new file mode 100644 index 00000000..57c0fd61 --- /dev/null +++ b/api/app/models/implicit_emotions_storage_model.py @@ -0,0 +1,46 @@ +""" +Implicit Emotions Storage Model + +数据库模型：存储用户的隐性记忆画像和情绪建议数据 +替代原有的Redis缓存方式 +""" +import uuid +from datetime import datetime +from sqlalchemy import Column, String, Text, DateTime, Index +from sqlalchemy.dialects.postgresql import UUID, JSONB +from app.db import Base + + +class ImplicitEmotionsStorage(Base): + """隐性记忆和情绪存储表""" + + __tablename__ = "implicit_emotions_storage" + + # 主键 + id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, comment="主键ID") + + # 用户标识 + end_user_id = Column(String(255), nullable=False, unique=True, index=True, comment="终端用户ID") + + # 隐性记忆画像数据（JSON格式） + implicit_profile = Column(JSONB, nullable=True, comment="隐性记忆用户画像数据") + + # 情绪建议数据（JSON格式） + emotion_suggestions = Column(JSONB, nullable=True, comment="情绪个性化建议数据") + + # 时间戳 + created_at = Column(DateTime, nullable=False, default=datetime.utcnow, comment="创建时间") + updated_at = Column(DateTime, nullable=False, default=datetime.utcnow, onupdate=datetime.utcnow, comment="更新时间") + + # 数据生成时间（用于业务逻辑） + implicit_generated_at = Column(DateTime, nullable=True, comment="隐性记忆画像生成时间") + emotion_generated_at = Column(DateTime, nullable=True, comment="情绪建议生成时间") + + # 索引 + __table_args__ = ( + Index('idx_end_user_id', 'end_user_id'), + Index('idx_updated_at', 'updated_at'), + ) + + def __repr__(self): + return f"" diff --git a/api/app/repositories/implicit_emotions_storage_repository.py b/api/app/repositories/implicit_emotions_storage_repository.py new file mode 100644 index 00000000..fd4b10ce --- /dev/null +++ b/api/app/repositories/implicit_emotions_storage_repository.py @@ -0,0 +1,169 @@ +""" +Implicit Emotions Storage Repository + +数据访问层：处理隐性记忆和情绪数据的数据库操作 +""" +import logging +from datetime import datetime +from typing import Optional, List +from sqlalchemy.orm import Session +from sqlalchemy import select + +from app.models.implicit_emotions_storage_model import ImplicitEmotionsStorage + +logger = logging.getLogger(__name__) + + +class ImplicitEmotionsStorageRepository: + """隐性记忆和情绪存储仓储类""" + + def __init__(self, db: Session): + self.db = db + + def get_by_end_user_id(self, end_user_id: str) -> Optional[ImplicitEmotionsStorage]: + """根据终端用户ID获取存储记录 + + Args: + end_user_id: 终端用户ID + + Returns: + 存储记录，如果不存在返回None + """ + try: + stmt = select(ImplicitEmotionsStorage).where( + ImplicitEmotionsStorage.end_user_id == end_user_id + ) + result = self.db.execute(stmt).scalar_one_or_none() + return result + except Exception as e: + logger.error(f"获取用户存储记录失败: end_user_id={end_user_id}, error={e}") + return None + + def create(self, end_user_id: str) -> ImplicitEmotionsStorage: + """创建新的存储记录 + + Args: + end_user_id: 终端用户ID + + Returns: + 新创建的存储记录 + """ + try: + storage = ImplicitEmotionsStorage( + end_user_id=end_user_id, + created_at=datetime.utcnow(), + updated_at=datetime.utcnow() + ) + self.db.add(storage) + self.db.commit() + self.db.refresh(storage) + logger.info(f"创建用户存储记录成功: end_user_id={end_user_id}") + return storage + except Exception as e: + self.db.rollback() + logger.error(f"创建用户存储记录失败: end_user_id={end_user_id}, error={e}") + raise + + def update_implicit_profile( + self, + end_user_id: str, + profile_data: dict + ) -> Optional[ImplicitEmotionsStorage]: + """更新隐性记忆画像数据 + + Args: + end_user_id: 终端用户ID + profile_data: 画像数据 + + Returns: + 更新后的存储记录 + """ + try: + storage = self.get_by_end_user_id(end_user_id) + + if storage is None: + # 如果记录不存在，创建新记录 + storage = self.create(end_user_id) + + storage.implicit_profile = profile_data + storage.implicit_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.commit() + self.db.refresh(storage) + logger.info(f"更新隐性记忆画像成功: end_user_id={end_user_id}") + return storage + except Exception as e: + self.db.rollback() + logger.error(f"更新隐性记忆画像失败: end_user_id={end_user_id}, error={e}") + raise + + def update_emotion_suggestions( + self, + end_user_id: str, + suggestions_data: dict + ) -> Optional[ImplicitEmotionsStorage]: + """更新情绪建议数据 + + Args: + end_user_id: 终端用户ID + suggestions_data: 建议数据 + + Returns: + 更新后的存储记录 + """ + try: + storage = self.get_by_end_user_id(end_user_id) + + if storage is None: + # 如果记录不存在，创建新记录 + storage = self.create(end_user_id) + + storage.emotion_suggestions = suggestions_data + storage.emotion_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.commit() + self.db.refresh(storage) + logger.info(f"更新情绪建议成功: end_user_id={end_user_id}") + return storage + except Exception as e: + self.db.rollback() + logger.error(f"更新情绪建议失败: end_user_id={end_user_id}, error={e}") + raise + + def get_all_user_ids(self) -> List[str]: + """获取所有已存储数据的用户ID列表 + + Returns: + 用户ID列表 + """ + try: + stmt = select(ImplicitEmotionsStorage.end_user_id) + result = self.db.execute(stmt).scalars().all() + return list(result) + except Exception as e: + logger.error(f"获取所有用户ID失败: error={e}") + return [] + + def delete_by_end_user_id(self, end_user_id: str) -> bool: + """删除用户的存储记录 + + Args: + end_user_id: 终端用户ID + + Returns: + 是否删除成功 + """ + try: + storage = self.get_by_end_user_id(end_user_id) + if storage: + self.db.delete(storage) + self.db.commit() + logger.info(f"删除用户存储记录成功: end_user_id={end_user_id}") + return True + return False + except Exception as e: + self.db.rollback() + logger.error(f"删除用户存储记录失败: end_user_id={end_user_id}, error={e}") + return False diff --git a/api/app/services/emotion_analytics_service.py b/api/app/services/emotion_analytics_service.py index 89e3cab9..099cbfb7 100644 --- a/api/app/services/emotion_analytics_service.py +++ b/api/app/services/emotion_analytics_service.py @@ -843,32 +843,33 @@ class EmotionAnalyticsService: end_user_id: str, db: Session, ) -> Optional[Dict[str, Any]]: - """从 Redis 缓存获取个性化情绪建议 + """从数据库获取个性化情绪建议 Args: end_user_id: 宿主ID（用户组ID） - db: 数据库会话（保留参数以保持接口兼容性） + db: 数据库会话 Returns: - Dict: 缓存的建议数据，如果不存在或已过期返回 None + Dict: 存储的建议数据，如果不存在返回 None """ try: - from app.cache.memory.emotion_memory import EmotionMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"尝试从 Redis 缓存获取情绪建议: user={end_user_id}") + logger.info(f"尝试从数据库获取情绪建议: user={end_user_id}") - # 从 Redis 获取缓存 - cached_data = await EmotionMemoryCache.get_emotion_suggestions(end_user_id) + # 从数据库获取存储记录 + repo = ImplicitEmotionsStorageRepository(db) + storage = repo.get_by_end_user_id(end_user_id) - if cached_data is None: - logger.info(f"用户 {end_user_id} 的建议缓存不存在或已过期") + if storage is None or storage.emotion_suggestions is None: + logger.info(f"用户 {end_user_id} 的建议数据不存在") return None - logger.info(f"成功从 Redis 缓存获取建议: user={end_user_id}") - return cached_data + logger.info(f"成功从数据库获取建议: user={end_user_id}") + return storage.emotion_suggestions except Exception as e: - logger.error(f"从 Redis 缓存获取建议失败: {str(e)}", exc_info=True) + logger.error(f"从数据库获取建议失败: {str(e)}", exc_info=True) return None async def save_suggestions_cache( @@ -876,36 +877,27 @@ class EmotionAnalyticsService: end_user_id: str, suggestions_data: Dict[str, Any], db: Session, - expires_hours: int = 24 + expires_hours: int = 24 # 参数保留以保持接口兼容性 ) -> None: - """保存建议到 Redis 缓存 + """保存建议到数据库 Args: end_user_id: 宿主ID（用户组ID） suggestions_data: 建议数据 - db: 数据库会话（保留参数以保持接口兼容性） - expires_hours: 过期时间（小时），默认24小时 + db: 数据库会话 + expires_hours: 保留参数（兼容性） """ try: - from app.cache.memory.emotion_memory import EmotionMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"保存建议到 Redis 缓存: user={end_user_id}, expires={expires_hours}小时") + logger.info(f"保存建议到数据库: user={end_user_id}") - # 计算过期时间（秒） - expire_seconds = expires_hours * 3600 + # 保存到数据库 + repo = ImplicitEmotionsStorageRepository(db) + repo.update_emotion_suggestions(end_user_id, suggestions_data) - # 保存到 Redis - success = await EmotionMemoryCache.set_emotion_suggestions( - user_id=end_user_id, - suggestions_data=suggestions_data, - expire=expire_seconds - ) - - if success: - logger.info(f"建议缓存保存成功: user={end_user_id}") - else: - logger.warning(f"建议缓存保存失败: user={end_user_id}") + logger.info(f"建议保存成功: user={end_user_id}") except Exception as e: - logger.error(f"保存建议缓存失败: {str(e)}", exc_info=True) - # 不抛出异常，缓存失败不应影响主流程 \ No newline at end of file + logger.error(f"保存建议失败: {str(e)}", exc_info=True) + # 不抛出异常，存储失败不应影响主流程 \ No newline at end of file diff --git a/api/app/services/implicit_memory_service.py b/api/app/services/implicit_memory_service.py index 34ebe880..534f138c 100644 --- a/api/app/services/implicit_memory_service.py +++ b/api/app/services/implicit_memory_service.py @@ -422,32 +422,33 @@ class ImplicitMemoryService: end_user_id: str, db: Session ) -> Optional[dict]: - """从 Redis 缓存获取完整用户画像 + """从数据库获取完整用户画像 Args: end_user_id: 终端用户ID - db: 数据库会话（保留参数以保持接口兼容性） + db: 数据库会话 Returns: - Dict: 缓存的画像数据，如果不存在或已过期返回 None + Dict: 存储的画像数据，如果不存在返回 None """ try: - from app.cache.memory.implicit_memory import ImplicitMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"尝试从 Redis 缓存获取用户画像: user={end_user_id}") + logger.info(f"尝试从数据库获取用户画像: user={end_user_id}") - # 从 Redis 获取缓存 - cached_data = await ImplicitMemoryCache.get_user_profile(end_user_id) + # 从数据库获取存储记录 + repo = ImplicitEmotionsStorageRepository(db) + storage = repo.get_by_end_user_id(end_user_id) - if cached_data is None: - logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + if storage is None or storage.implicit_profile is None: + logger.info(f"用户 {end_user_id} 的画像数据不存在") return None - logger.info(f"成功从 Redis 缓存获取用户画像: user={end_user_id}") - return cached_data + logger.info(f"成功从数据库获取用户画像: user={end_user_id}") + return storage.implicit_profile except Exception as e: - logger.error(f"从 Redis 缓存获取用户画像失败: {str(e)}", exc_info=True) + logger.error(f"从数据库获取用户画像失败: {str(e)}", exc_info=True) return None async def save_profile_cache( @@ -455,36 +456,27 @@ class ImplicitMemoryService: end_user_id: str, profile_data: dict, db: Session, - expires_hours: int = 168 # 默认7天 + expires_hours: int = 168 # 参数保留以保持接口兼容性 ) -> None: - """保存用户画像到 Redis 缓存 + """保存用户画像到数据库 Args: end_user_id: 终端用户ID profile_data: 画像数据 - db: 数据库会话（保留参数以保持接口兼容性） - expires_hours: 过期时间（小时），默认168小时（7天） + db: 数据库会话 + expires_hours: 保留参数（兼容性） """ try: - from app.cache.memory.implicit_memory import ImplicitMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"保存用户画像到 Redis 缓存: user={end_user_id}, expires={expires_hours}小时") + logger.info(f"保存用户画像到数据库: user={end_user_id}") - # 计算过期时间（秒） - expire_seconds = expires_hours * 3600 + # 保存到数据库 + repo = ImplicitEmotionsStorageRepository(db) + repo.update_implicit_profile(end_user_id, profile_data) - # 保存到 Redis - success = await ImplicitMemoryCache.set_user_profile( - user_id=end_user_id, - profile_data=profile_data, - expire=expire_seconds - ) - - if success: - logger.info(f"用户画像缓存保存成功: user={end_user_id}") - else: - logger.warning(f"用户画像缓存保存失败: user={end_user_id}") + logger.info(f"用户画像保存成功: user={end_user_id}") except Exception as e: - logger.error(f"保存用户画像缓存失败: {str(e)}", exc_info=True) - # 不抛出异常，缓存失败不应影响主流程 + logger.error(f"保存用户画像失败: {str(e)}", exc_info=True) + # 不抛出异常，存储失败不应影响主流程 diff --git a/api/app/tasks.py b/api/app/tasks.py index d408a0da..5a320c3f 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -1924,4 +1924,213 @@ def run_forgetting_cycle_task(self, config_id: Optional[uuid.UUID] = None) -> Di # "config_id": config_id, # "elapsed_time": elapsed_time, # "task_id": self.request.id -# } \ No newline at end of file +# } + + +# ============================================================================= +# 隐性记忆和情绪数据更新定时任务 +# ============================================================================= + +@celery_app.task( + name="app.tasks.update_implicit_emotions_storage", + bind=True, + ignore_result=True, + max_retries=0, + acks_late=False, + time_limit=7200, # 2小时硬超时 + soft_time_limit=6900, # 1小时55分钟软超时 +) +def update_implicit_emotions_storage(self) -> Dict[str, Any]: + """定时任务：更新所有用户的隐性记忆画像和情绪建议数据 + + 遍历数据库中所有已存在数据的用户，为每个用户重新生成隐性记忆画像和情绪建议。 + 实现错误隔离，单个用户失败不影响其他用户的处理。 + + Returns: + 包含任务执行结果的字典，包括： + - status: 任务状态 (SUCCESS/FAILURE) + - message: 执行消息 + - total_users: 总用户数 + - successful_implicit: 成功更新隐性记忆的用户数 + - successful_emotion: 成功更新情绪建议的用户数 + - failed: 失败的用户数 + - user_results: 每个用户的详细结果 + - elapsed_time: 执行耗时（秒） + - task_id: 任务ID + """ + start_time = time.time() + + async def _run() -> Dict[str, Any]: + from app.core.logging_config import get_logger + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository + from app.services.implicit_memory_service import ImplicitMemoryService + from app.services.emotion_analytics_service import EmotionAnalyticsService + + logger = get_logger(__name__) + logger.info("开始执行隐性记忆和情绪数据更新定时任务") + + total_users = 0 + successful_implicit = 0 + successful_emotion = 0 + failed = 0 + user_results = [] + + with get_db_context() as db: + try: + # 获取所有已存储数据的用户ID + repo = ImplicitEmotionsStorageRepository(db) + user_ids = repo.get_all_user_ids() + total_users = len(user_ids) + + logger.info(f"找到 {total_users} 个需要更新的用户") + + # 遍历每个用户并更新数据 + for end_user_id in user_ids: + logger.info(f"开始处理用户: {end_user_id}") + user_start_time = time.time() + + implicit_success = False + emotion_success = False + errors = [] + + try: + # 更新隐性记忆画像 + try: + implicit_service = ImplicitMemoryService(db=db, end_user_id=end_user_id) + profile_data = await implicit_service.generate_complete_profile(user_id=end_user_id) + await implicit_service.save_profile_cache( + end_user_id=end_user_id, + profile_data=profile_data, + db=db + ) + implicit_success = True + logger.info(f"成功更新用户 {end_user_id} 的隐性记忆画像") + except Exception as e: + error_msg = f"隐性记忆更新失败: {str(e)}" + errors.append(error_msg) + logger.error(f"用户 {end_user_id} {error_msg}") + + # 更新情绪建议 + try: + emotion_service = EmotionAnalyticsService(db=db, end_user_id=end_user_id) + suggestions_data = await emotion_service.generate_emotion_suggestions( + end_user_id=end_user_id, + db=db, + language="zh" + ) + await emotion_service.save_suggestions_cache( + end_user_id=end_user_id, + suggestions_data=suggestions_data, + db=db + ) + emotion_success = True + logger.info(f"成功更新用户 {end_user_id} 的情绪建议") + except Exception as e: + error_msg = f"情绪建议更新失败: {str(e)}" + errors.append(error_msg) + logger.error(f"用户 {end_user_id} {error_msg}") + + # 统计结果 + if implicit_success: + successful_implicit += 1 + if emotion_success: + successful_emotion += 1 + if not implicit_success and not emotion_success: + failed += 1 + + user_elapsed = time.time() - user_start_time + + # 记录用户处理结果 + user_result = { + "end_user_id": end_user_id, + "implicit_success": implicit_success, + "emotion_success": emotion_success, + "errors": errors, + "elapsed_time": user_elapsed + } + user_results.append(user_result) + + logger.info( + f"用户 {end_user_id} 处理完成: " + f"隐性记忆={'成功' if implicit_success else '失败'}, " + f"情绪建议={'成功' if emotion_success else '失败'}, " + f"耗时={user_elapsed:.2f}秒" + ) + + except Exception as e: + # 单个用户失败不影响其他用户（错误隔离） + failed += 1 + user_elapsed = time.time() - user_start_time + error_info = { + "end_user_id": end_user_id, + "implicit_success": False, + "emotion_success": False, + "errors": [str(e)], + "elapsed_time": user_elapsed + } + user_results.append(error_info) + logger.error(f"处理用户 {end_user_id} 时出错: {str(e)}") + + # 记录总体统计信息 + logger.info( + f"隐性记忆和情绪数据更新定时任务完成: " + f"总用户数={total_users}, " + f"隐性记忆成功={successful_implicit}, " + f"情绪建议成功={successful_emotion}, " + f"失败={failed}" + ) + + return { + "status": "SUCCESS", + "message": f"成功处理 {total_users} 个用户，隐性记忆 {successful_implicit} 个成功，情绪建议 {successful_emotion} 个成功", + "total_users": total_users, + "successful_implicit": successful_implicit, + "successful_emotion": successful_emotion, + "failed": failed, + "user_results": user_results[:50] # 只保留前50个用户的详细结果 + } + + except Exception as e: + logger.error(f"隐性记忆和情绪数据更新定时任务执行失败: {str(e)}") + return { + "status": "FAILURE", + "error": str(e), + "total_users": total_users, + "successful_implicit": successful_implicit, + "successful_emotion": successful_emotion, + "failed": failed, + "user_results": user_results[:50] + } + + try: + # 使用 nest_asyncio 来避免事件循环冲突 + try: + import nest_asyncio + nest_asyncio.apply() + except ImportError: + pass + + # 尝试获取现有事件循环，如果不存在则创建新的 + 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) + + result = loop.run_until_complete(_run()) + elapsed_time = time.time() - start_time + result["elapsed_time"] = elapsed_time + result["task_id"] = self.request.id + + return result + except Exception as e: + elapsed_time = time.time() - start_time + return { + "status": "FAILURE", + "error": str(e), + "elapsed_time": elapsed_time, + "task_id": self.request.id + } From 006c6cd1595a33f549b4bb8d94969efba1490204 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 15:16:47 +0800 Subject: [PATCH 05/31] [changes] AI reviews and modifies the code --- api/app/cache/__init__.py | 7 +- api/app/cache/memory/__init__.py | 8 +- api/app/controllers/emotion_controller.py | 12 +- .../controllers/implicit_memory_controller.py | 31 +-- .../models/implicit_emotions_storage_model.py | 7 +- .../implicit_emotions_storage_repository.py | 212 +++++++----------- api/app/services/emotion_analytics_service.py | 6 +- api/app/services/implicit_memory_service.py | 4 +- api/app/tasks.py | 15 +- 9 files changed, 114 insertions(+), 188 deletions(-) diff --git a/api/app/cache/__init__.py b/api/app/cache/__init__.py index a79d4cb2..748ce8ae 100644 --- a/api/app/cache/__init__.py +++ b/api/app/cache/__init__.py @@ -2,10 +2,7 @@ Cache 缓存模块 提供各种缓存功能的统一入口 +注意：隐性记忆和情绪建议已迁移到数据库存储，不再使用Redis缓存 """ -from .memory import EmotionMemoryCache, ImplicitMemoryCache -__all__ = [ - "EmotionMemoryCache", - "ImplicitMemoryCache", -] +__all__ = [] diff --git a/api/app/cache/memory/__init__.py b/api/app/cache/memory/__init__.py index 4ada3153..35f45aad 100644 --- a/api/app/cache/memory/__init__.py +++ b/api/app/cache/memory/__init__.py @@ -2,11 +2,7 @@ Memory 缓存模块 提供记忆系统相关的缓存功能 +注意：隐性记忆和情绪建议已迁移到数据库存储，不再使用Redis缓存 """ -from .emotion_memory import EmotionMemoryCache -from .implicit_memory import ImplicitMemoryCache -__all__ = [ - "EmotionMemoryCache", - "ImplicitMemoryCache", -] +__all__ = [] diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 02ce7862..0a8b5fc8 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -262,7 +262,6 @@ async def check_emotion_data_exists( @router.post("/suggestions", response_model=ApiResponse) async def get_emotion_suggestions( request: EmotionSuggestionsRequest, - language_type: str = Header(default=None, alias="X-Language-Type"), db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): @@ -277,9 +276,6 @@ async def get_emotion_suggestions( 存储的个性化情绪建议响应 """ try: - # 使用集中化的语言校验 - language = get_language_from_header(language_type) - api_logger.info( f"用户 {current_user.username} 请求获取个性化情绪建议", extra={ @@ -295,15 +291,13 @@ async def get_emotion_suggestions( ) if data is None: - # 数据不存在，返回提示信息 api_logger.info( f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - return fail( - BizCode.NOT_FOUND, - "情绪建议数据不存在，请点击右上角刷新进行初始化", - "" + return success( + data={"exists": False}, + msg="情绪建议数据不存在，请点击右上角刷新进行初始化" ) api_logger.info( diff --git a/api/app/controllers/implicit_memory_controller.py b/api/app/controllers/implicit_memory_controller.py index 91e634c9..76a87c5f 100644 --- a/api/app/controllers/implicit_memory_controller.py +++ b/api/app/controllers/implicit_memory_controller.py @@ -152,10 +152,9 @@ async def check_user_data_exists( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - {"exists": False} + return success( + data={"exists": False}, + msg="画像数据不存在，请点击右上角刷新进行初始化" ) api_logger.info(f"用户 {end_user_id} 的画像数据存在") @@ -203,11 +202,7 @@ async def get_preference_tags( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract preferences from cache preferences = cached_profile.get("preferences", []) @@ -274,11 +269,7 @@ async def get_dimension_portrait( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract portrait from cache portrait = cached_profile.get("portrait", {}) @@ -322,11 +313,7 @@ async def get_interest_area_distribution( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract interest areas from cache interest_areas = cached_profile.get("interest_areas", {}) @@ -374,11 +361,7 @@ async def get_behavior_habits( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract habits from cache habits = cached_profile.get("habits", []) diff --git a/api/app/models/implicit_emotions_storage_model.py b/api/app/models/implicit_emotions_storage_model.py index 57c0fd61..cf654950 100644 --- a/api/app/models/implicit_emotions_storage_model.py +++ b/api/app/models/implicit_emotions_storage_model.py @@ -19,8 +19,8 @@ class ImplicitEmotionsStorage(Base): # 主键 id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, comment="主键ID") - # 用户标识 - end_user_id = Column(String(255), nullable=False, unique=True, index=True, comment="终端用户ID") + # 用户标识（unique=True会自动创建唯一索引） + end_user_id = Column(String(255), nullable=False, unique=True, comment="终端用户ID") # 隐性记忆画像数据（JSON格式） implicit_profile = Column(JSONB, nullable=True, comment="隐性记忆用户画像数据") @@ -36,9 +36,8 @@ class ImplicitEmotionsStorage(Base): implicit_generated_at = Column(DateTime, nullable=True, comment="隐性记忆画像生成时间") emotion_generated_at = Column(DateTime, nullable=True, comment="情绪建议生成时间") - # 索引 + # 索引（只为updated_at创建索引，end_user_id的unique约束已自动创建索引） __table_args__ = ( - Index('idx_end_user_id', 'end_user_id'), Index('idx_updated_at', 'updated_at'), ) diff --git a/api/app/repositories/implicit_emotions_storage_repository.py b/api/app/repositories/implicit_emotions_storage_repository.py index fd4b10ce..176012b7 100644 --- a/api/app/repositories/implicit_emotions_storage_repository.py +++ b/api/app/repositories/implicit_emotions_storage_repository.py @@ -2,10 +2,11 @@ Implicit Emotions Storage Repository 数据访问层：处理隐性记忆和情绪数据的数据库操作 +事务由调用方控制，仓储层只使用 flush/refresh """ import logging from datetime import datetime -from typing import Optional, List +from typing import Optional, Generator from sqlalchemy.orm import Session from sqlalchemy import select @@ -16,154 +17,105 @@ logger = logging.getLogger(__name__) class ImplicitEmotionsStorageRepository: """隐性记忆和情绪存储仓储类""" - + def __init__(self, db: Session): self.db = db - + def get_by_end_user_id(self, end_user_id: str) -> Optional[ImplicitEmotionsStorage]: - """根据终端用户ID获取存储记录 - - Args: - end_user_id: 终端用户ID - - Returns: - 存储记录，如果不存在返回None - """ + """根据终端用户ID获取存储记录""" try: stmt = select(ImplicitEmotionsStorage).where( ImplicitEmotionsStorage.end_user_id == end_user_id ) - result = self.db.execute(stmt).scalar_one_or_none() - return result + return self.db.execute(stmt).scalar_one_or_none() except Exception as e: logger.error(f"获取用户存储记录失败: end_user_id={end_user_id}, error={e}") return None - + def create(self, end_user_id: str) -> ImplicitEmotionsStorage: - """创建新的存储记录 - - Args: - end_user_id: 终端用户ID - - Returns: - 新创建的存储记录 - """ - try: - storage = ImplicitEmotionsStorage( - end_user_id=end_user_id, - created_at=datetime.utcnow(), - updated_at=datetime.utcnow() - ) - self.db.add(storage) - self.db.commit() - self.db.refresh(storage) - logger.info(f"创建用户存储记录成功: end_user_id={end_user_id}") - return storage - except Exception as e: - self.db.rollback() - logger.error(f"创建用户存储记录失败: end_user_id={end_user_id}, error={e}") - raise - + """创建新的存储记录（事务由调用方提交）""" + storage = ImplicitEmotionsStorage( + end_user_id=end_user_id, + created_at=datetime.utcnow(), + updated_at=datetime.utcnow() + ) + self.db.add(storage) + self.db.flush() + self.db.refresh(storage) + logger.info(f"创建用户存储记录成功: end_user_id={end_user_id}") + return storage + def update_implicit_profile( self, end_user_id: str, profile_data: dict - ) -> Optional[ImplicitEmotionsStorage]: - """更新隐性记忆画像数据 - - Args: - end_user_id: 终端用户ID - profile_data: 画像数据 - - Returns: - 更新后的存储记录 - """ - try: - storage = self.get_by_end_user_id(end_user_id) - - if storage is None: - # 如果记录不存在，创建新记录 - storage = self.create(end_user_id) - - storage.implicit_profile = profile_data - storage.implicit_generated_at = datetime.utcnow() - storage.updated_at = datetime.utcnow() - - self.db.commit() - self.db.refresh(storage) - logger.info(f"更新隐性记忆画像成功: end_user_id={end_user_id}") - return storage - except Exception as e: - self.db.rollback() - logger.error(f"更新隐性记忆画像失败: end_user_id={end_user_id}, error={e}") - raise - + ) -> ImplicitEmotionsStorage: + """更新隐性记忆画像数据（事务由调用方提交）""" + storage = self.get_by_end_user_id(end_user_id) + if storage is None: + storage = self.create(end_user_id) + + storage.implicit_profile = profile_data + storage.implicit_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.flush() + self.db.refresh(storage) + logger.info(f"更新隐性记忆画像成功: end_user_id={end_user_id}") + return storage + def update_emotion_suggestions( self, end_user_id: str, suggestions_data: dict - ) -> Optional[ImplicitEmotionsStorage]: - """更新情绪建议数据 - + ) -> ImplicitEmotionsStorage: + """更新情绪建议数据（事务由调用方提交）""" + storage = self.get_by_end_user_id(end_user_id) + if storage is None: + storage = self.create(end_user_id) + + storage.emotion_suggestions = suggestions_data + storage.emotion_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.flush() + self.db.refresh(storage) + logger.info(f"更新情绪建议成功: end_user_id={end_user_id}") + return storage + + def get_all_user_ids(self, batch_size: int = 100) -> Generator[str, None, None]: + """分批次获取所有已存储数据的用户ID（避免大数据量内存溢出） + Args: - end_user_id: 终端用户ID - suggestions_data: 建议数据 - - Returns: - 更新后的存储记录 + batch_size: 每批次加载的数量，默认100 + + Yields: + 用户ID字符串 """ - try: - storage = self.get_by_end_user_id(end_user_id) - - if storage is None: - # 如果记录不存在，创建新记录 - storage = self.create(end_user_id) - - storage.emotion_suggestions = suggestions_data - storage.emotion_generated_at = datetime.utcnow() - storage.updated_at = datetime.utcnow() - - self.db.commit() - self.db.refresh(storage) - logger.info(f"更新情绪建议成功: end_user_id={end_user_id}") - return storage - except Exception as e: - self.db.rollback() - logger.error(f"更新情绪建议失败: end_user_id={end_user_id}, error={e}") - raise - - def get_all_user_ids(self) -> List[str]: - """获取所有已存储数据的用户ID列表 - - Returns: - 用户ID列表 - """ - try: - stmt = select(ImplicitEmotionsStorage.end_user_id) - result = self.db.execute(stmt).scalars().all() - return list(result) - except Exception as e: - logger.error(f"获取所有用户ID失败: error={e}") - return [] - + offset = 0 + while True: + try: + stmt = ( + select(ImplicitEmotionsStorage.end_user_id) + .order_by(ImplicitEmotionsStorage.end_user_id) + .limit(batch_size) + .offset(offset) + ) + batch = self.db.execute(stmt).scalars().all() + if not batch: + break + yield from batch + offset += batch_size + except Exception as e: + logger.error(f"分批获取用户ID失败: offset={offset}, error={e}") + break + def delete_by_end_user_id(self, end_user_id: str) -> bool: - """删除用户的存储记录 - - Args: - end_user_id: 终端用户ID - - Returns: - 是否删除成功 - """ - try: - storage = self.get_by_end_user_id(end_user_id) - if storage: - self.db.delete(storage) - self.db.commit() - logger.info(f"删除用户存储记录成功: end_user_id={end_user_id}") - return True - return False - except Exception as e: - self.db.rollback() - logger.error(f"删除用户存储记录失败: end_user_id={end_user_id}, error={e}") - return False + """删除用户的存储记录（事务由调用方提交）""" + storage = self.get_by_end_user_id(end_user_id) + if storage: + self.db.delete(storage) + self.db.flush() + logger.info(f"删除用户存储记录成功: end_user_id={end_user_id}") + return True + return False diff --git a/api/app/services/emotion_analytics_service.py b/api/app/services/emotion_analytics_service.py index 099cbfb7..c226348e 100644 --- a/api/app/services/emotion_analytics_service.py +++ b/api/app/services/emotion_analytics_service.py @@ -892,12 +892,12 @@ class EmotionAnalyticsService: logger.info(f"保存建议到数据库: user={end_user_id}") - # 保存到数据库 repo = ImplicitEmotionsStorageRepository(db) repo.update_emotion_suggestions(end_user_id, suggestions_data) + db.commit() logger.info(f"建议保存成功: user={end_user_id}") except Exception as e: - logger.error(f"保存建议失败: {str(e)}", exc_info=True) - # 不抛出异常，存储失败不应影响主流程 \ No newline at end of file + db.rollback() + logger.error(f"保存建议失败: {str(e)}", exc_info=True) \ No newline at end of file diff --git a/api/app/services/implicit_memory_service.py b/api/app/services/implicit_memory_service.py index 534f138c..4bd11deb 100644 --- a/api/app/services/implicit_memory_service.py +++ b/api/app/services/implicit_memory_service.py @@ -471,12 +471,12 @@ class ImplicitMemoryService: logger.info(f"保存用户画像到数据库: user={end_user_id}") - # 保存到数据库 repo = ImplicitEmotionsStorageRepository(db) repo.update_implicit_profile(end_user_id, profile_data) + db.commit() logger.info(f"用户画像保存成功: user={end_user_id}") except Exception as e: + db.rollback() logger.error(f"保存用户画像失败: {str(e)}", exc_info=True) - # 不抛出异常，存储失败不应影响主流程 diff --git a/api/app/tasks.py b/api/app/tasks.py index 5a320c3f..1675f25d 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -1963,6 +1963,8 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: async def _run() -> Dict[str, Any]: from app.core.logging_config import get_logger from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository + from app.models.implicit_emotions_storage_model import ImplicitEmotionsStorage + from sqlalchemy import select, func from app.services.implicit_memory_service import ImplicitMemoryService from app.services.emotion_analytics_service import EmotionAnalyticsService @@ -1977,15 +1979,18 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: with get_db_context() as db: try: - # 获取所有已存储数据的用户ID + # 获取所有已存储数据的用户ID（分批次处理） repo = ImplicitEmotionsStorageRepository(db) - user_ids = repo.get_all_user_ids() - total_users = len(user_ids) + # 先统计总数用于日志 + from sqlalchemy import func + total_users = db.execute( + select(func.count()).select_from(ImplicitEmotionsStorage) + ).scalar() or 0 logger.info(f"找到 {total_users} 个需要更新的用户") - # 遍历每个用户并更新数据 - for end_user_id in user_ids: + # 遍历每个用户并更新数据（分批次，避免一次性加载所有ID） + for end_user_id in repo.get_all_user_ids(batch_size=100): logger.info(f"开始处理用户: {end_user_id}") user_start_time = time.time() From 5edf3f2b8a698056ed1a17dc7ea2562c31888c9c Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 16:16:16 +0800 Subject: [PATCH 06/31] [changes] Test the scheduled task --- api/app/celery_app.py | 8 +-- api/app/controllers/emotion_controller.py | 88 +++++++++++------------ redbear-mem-benchmark | 2 +- 3 files changed, 47 insertions(+), 51 deletions(-) diff --git a/api/app/celery_app.py b/api/app/celery_app.py index e804d303..33fa1703 100644 --- a/api/app/celery_app.py +++ b/api/app/celery_app.py @@ -117,12 +117,8 @@ beat_schedule_config = { "config_id": None, # 使用默认配置，可以通过环境变量配置 }, }, -} - -#如果配置了默认工作空间ID，则添加记忆总量统计任务 -if settings.DEFAULT_WORKSPACE_ID: - beat_schedule_config["write-total-memory"] = { - "task": "app.controllers.memory_storage_controller.search_all", + "write-all-workspaces-memory": { + "task": "app.tasks.write_all_workspaces_memory_task", "schedule": memory_increment_schedule, "args": (), }, diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 0a8b5fc8..8cfc5014 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -208,55 +208,55 @@ async def get_emotion_health( -@router.post("/check-data", response_model=ApiResponse) -async def check_emotion_data_exists( - request: EmotionSuggestionsRequest, - db: Session = Depends(get_db), - current_user: User = Depends(get_current_user), -): - """检查用户情绪建议数据是否存在 +# @router.post("/check-data", response_model=ApiResponse) +# async def check_emotion_data_exists( +# request: EmotionSuggestionsRequest, +# db: Session = Depends(get_db), +# current_user: User = Depends(get_current_user), +# ): +# """检查用户情绪建议数据是否存在 - Args: - request: 包含 end_user_id - db: 数据库会话 - current_user: 当前用户 +# Args: +# request: 包含 end_user_id +# db: 数据库会话 +# current_user: 当前用户 - Returns: - 数据存在状态 - """ - try: - api_logger.info( - f"检查用户情绪建议数据是否存在: {request.end_user_id}", - extra={"end_user_id": request.end_user_id} - ) +# Returns: +# 数据存在状态 +# """ +# try: +# api_logger.info( +# f"检查用户情绪建议数据是否存在: {request.end_user_id}", +# extra={"end_user_id": request.end_user_id} +# ) - # 从数据库获取建议 - data = await emotion_service.get_cached_suggestions( - end_user_id=request.end_user_id, - db=db - ) +# # 从数据库获取建议 +# data = await emotion_service.get_cached_suggestions( +# end_user_id=request.end_user_id, +# db=db +# ) - if data is None: - api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据不存在") - return fail( - BizCode.NOT_FOUND, - "情绪建议数据不存在，请点击右上角刷新进行初始化", - {"exists": False} - ) +# if data is None: +# api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据不存在") +# return fail( +# BizCode.NOT_FOUND, +# "情绪建议数据不存在，请点击右上角刷新进行初始化", +# {"exists": False} +# ) - api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据存在") - return success(data={"exists": True}, msg="情绪建议数据已存在") +# api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据存在") +# return success(data={"exists": True}, msg="情绪建议数据已存在") - except Exception as e: - api_logger.error( - f"检查情绪建议数据失败: {str(e)}", - extra={"end_user_id": request.end_user_id}, - exc_info=True - ) - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail=f"检查情绪建议数据失败: {str(e)}" - ) +# except Exception as e: +# api_logger.error( +# f"检查情绪建议数据失败: {str(e)}", +# extra={"end_user_id": request.end_user_id}, +# exc_info=True +# ) +# raise HTTPException( +# status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, +# detail=f"检查情绪建议数据失败: {str(e)}" +# ) @router.post("/suggestions", response_model=ApiResponse) @@ -383,4 +383,4 @@ async def generate_emotion_suggestions( raise HTTPException( status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=f"生成个性化建议失败: {str(e)}" - ) + ) \ No newline at end of file diff --git a/redbear-mem-benchmark b/redbear-mem-benchmark index 4b0257bb..8494e824 160000 --- a/redbear-mem-benchmark +++ b/redbear-mem-benchmark @@ -1 +1 @@ -Subproject commit 4b0257bb4e7dc384b2aaf849b0bd6eae4b39835d +Subproject commit 8494e82498cb99c70ac67a64a544ff872432363a From bbb2c6c903460ae986e5113653f6ef68dcb1fba1 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 16:47:50 +0800 Subject: [PATCH 07/31] [changes] Modify the pop-up window for emotional suggestions at the backend --- api/app/controllers/emotion_controller.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 8cfc5014..ea7b719f 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -295,8 +295,8 @@ async def get_emotion_suggestions( f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - return success( - data={"exists": False}, + return fail( + code=404, msg="情绪建议数据不存在，请点击右上角刷新进行初始化" ) From 94836ed9af78e60c8417d7f174705822259b989c Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Wed, 4 Mar 2026 12:28:55 +0800 Subject: [PATCH 08/31] [add] Set up scheduled tasks for existing and new users --- api/app/celery_app.py | 11 ++- api/app/core/config.py | 10 +- .../implicit_emotions_storage_repository.py | 48 ++++++++- api/app/tasks.py | 97 ++++++++++++++++++- 4 files changed, 155 insertions(+), 11 deletions(-) diff --git a/api/app/celery_app.py b/api/app/celery_app.py index 33fa1703..ba294651 100644 --- a/api/app/celery_app.py +++ b/api/app/celery_app.py @@ -4,6 +4,7 @@ from datetime import timedelta from urllib.parse import quote from celery import Celery +from celery.schedules import crontab from app.core.config import settings @@ -93,10 +94,12 @@ celery_app.autodiscover_tasks(['app']) # Celery Beat schedule for periodic tasks memory_increment_schedule = timedelta(hours=settings.MEMORY_INCREMENT_INTERVAL_HOURS) memory_cache_regeneration_schedule = timedelta(hours=settings.MEMORY_CACHE_REGENERATION_HOURS) -# 这个30秒的设计不合理 -workspace_reflection_schedule = timedelta(seconds=30) # 每30秒运行一次settings.REFLECTION_INTERVAL_TIME -forgetting_cycle_schedule = timedelta(hours=24) # 每24小时运行一次遗忘周期 -implicit_emotions_update_schedule = timedelta(hours=24) # 每24小时更新一次隐性记忆和情绪数据 +workspace_reflection_schedule = timedelta(seconds=settings.WORKSPACE_REFLECTION_INTERVAL_SECONDS) +forgetting_cycle_schedule = timedelta(hours=settings.FORGETTING_CYCLE_INTERVAL_HOURS) +implicit_emotions_update_schedule = crontab( + hour=settings.IMPLICIT_EMOTIONS_UPDATE_HOUR, + minute=settings.IMPLICIT_EMOTIONS_UPDATE_MINUTE, +) #构建定时任务配置 beat_schedule_config = { diff --git a/api/app/core/config.py b/api/app/core/config.py index 3a0c97b4..dc993e24 100644 --- a/api/app/core/config.py +++ b/api/app/core/config.py @@ -208,7 +208,15 @@ class Settings: # Memory Cache Regeneration Configuration MEMORY_CACHE_REGENERATION_HOURS: int = int(os.getenv("MEMORY_CACHE_REGENERATION_HOURS", "24")) - # Memory Module Configuration (internal) + # Periodic Task Schedule Configuration + # workspace_reflection: 每隔多少秒执行一次 + WORKSPACE_REFLECTION_INTERVAL_SECONDS: int = int(os.getenv("WORKSPACE_REFLECTION_INTERVAL_SECONDS", "30")) + # forgetting_cycle: 每隔多少小时执行一次 + FORGETTING_CYCLE_INTERVAL_HOURS: int = int(os.getenv("FORGETTING_CYCLE_INTERVAL_HOURS", "24")) + # implicit_emotions_update: 每天几点执行（小时，0-23） + IMPLICIT_EMOTIONS_UPDATE_HOUR: int = int(os.getenv("IMPLICIT_EMOTIONS_UPDATE_HOUR", "2")) + # implicit_emotions_update: 每天几分执行（分钟，0-59） + IMPLICIT_EMOTIONS_UPDATE_MINUTE: int = int(os.getenv("IMPLICIT_EMOTIONS_UPDATE_MINUTE", "0")) # Memory Module Configuration (internal) MEMORY_OUTPUT_DIR: str = os.getenv("MEMORY_OUTPUT_DIR", "logs/memory-output") MEMORY_CONFIG_DIR: str = os.getenv("MEMORY_CONFIG_DIR", "app/core/memory") diff --git a/api/app/repositories/implicit_emotions_storage_repository.py b/api/app/repositories/implicit_emotions_storage_repository.py index 176012b7..1d11f89e 100644 --- a/api/app/repositories/implicit_emotions_storage_repository.py +++ b/api/app/repositories/implicit_emotions_storage_repository.py @@ -5,12 +5,13 @@ Implicit Emotions Storage Repository 事务由调用方控制，仓储层只使用 flush/refresh """ import logging -from datetime import datetime +from datetime import datetime, date from typing import Optional, Generator from sqlalchemy.orm import Session -from sqlalchemy import select +from sqlalchemy import select, not_, exists from app.models.implicit_emotions_storage_model import ImplicitEmotionsStorage +from app.models.end_user_model import EndUser logger = logging.getLogger(__name__) @@ -110,6 +111,49 @@ class ImplicitEmotionsStorageRepository: logger.error(f"分批获取用户ID失败: offset={offset}, error={e}") break + def get_new_user_ids_today(self, batch_size: int = 100) -> Generator[str, None, None]: + """分批次获取当天新增的、尚未初始化隐性记忆和情绪建议数据的用户ID + + 查询逻辑：end_users 表中 created_at 为今天，且在 implicit_emotions_storage 中没有对应记录。 + 没有对应记录意味着隐性记忆画像和情绪建议均未初始化，需要对这批用户执行首次初始化。 + end_users.id（UUID）转为字符串后与 implicit_emotions_storage.end_user_id（String）对比。 + + Args: + batch_size: 每批次加载的数量，默认100 + + Yields: + 用户ID字符串 + """ + from sqlalchemy import cast, String as SAString + today_start = datetime.combine(date.today(), datetime.min.time()) + offset = 0 + while True: + try: + stmt = ( + select(EndUser.id) + .where( + EndUser.created_at >= today_start, + not_( + exists( + select(ImplicitEmotionsStorage.end_user_id).where( + ImplicitEmotionsStorage.end_user_id == cast(EndUser.id, SAString) + ) + ) + ) + ) + .order_by(EndUser.id) + .limit(batch_size) + .offset(offset) + ) + batch = self.db.execute(stmt).scalars().all() + if not batch: + break + yield from (str(uid) for uid in batch) + offset += batch_size + except Exception as e: + logger.error(f"分批获取当天新增用户ID失败: offset={offset}, error={e}") + break + def delete_by_end_user_id(self, end_user_id: str) -> bool: """删除用户的存储记录（事务由调用方提交）""" storage = self.get_by_end_user_id(end_user_id) diff --git a/api/app/tasks.py b/api/app/tasks.py index 1675f25d..f30bbb81 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -2017,7 +2017,7 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: # 更新情绪建议 try: - emotion_service = EmotionAnalyticsService(db=db, end_user_id=end_user_id) + emotion_service = EmotionAnalyticsService() suggestions_data = await emotion_service.generate_emotion_suggestions( end_user_id=end_user_id, db=db, @@ -2076,22 +2076,109 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: user_results.append(error_info) logger.error(f"处理用户 {end_user_id} 时出错: {str(e)}") + # ---- 处理增量用户（当天新增、尚未初始化的用户）---- + new_users_initialized = 0 + new_users_failed = 0 + logger.info("开始处理当天新增的增量用户初始化") + + for end_user_id in repo.get_new_user_ids_today(batch_size=100): + logger.info(f"开始初始化新用户: {end_user_id}") + user_start_time = time.time() + implicit_success = False + emotion_success = False + errors = [] + + try: + try: + implicit_service = ImplicitMemoryService(db=db, end_user_id=end_user_id) + profile_data = await implicit_service.generate_complete_profile(user_id=end_user_id) + await implicit_service.save_profile_cache( + end_user_id=end_user_id, + profile_data=profile_data, + db=db + ) + implicit_success = True + logger.info(f"成功初始化新用户 {end_user_id} 的隐性记忆画像") + except Exception as e: + error_msg = f"隐性记忆初始化失败: {str(e)}" + errors.append(error_msg) + logger.error(f"新用户 {end_user_id} {error_msg}") + + try: + emotion_service = EmotionAnalyticsService() + suggestions_data = await emotion_service.generate_emotion_suggestions( + end_user_id=end_user_id, + db=db, + language="zh" + ) + await emotion_service.save_suggestions_cache( + end_user_id=end_user_id, + suggestions_data=suggestions_data, + db=db + ) + emotion_success = True + logger.info(f"成功初始化新用户 {end_user_id} 的情绪建议") + except Exception as e: + error_msg = f"情绪建议初始化失败: {str(e)}" + errors.append(error_msg) + logger.error(f"新用户 {end_user_id} {error_msg}") + + if implicit_success or emotion_success: + new_users_initialized += 1 + else: + new_users_failed += 1 + + user_elapsed = time.time() - user_start_time + user_results.append({ + "end_user_id": end_user_id, + "type": "init", + "implicit_success": implicit_success, + "emotion_success": emotion_success, + "errors": errors, + "elapsed_time": user_elapsed + }) + + except Exception as e: + new_users_failed += 1 + user_elapsed = time.time() - user_start_time + user_results.append({ + "end_user_id": end_user_id, + "type": "init", + "implicit_success": False, + "emotion_success": False, + "errors": [str(e)], + "elapsed_time": user_elapsed + }) + logger.error(f"初始化新用户 {end_user_id} 时出错: {str(e)}") + + logger.info( + f"增量用户初始化完成: 成功={new_users_initialized}, 失败={new_users_failed}" + ) + # ---- 增量用户处理结束 ---- + # 记录总体统计信息 logger.info( f"隐性记忆和情绪数据更新定时任务完成: " - f"总用户数={total_users}, " + f"存量用户总数={total_users}, " f"隐性记忆成功={successful_implicit}, " f"情绪建议成功={successful_emotion}, " - f"失败={failed}" + f"存量失败={failed}, " + f"增量初始化成功={new_users_initialized}, " + f"增量初始化失败={new_users_failed}" ) return { "status": "SUCCESS", - "message": f"成功处理 {total_users} 个用户，隐性记忆 {successful_implicit} 个成功，情绪建议 {successful_emotion} 个成功", + "message": ( + f"存量用户 {total_users} 个，隐性记忆 {successful_implicit} 个成功，情绪建议 {successful_emotion} 个成功；" + f"增量新用户初始化 {new_users_initialized} 个成功，{new_users_failed} 个失败" + ), "total_users": total_users, "successful_implicit": successful_implicit, "successful_emotion": successful_emotion, "failed": failed, + "new_users_initialized": new_users_initialized, + "new_users_failed": new_users_failed, "user_results": user_results[:50] # 只保留前50个用户的详细结果 } @@ -2104,6 +2191,8 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: "successful_implicit": successful_implicit, "successful_emotion": successful_emotion, "failed": failed, + "new_users_initialized": 0, + "new_users_failed": 0, "user_results": user_results[:50] } From 78fd1895104c9a9082fe121d24d9c69baf5f404b Mon Sep 17 00:00:00 2001 From: zhaoying Date: Fri, 27 Feb 2026 10:13:49 +0800 Subject: [PATCH 09/31] fix(web): release bugfix --- .../components/ChangeEmailModal.tsx | 6 +- .../views/Workflow/components/Chat/Chat.tsx | 812 +----------------- 2 files changed, 5 insertions(+), 813 deletions(-) diff --git a/web/src/views/UserManagement/components/ChangeEmailModal.tsx b/web/src/views/UserManagement/components/ChangeEmailModal.tsx index fbf93480..64791519 100644 --- a/web/src/views/UserManagement/components/ChangeEmailModal.tsx +++ b/web/src/views/UserManagement/components/ChangeEmailModal.tsx @@ -1,8 +1,8 @@ /* * @Author: ZhaoYing * @Date: 2026-02-25 11:45:07 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-25 11:45:07 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-02-27 09:59:41 */ /** * ChangeEmailModal Component @@ -114,7 +114,7 @@ const ChangeEmailModal = forwardRef( sendEmailCode({ email: values.new_email }) .then(() => { message.success(t('user.sendSuccess')) - setCountdown(300) + setCountdown(60) const timer = setInterval(() => { setCountdown((prev) => { if (prev <= 1) { diff --git a/web/src/views/Workflow/components/Chat/Chat.tsx b/web/src/views/Workflow/components/Chat/Chat.tsx index 51b1be38..895ade24 100644 --- a/web/src/views/Workflow/components/Chat/Chat.tsx +++ b/web/src/views/Workflow/components/Chat/Chat.tsx @@ -2,7 +2,7 @@ * @Author: ZhaoYing * @Date: 2026-02-06 21:10:56 * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-24 17:55:08 + * @Last Modified time: 2026-02-27 09:58:30 */ /** * Workflow Chat Component @@ -50,815 +50,7 @@ const Chat = forwardRef(({ appId // State management const [open, setOpen] = useState(false) // Drawer visibility const [loading, setLoading] = useState(false) // Send button loading state - const [chatList, setChatList] = useState([ - { - "role": "assistant", - "content": "经过多次打磨，最终作品如下：\n《咏一·三题》 \n孤光未凿太初溟， \n一粟吞天万籁宁。 \n影堕千峰青未染， \n心空四象白犹灵。 \n非从烛焰求明性， \n但向尘劳见本形。 \n忽有松风穿石罅， \n泠然吹落满山星。 \n\n注：本诗严守平水韵九青部（溟、宁、灵、形、星），其中“星”属下平声九青部异读字（《广韵》息盈切，与“灵”“宁”同部），古诗常用以协律，如王维“清溪流过碧山头，空水澄鲜一色秋。隔断红尘三十里，白云红叶两悠悠”中“悠”亦借韵通协。全诗紧扣“以一为魂”之旨：首句“孤光未凿”化《庄子·应帝王》“浑沌凿七窍而死”典，反写太初本明未分之境；次句“一粟吞天”，以微纳巨，承“一芥”而力愈雄浑；颔联“青未染”“白犹灵”，双色映照，暗喻性体离垢绝染而朗然常照；颈联直破二边——不假烛焰（破外求）、不避尘劳（破厌离），显《坛经》“佛法在世间，不离世间觉”之旨；结句松风裂石、星落满山，是“一”之活泼妙用：寂而常照，照而恒寂，恰如《道德经》“天得一以清，地得一以宁”之诗性证成。 \nLLM1结果：\n《咏一》 \n孤峰独峙破苍冥， \n一芥微身立太清。 \n万古乾坤凝此数， \n千山雪落只无声。 \n\n注：本诗以“一”为魂，通过“孤峰”“一芥”“此数”层层递进，赋予数字哲思——既写天地间唯一性之壮美（孤峰破冥），又寓渺小个体与永恒宇宙的辩证（芥子纳太清）。末句“千山雪落只无声”，以大静写大一，雪覆千山而声息俱寂，暗合《道德经》“天得一以清”之境。平仄依平水韵，押九青部（冥、清、声）。 ", - "created_at": 1771925594511, - "subContent": [ - { - "id": "start_1767617465337_0djnmpk2y", - "node_id": "start_1767617465337_0djnmpk2y", - "node_name": "开始（Start）", - "icon": "/src/assets/images/workflow/start.png", - "content": { - "input": { - "execution_id": "exec_11a80fb1cde148cb", - "conversation_id": "37ee003e-cc53-47e7-930f-a436a1252dd1", - "message": "1", - "conversation_vars": {} - }, - "output": { - "message": "1", - "execution_id": "exec_11a80fb1cde148cb", - "conversation_id": "37ee003e-cc53-47e7-930f-a436a1252dd1", - "workspace_id": "d17cd62d-a725-4fc0-813b-1093f2dfdee4", - "user_id": "ab27a27f-072b-47e9-8bbb-1f19322debcd", - "topic": "", - "number": 0, - "Boolean": false - } - }, - "status": "completed", - "elapsed_time": 0 - }, - { - "id": "llm_1767617499720_zvqwjpw3b", - "node_id": "llm_1767617499720_zvqwjpw3b", - "node_name": "大语言模型 (LLM)-初始创作", - "icon": "/src/assets/images/workflow/llm.png", - "content": { - "input": { - "prompt": null, - "messages": [ - { - "role": "system", - "content": "请根据1 为主题写一首七字诗。" - } - ], - "config": { - "model_id": "2699984d-23be-4817-b81c-c38682a08306", - "temperature": 0.7, 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"output": { - "poem_content": "《咏一》 \n孤峰独峙破苍冥， \n一芥微身立太清。 \n万古乾坤凝此数， \n千山雪落只无声。 \n\n注：本诗以“一”为魂，通过“孤峰”“一芥”“此数”层层递进，赋予数字哲思——既写天地间唯一性之壮美（孤峰破冥），又寓渺小个体与永恒宇宙的辩证（芥子纳太清）。末句“千山雪落只无声”，以大静写大一，雪覆千山而声息俱寂，暗合《道德经》“天得一以清”之境。平仄依平水韵，押九青部（冥、清、声）。", - "round": 0 - } - }, - "status": "completed", - "elapsed_time": 0.0005278587341308594 - }, - { - "cycle_idx": 0, - "node_id": "llm_1767617560401_bsx1vhi25", - "node_name": "大语言模型 (LLM)-润色器", - "icon": "/src/assets/images/workflow/llm.png", - "content": { - "cycle_idx": 0, - "input": { - "prompt": null, - "messages": [ - { - "role": "system", - "content": "请根据《咏一》 \n孤峰独峙破苍冥， \n一芥微身立太清。 \n万古乾坤凝此数， \n千山雪落只无声。 \n\n注：本诗以“一”为魂，通过“孤峰”“一芥”“此数”层层递进，赋予数字哲思——既写天地间唯一性之壮美（孤峰破冥），又寓渺小个体与永恒宇宙的辩证（芥子纳太清）。末句“千山雪落只无声”，以大静写大一，雪覆千山而声息俱寂，暗合《道德经》“天得一以清”之境。平仄依平水韵，押九青部（冥、清、声）。 为主题写一首七字诗。" - } - ], - "config": { - "model_id": "2699984d-23be-4817-b81c-c38682a08306", - "temperature": 0.7, - "max_tokens": 2000 - } - }, - "output": "《咏一·次韵》 \n千峰削玉立空青， \n一羽浮天亦自宁。 \n万籁收声归太始， \n孤光未堕即长明。 \n\n注：本诗承原作“以一为魂”之旨，严守平水韵九青部（青、宁、明），平仄谐律。首句“千峰削玉”反衬“一羽浮天”，以极繁托极简；次句“一羽”既承“一芥”之微，更取《庄子》“鹏徙南冥”之逸气，言至微者亦可持守本然之宁。三句“万籁收声”暗应原作“千山雪落只无声”，而升华为宇宙初开的“太始”静界；结句“孤光未堕即长明”，化用《淮南子》“日月不为明而明”与禅宗“一念不生即佛”，昭示“一”非寂灭之空，乃不假外求、本自圆成的永恒觉性——此即《道德经》“天得一以清”的诗性证悟。" - }, - "status": "completed", - "elapsed_time": 6.8497374057769775 - }, - { - "cycle_idx": 0, - "node_id": "assigner_1768285417545_qsoqleflh", - "node_name": "变量赋值", - "icon": "/src/assets/images/workflow/assigner.png", - "content": { - "cycle_idx": 0, - "input": { - "config": { - "assignments": [ - { - "value": "{{llm_1767617560401_bsx1vhi25.output}}", - "operation": "cover", - "variable_selector": "{{loop_1767617552451_hq3j342ha.poem_content}}" - }, - { - "value": 1, - "operation": "add", - "variable_selector": "{{loop_1767617552451_hq3j342ha.round}}" - } - ] - } - }, - "output": null - }, - "status": "completed", - "elapsed_time": 0.0003705024719238281 - }, - { - "cycle_idx": 1, - "node_id": "21046fb8-1f33-45f7-aeda-2c196471f119", - "node_name": null, - "icon": "/src/assets/images/workflow/loop.png", - "content": { - "cycle_idx": 1, - "input": { - "poem_content": "《咏一·次韵》 \n千峰削玉立空青， \n一羽浮天亦自宁。 \n万籁收声归太始， \n孤光未堕即长明。 \n\n注：本诗承原作“以一为魂”之旨，严守平水韵九青部（青、宁、明），平仄谐律。首句“千峰削玉”反衬“一羽浮天”，以极繁托极简；次句“一羽”既承“一芥”之微，更取《庄子》“鹏徙南冥”之逸气，言至微者亦可持守本然之宁。三句“万籁收声”暗应原作“千山雪落只无声”，而升华为宇宙初开的“太始”静界；结句“孤光未堕即长明”，化用《淮南子》“日月不为明而明”与禅宗“一念不生即佛”，昭示“一”非寂灭之空，乃不假外求、本自圆成的永恒觉性——此即《道德经》“天得一以清”的诗性证悟。", - "round": 1 - }, - "output": { - "poem_content": "《咏一·次韵》 \n千峰削玉立空青， \n一羽浮天亦自宁。 \n万籁收声归太始， \n孤光未堕即长明。 \n\n注：本诗承原作“以一为魂”之旨，严守平水韵九青部（青、宁、明），平仄谐律。首句“千峰削玉”反衬“一羽浮天”，以极繁托极简；次句“一羽”既承“一芥”之微，更取《庄子》“鹏徙南冥”之逸气，言至微者亦可持守本然之宁。三句“万籁收声”暗应原作“千山雪落只无声”，而升华为宇宙初开的“太始”静界；结句“孤光未堕即长明”，化用《淮南子》“日月不为明而明”与禅宗“一念不生即佛”，昭示“一”非寂灭之空，乃不假外求、本自圆成的永恒觉性——此即《道德经》“天得一以清”的诗性证悟。", - "round": 1 - } - }, - "status": "completed", - "elapsed_time": 0 - }, - { - "cycle_idx": 1, - "node_id": "llm_1767617560401_bsx1vhi25", - "node_name": "大语言模型 (LLM)-润色器", - "icon": "/src/assets/images/workflow/llm.png", - "content": { - "cycle_idx": 1, - "input": { - "prompt": null, - "messages": [ - { - "role": "system", - "content": "请根据《咏一·次韵》 \n千峰削玉立空青， \n一羽浮天亦自宁。 \n万籁收声归太始， \n孤光未堕即长明。 \n\n注：本诗承原作“以一为魂”之旨，严守平水韵九青部（青、宁、明），平仄谐律。首句“千峰削玉”反衬“一羽浮天”，以极繁托极简；次句“一羽”既承“一芥”之微，更取《庄子》“鹏徙南冥”之逸气，言至微者亦可持守本然之宁。三句“万籁收声”暗应原作“千山雪落只无声”，而升华为宇宙初开的“太始”静界；结句“孤光未堕即长明”，化用《淮南子》“日月不为明而明”与禅宗“一念不生即佛”，昭示“一”非寂灭之空，乃不假外求、本自圆成的永恒觉性——此即《道德经》“天得一以清”的诗性证悟。 为主题写一首七字诗。" - } - ], - "config": { - "model_id": "2699984d-23be-4817-b81c-c38682a08306", - "temperature": 0.7, - "max_tokens": 2000 - } - }, - "output": "《咏一·再题》 \n一芥浮空万籁停， \n千峰影落太初青。 \n光非燃烛恒明在， \n心不沾尘即性灵。 \n\n注：本诗续写“以一为魂”之旨，严守平水韵九青部（停、青、灵），平仄精严。首句“一芥”承原作微渺意象，而“万籁停”较“收声”更显寂然自定之境；次句倒装“千峰影落”，使苍茫山势如墨痕沉入宇宙初青，暗契《淮南子》“虚霩生宇宙，宇宙生气”之太始气象。三句翻出新境：“光非燃烛”，破除对光明之形器执取，直指《楞严经》“性觉妙明，本觉明妙”之不假缘起的本明；结句“心不沾尘即性灵”，化用六祖“本来无一物”与程颢“天地之大德曰生”，言“一”非枯寂之数，乃活泼泼的性灵朗现——此即《道德经》“昔之得一者，天清地宁”的诗性澄明。" - }, - "status": "completed", - "elapsed_time": 7.1851232051849365 - }, - { - "cycle_idx": 1, - "node_id": "assigner_1768285417545_qsoqleflh", - "node_name": "变量赋值", - "icon": "/src/assets/images/workflow/assigner.png", - "content": { - "cycle_idx": 1, - "input": { - "config": { - "assignments": [ - { - "value": "{{llm_1767617560401_bsx1vhi25.output}}", - "operation": "cover", - "variable_selector": "{{loop_1767617552451_hq3j342ha.poem_content}}" - }, - { - "value": 1, - "operation": "add", - "variable_selector": "{{loop_1767617552451_hq3j342ha.round}}" - } - ] - } - }, - "output": null - }, - "status": "completed", - "elapsed_time": 0 - }, - { - "cycle_idx": 2, - "node_id": "21046fb8-1f33-45f7-aeda-2c196471f119", - "node_name": null, - "icon": "/src/assets/images/workflow/loop.png", - "content": { - "cycle_idx": 2, - "input": { - "poem_content": "《咏一·再题》 \n一芥浮空万籁停， \n千峰影落太初青。 \n光非燃烛恒明在， \n心不沾尘即性灵。 \n\n注：本诗续写“以一为魂”之旨，严守平水韵九青部（停、青、灵），平仄精严。首句“一芥”承原作微渺意象，而“万籁停”较“收声”更显寂然自定之境；次句倒装“千峰影落”，使苍茫山势如墨痕沉入宇宙初青，暗契《淮南子》“虚霩生宇宙，宇宙生气”之太始气象。三句翻出新境：“光非燃烛”，破除对光明之形器执取，直指《楞严经》“性觉妙明，本觉明妙”之不假缘起的本明；结句“心不沾尘即性灵”，化用六祖“本来无一物”与程颢“天地之大德曰生”，言“一”非枯寂之数，乃活泼泼的性灵朗现——此即《道德经》“昔之得一者，天清地宁”的诗性澄明。", - "round": 2 - }, - "output": { - "poem_content": "《咏一·再题》 \n一芥浮空万籁停， \n千峰影落太初青。 \n光非燃烛恒明在， \n心不沾尘即性灵。 \n\n注：本诗续写“以一为魂”之旨，严守平水韵九青部（停、青、灵），平仄精严。首句“一芥”承原作微渺意象，而“万籁停”较“收声”更显寂然自定之境；次句倒装“千峰影落”，使苍茫山势如墨痕沉入宇宙初青，暗契《淮南子》“虚霩生宇宙，宇宙生气”之太始气象。三句翻出新境：“光非燃烛”，破除对光明之形器执取，直指《楞严经》“性觉妙明，本觉明妙”之不假缘起的本明；结句“心不沾尘即性灵”，化用六祖“本来无一物”与程颢“天地之大德曰生”，言“一”非枯寂之数，乃活泼泼的性灵朗现——此即《道德经》“昔之得一者，天清地宁”的诗性澄明。", - "round": 2 - } - }, - "status": "completed", - "elapsed_time": 0 - }, - { - "cycle_idx": 2, - "node_id": "llm_1767617560401_bsx1vhi25", - "node_name": "大语言模型 (LLM)-润色器", - "icon": "/src/assets/images/workflow/llm.png", - "content": { - "cycle_idx": 2, - "input": { - "prompt": null, - "messages": [ - { - "role": "system", - "content": "请根据《咏一·再题》 \n一芥浮空万籁停， \n千峰影落太初青。 \n光非燃烛恒明在， \n心不沾尘即性灵。 \n\n注：本诗续写“以一为魂”之旨，严守平水韵九青部（停、青、灵），平仄精严。首句“一芥”承原作微渺意象，而“万籁停”较“收声”更显寂然自定之境；次句倒装“千峰影落”，使苍茫山势如墨痕沉入宇宙初青，暗契《淮南子》“虚霩生宇宙，宇宙生气”之太始气象。三句翻出新境：“光非燃烛”，破除对光明之形器执取，直指《楞严经》“性觉妙明，本觉明妙”之不假缘起的本明；结句“心不沾尘即性灵”，化用六祖“本来无一物”与程颢“天地之大德曰生”，言“一”非枯寂之数，乃活泼泼的性灵朗现——此即《道德经》“昔之得一者，天清地宁”的诗性澄明。 为主题写一首七字诗。" - } - ], - "config": { - "model_id": "2699984d-23be-4817-b81c-c38682a08306", - "temperature": 0.7, - "max_tokens": 2000 - } - }, - "output": "《咏一·三题》 \n孤光未凿太初溟， \n一粟吞天万籁宁。 \n影堕千峰青未染， \n心空四象白犹灵。 \n非从烛焰求明性， \n但向尘劳见本形。 \n忽有松风穿石罅， \n泠然吹落满山星。 \n\n注：本诗严守平水韵九青部（溟、宁、灵、形、星），其中“星”属下平声九青部异读字（《广韵》息盈切，与“灵”“宁”同部），古诗常用以协律，如王维“清溪流过碧山头，空水澄鲜一色秋。隔断红尘三十里，白云红叶两悠悠”中“悠”亦借韵通协。全诗紧扣“以一为魂”之旨：首句“孤光未凿”化《庄子·应帝王》“浑沌凿七窍而死”典，反写太初本明未分之境；次句“一粟吞天”，以微纳巨，承“一芥”而力愈雄浑；颔联“青未染”“白犹灵”，双色映照，暗喻性体离垢绝染而朗然常照；颈联直破二边——不假烛焰（破外求）、不避尘劳（破厌离），显《坛经》“佛法在世间，不离世间觉”之旨；结句松风裂石、星落满山，是“一”之活泼妙用：寂而常照，照而恒寂，恰如《道德经》“天得一以清，地得一以宁”之诗性证成。" - }, - "status": "completed", - "elapsed_time": 9.531717538833618 - }, - { - "cycle_idx": 2, - "node_id": "assigner_1768285417545_qsoqleflh", - "node_name": "变量赋值", - "icon": "/src/assets/images/workflow/assigner.png", - "content": { - "cycle_idx": 2, - "input": { - "config": { - "assignments": [ - { - "value": "{{llm_1767617560401_bsx1vhi25.output}}", - "operation": "cover", - "variable_selector": "{{loop_1767617552451_hq3j342ha.poem_content}}" - }, - { - "value": 1, - "operation": "add", - "variable_selector": "{{loop_1767617552451_hq3j342ha.round}}" - } - ] - } - }, - "output": null - }, - "status": "completed", - "elapsed_time": 0 - } - ], - "status": "completed", - "elapsed_time": 23.57662582397461 - }, - { - "id": "end_1767619139811_ko97mb12l", - "node_id": "end_1767619139811_ko97mb12l", - "node_name": "结束（End）", - "icon": "/src/assets/images/workflow/end.png", - "content": { - "input": { - "config": { - "output": "经过多次打磨，最终作品如下：\n{{loop_1767617552451_hq3j342ha.poem_content}} \nLLM1结果：\n{{llm_1767617499720_zvqwjpw3b.output}} " - } - }, - "output": "经过多次打磨，最终作品如下：\n《咏一·三题》 \n孤光未凿太初溟， \n一粟吞天万籁宁。 \n影堕千峰青未染， \n心空四象白犹灵。 \n非从烛焰求明性， \n但向尘劳见本形。 \n忽有松风穿石罅， \n泠然吹落满山星。 \n\n注：本诗严守平水韵九青部（溟、宁、灵、形、星），其中“星”属下平声九青部异读字（《广韵》息盈切，与“灵”“宁”同部），古诗常用以协律，如王维“清溪流过碧山头，空水澄鲜一色秋。隔断红尘三十里，白云红叶两悠悠”中“悠”亦借韵通协。全诗紧扣“以一为魂”之旨：首句“孤光未凿”化《庄子·应帝王》“浑沌凿七窍而死”典，反写太初本明未分之境；次句“一粟吞天”，以微纳巨，承“一芥”而力愈雄浑；颔联“青未染”“白犹灵”，双色映照，暗喻性体离垢绝染而朗然常照；颈联直破二边——不假烛焰（破外求）、不避尘劳（破厌离），显《坛经》“佛法在世间，不离世间觉”之旨；结句松风裂石、星落满山，是“一”之活泼妙用：寂而常照，照而恒寂，恰如《道德经》“天得一以清，地得一以宁”之诗性证成。 \nLLM1结果：\n《咏一》 \n孤峰独峙破苍冥， \n一芥微身立太清。 \n万古乾坤凝此数， \n千山雪落只无声。 \n\n注：本诗以“一”为魂，通过“孤峰”“一芥”“此数”层层递进，赋予数字哲思——既写天地间唯一性之壮美（孤峰破冥），又寓渺小个体与永恒宇宙的辩证（芥子纳太清）。末句“千山雪落只无声”，以大静写大一，雪覆千山而声息俱寂，暗合《道德经》“天得一以清”之境。平仄依平水韵，押九青部（冥、清、声）。 " - }, - "status": "completed", - "elapsed_time": 0.0005218982696533203 - } - ], - "status": "completed" - } - ]) // Chat message history + const [chatList, setChatList] = useState([]) // Chat message history const [variables, setVariables] = useState([]) // Workflow input variables const [streamLoading, setStreamLoading] = useState(false) // SSE streaming state const [conversationId, setConversationId] = useState(null) // Current conversation ID From 34310bfabe1559834223198b0f8452c1cb69147b Mon Sep 17 00:00:00 2001 From: Timebomb2018 <18868801967@163.com> Date: Thu, 26 Feb 2026 16:22:45 +0800 Subject: [PATCH 10/31] fix(version): fix version information --- api/app/version_info.json | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) diff --git a/api/app/version_info.json b/api/app/version_info.json index 991369d7..aea03dcd 100644 --- a/api/app/version_info.json +++ b/api/app/version_info.json @@ -1,4 +1,38 @@ { + "v0.2.4": { + "introduction": { + "codeName": "智远", + "releaseDate": "2026-2-11", + "upgradePosition": "🐻 生产级稳健性升级版本，智慧致远，从容应对复杂场景", + "coreUpgrades": [ + "1. Skills 技能框架 🛠️
* Skills 支持：引入全新的Skills技能系统，支持可扩展的能力模块，可在Agent和工作流中动态加载与编排", + "2. 多模态与交互 💬
* 文件多模态支持：全面支持消息输入、LLM处理和输出渲染中的多模态文件处理，实现更丰富的媒体感知对话
* 语音交互：语音交互功能正在积极开发中，为免提对话体验奠定基础（开发中）", + "3. 知识库集成 📚
* 飞书知识库：无缝对接飞书文档库，支持企业知识检索
* 语雀知识库：原生连接语雀文档平台，扩展对国内企业工具生态的覆盖
* Web站点知识库：通用Web站点抓取与索引，支持从公开网页内容构建知识库
* 视觉模型选择优化：知识库视觉模型配置现已支持LLM和Chat两种模型类型，移除了此前仅限Chat类型的限制", + "4. 记忆智能 🧠
* 本体工程（二期）：基于本体工程的高级记忆场景分类与萃取，实现结构化、领域感知的记忆组织，提升分类准确性
* 默认模型配置：情绪分析、反思和记忆萃取模块现默认使用空间级模型，确保开箱即用的一致性行为
* 智能模型回退：当已配置的情绪或反思模型为空或不可用时，系统自动回退至空间默认模型，避免静默失败
* 记忆模型回退兜底：当记忆中配置的模型为空或不可用时，系统优雅降级至空间默认模型", + "5. 性能与扩展 ⚡
* 模型并发（model_api_keys）：支持并发模型API Key管理，实现并行模型调用，提升高负载场景下的吞吐能力", + "6. 稳健性与缺陷修复 🔧
* 记忆配置版本固定：修复用户记忆配置未跟随应用版本发布固定的问题，消除跨部署的行为不一致
* 空间默认记忆保护：空间级默认记忆配置现不可删除；用户级配置仍可删除
* Agent与工作流配置兜底：解决Agent和工作流节点中记忆配置可能为空、或已选择但未配置的边界情况——全面的回退处理现可防止运行时错误
* 隐形记忆字段重命名：将隐形记忆接口JSON响应中的user_id修正为end_user_id，与规范数据模型对齐
* 记忆配置ID迁移：将Agent和工作流记忆配置中的memory_content重命名为memory_config_id，保持API一致性
* Worker-Memory告警解决：解决worker-memory服务中的告警级别问题，提升运维监控清晰度
* 双语接口修复：修复记忆相关API接口的中英文不一致问题
* 新用户记忆配置自动回填：新创建的EndUser若memory_config_id为None，系统自动从最新Release获取memory_config_id并回填
* 存量用户记忆配置自动回填：已有EndUser若memory_config_id为None，系统同样从最新Release获取并回填，确保向后兼容，无需手动迁移", + "
", + "Memory Bear v0.2.4 向生产级稳健性迈进，Skills框架与多模态支持开启认知平台新篇章。", + "记忆熊，智慧致远，从容应对真实世界的多样性。🐻✨" + ] + }, + "introduction_en": { + "codeName": "ZhiYuan", + "releaseDate": "2026-2-11", + "upgradePosition": "🐻 Production-grade resilience release — Wisdom Reaching Far, gracefully handling complex scenarios", + "coreUpgrades": [ + "1. Skills Framework 🛠️
* Skills Support: Introduced a new Skills system, enabling extensible capability modules that can be dynamically loaded and orchestrated within agents and workflows", + "2. Multimodal & Interaction 💬
* File Multimodal Support: Full multimodal file handling across message input, LLM processing, and output rendering — supporting richer, media-aware conversations
* Voice Interaction: Voice-based interaction capabilities are under active development, laying the groundwork for hands-free conversational experiences (In Progress)", + "3. Knowledge Base Integration 📚
* Feishu Knowledge Base: Seamless integration with Feishu (Lark) document repositories for enterprise knowledge retrieval
* Yuque Knowledge Base: Native connector for Yuque documentation platforms, expanding coverage of Chinese enterprise tooling
* Web Site Knowledge Base: General-purpose web site crawling and indexing for knowledge base construction from public web content
* Visual Model Selection: Knowledge base visual model configuration now supports both LLM and Chat model types, removing the previous restriction to Chat-only selection", + "4. Memory Intelligence 🧠
* Ontology Engineering (Phase 2): Advanced memory scene classification and extraction powered by ontology engineering — enabling structured, domain-aware memory organization with improved categorization accuracy
* Default Model Configuration: Emotion analysis, reflection, and memory extraction modules now default to the space-level model, ensuring consistent behavior out of the box
* Intelligent Model Fallback: If configured emotion or reflection models are empty or unavailable, the system automatically falls back to the space default model — preventing silent failures
* Memory Config Fallback for Models: When any memory-configured model is empty or unavailable, the system gracefully degrades to the space default model", + "5. Performance & Scalability ⚡
* Model Concurrency (model_api_keys): Support for concurrent model API key management, enabling parallel model invocations and improved throughput for high-load scenarios", + "6. Robustness & Bug Fixes 🔧
* Memory Config Version Pinning: Fixed an issue where user memory configurations were not pinned to application release versions, causing inconsistent behavior across deployments
* Space Default Memory Protection: Space-level default memory configurations are now protected from deletion; user-level configurations remain deletable
* Agent & Workflow Config Fallback: Resolved edge cases in Agent and Workflow nodes where memory config could be empty or selected but unconfigured — comprehensive fallback handling now prevents runtime errors
* Implicit Memory Field Rename: Corrected user_id to end_user_id in JSON responses from implicit memory interfaces, aligning with the canonical data model
* Memory Config ID Migration: Renamed memory_content to memory_config_id in Agent and Workflow memory configurations for API consistency
* Worker-Memory Alerts: Resolved warning-level alerts in the worker-memory service, improving operational monitoring clarity
* Bilingual Interface Fixes: Fixed Chinese/English language inconsistencies across memory-related API interfaces
* EndUser Memory Config Auto-Backfill (New Users): When a newly created EndUser has memory_config_id as None, the system automatically fetches the latest release's memory_config_id and backfills it
* EndUser Memory Config Auto-Backfill (Existing Users): For existing EndUsers with memory_config_id as None, the system similarly retrieves and backfills from the latest release — ensuring backward compatibility without manual migration", + "
", + "Memory Bear v0.2.4 advances toward production-grade resilience, with the Skills framework and multimodal support opening a new chapter for the cognitive platform.", + "MemoryBear — Wisdom Reaching Far, gracefully handling real-world variability. 🐻✨" + ] + } + }, "v0.2.3": { "introduction": { "codeName": "归墟", From a39ba564faeb11a68520f01442ff038f6e4a4d02 Mon Sep 17 00:00:00 2001 From: Timebomb2018 <18868801967@163.com> Date: Thu, 26 Feb 2026 17:09:50 +0800 Subject: [PATCH 11/31] fix(file): File uploads can be made without workspace. --- api/app/models/file_metadata_model.py | 2 +- api/app/services/file_storage_service.py | 9 +++++---- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/api/app/models/file_metadata_model.py b/api/app/models/file_metadata_model.py index baf9bd97..28e87367 100644 --- a/api/app/models/file_metadata_model.py +++ b/api/app/models/file_metadata_model.py @@ -35,7 +35,7 @@ class FileMetadata(Base): id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True) tenant_id = Column(UUID(as_uuid=True), nullable=False, index=True, comment="Tenant ID") - workspace_id = Column(UUID(as_uuid=True), nullable=False, index=True, comment="Workspace ID") + workspace_id = Column(UUID(as_uuid=True), nullable=True, index=True, comment="Workspace ID") file_key = Column(String(512), nullable=False, unique=True, index=True, comment="Storage file key") file_name = Column(String(255), nullable=False, comment="Original file name") file_ext = Column(String(32), nullable=False, comment="File extension") diff --git a/api/app/services/file_storage_service.py b/api/app/services/file_storage_service.py index 672e1cff..bb9f1894 100644 --- a/api/app/services/file_storage_service.py +++ b/api/app/services/file_storage_service.py @@ -26,7 +26,7 @@ logger = get_business_logger() def generate_file_key( tenant_id: uuid.UUID, - workspace_id: uuid.UUID, + workspace_id: uuid.UUID | None, file_id: uuid.UUID, file_ext: str, ) -> str: @@ -56,8 +56,9 @@ def generate_file_key( # Ensure file_ext starts with a dot if file_ext and not file_ext.startswith('.'): file_ext = f'.{file_ext}' - - return f"{tenant_id}/{workspace_id}/{file_id}{file_ext}" + if workspace_id: + return f"{tenant_id}/{workspace_id}/{file_id}{file_ext}" + return f"{tenant_id}/{file_id}{file_ext}" class FileStorageService: @@ -96,7 +97,7 @@ class FileStorageService: async def upload_file( self, tenant_id: uuid.UUID, - workspace_id: uuid.UUID, + workspace_id: uuid.UUID | None, file_id: uuid.UUID, file_ext: str, content: bytes, From b9d7fb2598d8c303e4b2fad755d08a65556a9b6a Mon Sep 17 00:00:00 2001 From: Mark Date: Fri, 27 Feb 2026 10:22:36 +0800 Subject: [PATCH 12/31] [add] migration script --- .../versions/7672d8f0f939_202602271020.py | 36 +++++++++++++++++++ 1 file changed, 36 insertions(+) create mode 100644 api/migrations/versions/7672d8f0f939_202602271020.py diff --git a/api/migrations/versions/7672d8f0f939_202602271020.py b/api/migrations/versions/7672d8f0f939_202602271020.py new file mode 100644 index 00000000..b99953a2 --- /dev/null +++ b/api/migrations/versions/7672d8f0f939_202602271020.py @@ -0,0 +1,36 @@ +"""202602271020 + +Revision ID: 7672d8f0f939 +Revises: 75e28690ae87 +Create Date: 2026-02-27 10:21:46.951584 + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa + + +# revision identifiers, used by Alembic. +revision: str = '7672d8f0f939' +down_revision: Union[str, None] = '75e28690ae87' +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.alter_column('file_metadata', 'workspace_id', + existing_type=sa.UUID(), + nullable=True, + existing_comment='Workspace ID') + # ### end Alembic commands ### + + +def downgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.alter_column('file_metadata', 'workspace_id', + existing_type=sa.UUID(), + nullable=False, + existing_comment='Workspace ID') + # ### end Alembic commands ### From 2510f60dce981b58c4f37968ca748407a534bea4 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Fri, 27 Feb 2026 10:23:19 +0800 Subject: [PATCH 13/31] fix(web): change model list provider logo --- web/src/views/ModelManagement/List.tsx | 8 ++++---- web/src/views/ModelManagement/utils.ts | 25 +++++++++++++++++++++++-- 2 files changed, 27 insertions(+), 6 deletions(-) diff --git a/web/src/views/ModelManagement/List.tsx b/web/src/views/ModelManagement/List.tsx index ffa89fb4..ce4d61aa 100644 --- a/web/src/views/ModelManagement/List.tsx +++ b/web/src/views/ModelManagement/List.tsx @@ -1,8 +1,8 @@ /* * @Author: ZhaoYing * @Date: 2026-02-03 16:50:10 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-03 16:50:10 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-02-27 10:20:51 */ /** * Model List View @@ -21,7 +21,7 @@ import PageEmpty from '@/components/Empty/PageEmpty'; import Tag from '@/components/Tag'; import KeyConfigModal from './components/KeyConfigModal' import ModelListDetail from './components/ModelListDetail' -import { getLogoUrl } from './utils' +import { getListLogoUrl } from './utils' /** * Model list component @@ -70,7 +70,7 @@ const ModelList = forwardRef {item.provider[0].toUpperCase()} diff --git a/web/src/views/ModelManagement/utils.ts b/web/src/views/ModelManagement/utils.ts index fe36e137..bf44367f 100644 --- a/web/src/views/ModelManagement/utils.ts +++ b/web/src/views/ModelManagement/utils.ts @@ -1,8 +1,8 @@ /* * @Author: ZhaoYing * @Date: 2026-02-03 16:50:22 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-03 16:50:22 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-02-27 10:22:46 */ /** * Utility functions for Model Management @@ -40,5 +40,26 @@ export const getLogoUrl = (logo?: string) => { return logo } + return ICONS[logo as keyof typeof ICONS] || undefined +} + +/** + * Get logo URL from provider name or URL + * @param provider - Provider name + * @param logo - Provider name or logo URL + * @returns Logo URL or undefined + */ +export const getListLogoUrl = (provider?: string, logo?: string) => { + let url = ICONS[provider as keyof typeof ICONS] + + if (url) return url + + if (!logo) { + return undefined + } + if (logo.startsWith('http')) { + return logo + } + return ICONS[logo as keyof typeof ICONS] || undefined } \ No newline at end of file From 1ac6702eb0cfb1fd91bd2893c3a0210975bf4c4c Mon Sep 17 00:00:00 2001 From: Timebomb2018 <18868801967@163.com> Date: Fri, 27 Feb 2026 10:24:03 +0800 Subject: [PATCH 14/31] docs(version): Version 0.2.5 Release Notes --- api/app/version_info.json | 30 ++++++++++++++++++++++++++++++ 1 file changed, 30 insertions(+) diff --git a/api/app/version_info.json b/api/app/version_info.json index aea03dcd..a4ff5d55 100644 --- a/api/app/version_info.json +++ b/api/app/version_info.json @@ -1,4 +1,34 @@ { + "v0.2.5": { + "introduction": { + "codeName": "行云", + "releaseDate": "2026-2-26", + "upgradePosition": "🐻 精炼根基，优化核心用户体验与系统稳定性", + "coreUpgrades": [ + "1. 用户体验与国际化 🎨
* SSO 语言参数修复：解决 SSO 认证后添加 `?language=zh` 参数仍显示英文的问题，语言偏好现正确保留
* 邮箱修改支持：用户可直接在用户管理系统中修改邮箱地址", + "2. 工作流可视化增强 💬
* 循环与迭代节点输出展示：实时显示执行进度和中间输出，便于调试复杂迭代过程
* 变量支持回车选择：支持回车键确认变量选择，简化工作流配置流程", + "3. 多租户模型管理 ⚙️
* 租户隔离的模型密钥：模型广场排除自定义模型，模型列表按租户隔离密钥，防止跨租户密钥泄露", + "4. 稳健性与缺陷修复 🔧
* 知识图谱构建修复：解决知识图谱构建流程稳定性问题，确保更可靠的实体提取和关系映射", + "
", + "版本 0.2.5 通过解决国际化边界情况、增强多租户隔离和改进工作流透明度，构建更具生产就绪性的平台。工作流可视化改进为更复杂的调试和监控能力奠定基础。未来将继续深化企业就绪性，扩展用户管理功能、优化知识图谱智能和增强工作流编排能力，在可观测性、性能优化和无缝集成模式方面持续改进。", + "智慧致远 🐻✨" + ] + }, + "introduction_en": { + "codeName": "Flowing Clouds", + "releaseDate": "2026-2-26", + "upgradePosition": "🐻 Refined foundations with enhanced user experience and system stability", + "coreUpgrades": [ + "1. User Experience & Internationalization 🎨
* SSO Language Parameter Fix: Resolved issue where `?language=zh` parameter still showed English UI after SSO authentication
* Email Update Support: Users can now modify email addresses directly in user management system", + "2. Workflow Visualization Enhancements 💬
* Loop & Iteration Node Output Display: Real-time display of execution progress and intermediate outputs for easier debugging
* Variable Selection with Enter Key: Enabled Enter key confirmation for streamlined variable assignment", + "3. Multi-Tenant Model Management ⚙️
* Tenant-Scoped Model Keys: Model marketplace excludes custom models, model list properly isolates keys per tenant to prevent cross-tenant exposure", + "4. Robustness & Bug Fixes 🔧
* Knowledge Graph Construction Fix: Addressed stability issues in knowledge graph pipeline for more reliable entity extraction and relationship mapping", + "
", + "Version 0.2.5 matures MemoryBear's operational foundations by addressing internationalization edge cases, enhancing multi-tenant isolation, and improving workflow transparency. The workflow visualization improvements lay groundwork for sophisticated debugging and monitoring capabilities. Looking forward, we will deepen enterprise readiness by expanding user management features, refining knowledge graph intelligence, and enhancing workflow orchestration with continued improvements in observability, performance optimization, and seamless integration patterns.", + "Intelligent Resilience 🐻✨" + ] + } + }, "v0.2.4": { "introduction": { "codeName": "智远", From f38223c97fb0d33bfebce2a0abf0ad234c10bb1f Mon Sep 17 00:00:00 2001 From: Timebomb2018 <18868801967@163.com> Date: Fri, 27 Feb 2026 11:06:17 +0800 Subject: [PATCH 15/31] docs(version): Version 0.2.5 Release Notes --- api/app/version_info.json | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/api/app/version_info.json b/api/app/version_info.json index a4ff5d55..772ff56e 100644 --- a/api/app/version_info.json +++ b/api/app/version_info.json @@ -5,9 +5,9 @@ "releaseDate": "2026-2-26", "upgradePosition": "🐻 精炼根基，优化核心用户体验与系统稳定性", "coreUpgrades": [ - "1. 用户体验与国际化 🎨
* SSO 语言参数修复：解决 SSO 认证后添加 `?language=zh` 参数仍显示英文的问题，语言偏好现正确保留
* 邮箱修改支持：用户可直接在用户管理系统中修改邮箱地址", + "1. 用户体验与国际化 🎨
* 语言参数修复：语言偏好现正确保留
* 邮箱修改支持：用户可直接在用户管理系统中修改邮箱地址", "2. 工作流可视化增强 💬
* 循环与迭代节点输出展示：实时显示执行进度和中间输出，便于调试复杂迭代过程
* 变量支持回车选择：支持回车键确认变量选择，简化工作流配置流程", - "3. 多租户模型管理 ⚙️
* 租户隔离的模型密钥：模型广场排除自定义模型，模型列表按租户隔离密钥，防止跨租户密钥泄露", + "3. 优化模型管理 ⚙️
* 模型广场移除自定义模型，优化模型使用体验", "4. 稳健性与缺陷修复 🔧
* 知识图谱构建修复：解决知识图谱构建流程稳定性问题，确保更可靠的实体提取和关系映射", "
", "版本 0.2.5 通过解决国际化边界情况、增强多租户隔离和改进工作流透明度，构建更具生产就绪性的平台。工作流可视化改进为更复杂的调试和监控能力奠定基础。未来将继续深化企业就绪性，扩展用户管理功能、优化知识图谱智能和增强工作流编排能力，在可观测性、性能优化和无缝集成模式方面持续改进。", @@ -19,9 +19,9 @@ "releaseDate": "2026-2-26", "upgradePosition": "🐻 Refined foundations with enhanced user experience and system stability", "coreUpgrades": [ - "1. User Experience & Internationalization 🎨
* SSO Language Parameter Fix: Resolved issue where `?language=zh` parameter still showed English UI after SSO authentication
* Email Update Support: Users can now modify email addresses directly in user management system", + "1. User Experience & Internationalization 🎨
* Language parameter fix: language preferences are now correctly retained
* Email Update Support: Users can now modify email addresses directly in user management system", "2. Workflow Visualization Enhancements 💬
* Loop & Iteration Node Output Display: Real-time display of execution progress and intermediate outputs for easier debugging
* Variable Selection with Enter Key: Enabled Enter key confirmation for streamlined variable assignment", - "3. Multi-Tenant Model Management ⚙️
* Tenant-Scoped Model Keys: Model marketplace excludes custom models, model list properly isolates keys per tenant to prevent cross-tenant exposure", + "3. Optimized Model Management ⚙️
* Custom models have been removed from the Model marketplace to optimize the model usage experience", "4. Robustness & Bug Fixes 🔧
* Knowledge Graph Construction Fix: Addressed stability issues in knowledge graph pipeline for more reliable entity extraction and relationship mapping", "
", "Version 0.2.5 matures MemoryBear's operational foundations by addressing internationalization edge cases, enhancing multi-tenant isolation, and improving workflow transparency. The workflow visualization improvements lay groundwork for sophisticated debugging and monitoring capabilities. Looking forward, we will deepen enterprise readiness by expanding user management features, refining knowledge graph intelligence, and enhancing workflow orchestration with continued improvements in observability, performance optimization, and seamless integration patterns.", From 69af479224bb316e2ab8d2ba9af84253871efeac Mon Sep 17 00:00:00 2001 From: Timebomb2018 <18868801967@163.com> Date: Fri, 27 Feb 2026 11:16:15 +0800 Subject: [PATCH 16/31] docs(version): Version 0.2.5 Release Notes --- api/app/version_info.json | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/api/app/version_info.json b/api/app/version_info.json index 772ff56e..7d82eabc 100644 --- a/api/app/version_info.json +++ b/api/app/version_info.json @@ -10,7 +10,7 @@ "3. 优化模型管理 ⚙️
* 模型广场移除自定义模型，优化模型使用体验", "4. 稳健性与缺陷修复 🔧
* 知识图谱构建修复：解决知识图谱构建流程稳定性问题，确保更可靠的实体提取和关系映射", "
", - "版本 0.2.5 通过解决国际化边界情况、增强多租户隔离和改进工作流透明度，构建更具生产就绪性的平台。工作流可视化改进为更复杂的调试和监控能力奠定基础。未来将继续深化企业就绪性，扩展用户管理功能、优化知识图谱智能和增强工作流编排能力，在可观测性、性能优化和无缝集成模式方面持续改进。", + "版本 0.2.5 通过解决国际化边界情况和改进工作流透明度，构建更具生产就绪性的平台。工作流可视化改进为更复杂的调试和监控能力奠定基础。未来将继续深化企业就绪性，扩展用户管理功能、优化知识图谱智能和增强工作流编排能力，在可观测性、性能优化和无缝集成模式方面持续改进。", "智慧致远 🐻✨" ] }, @@ -24,7 +24,7 @@ "3. Optimized Model Management ⚙️
* Custom models have been removed from the Model marketplace to optimize the model usage experience", "4. Robustness & Bug Fixes 🔧
* Knowledge Graph Construction Fix: Addressed stability issues in knowledge graph pipeline for more reliable entity extraction and relationship mapping", "
", - "Version 0.2.5 matures MemoryBear's operational foundations by addressing internationalization edge cases, enhancing multi-tenant isolation, and improving workflow transparency. The workflow visualization improvements lay groundwork for sophisticated debugging and monitoring capabilities. Looking forward, we will deepen enterprise readiness by expanding user management features, refining knowledge graph intelligence, and enhancing workflow orchestration with continued improvements in observability, performance optimization, and seamless integration patterns.", + "Version 0.2.5 matures MemoryBear's operational foundations by addressing internationalization edge cases and improving workflow transparency. The workflow visualization improvements lay groundwork for sophisticated debugging and monitoring capabilities. Looking forward, we will deepen enterprise readiness by expanding user management features, refining knowledge graph intelligence, and enhancing workflow orchestration with continued improvements in observability, performance optimization, and seamless integration patterns.", "Intelligent Resilience 🐻✨" ] } From aef1a57ea8879b2086576ae8bc0589cbf35e3b2e Mon Sep 17 00:00:00 2001 From: Timebomb2018 <18868801967@163.com> Date: Fri, 27 Feb 2026 12:08:18 +0800 Subject: [PATCH 17/31] fix(user): The user changes the space and modifies the role, the role information is synchronized. --- api/app/controllers/user_controller.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/api/app/controllers/user_controller.py b/api/app/controllers/user_controller.py index 3c574c81..2806da1a 100644 --- a/api/app/controllers/user_controller.py +++ b/api/app/controllers/user_controller.py @@ -100,7 +100,7 @@ def get_current_user_info( result_schema.current_workspace_name = current_workspace.name for ws in result.workspaces: - if ws.workspace_id == current_user.current_workspace_id: + if ws.workspace_id == current_user.current_workspace_id and ws.is_active: result_schema.role = ws.role break From 37f77e099047046507f323b14fd8104c7e28f602 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Fri, 27 Feb 2026 18:48:02 +0800 Subject: [PATCH 18/31] fix(web): AutocompletePlugin key up/down support scroll --- .../Editor/plugin/AutocompletePlugin.tsx | 34 ++++++++++++++++--- 1 file changed, 30 insertions(+), 4 deletions(-) diff --git a/web/src/views/Workflow/components/Editor/plugin/AutocompletePlugin.tsx b/web/src/views/Workflow/components/Editor/plugin/AutocompletePlugin.tsx index 8e2687f1..f9fe097e 100644 --- a/web/src/views/Workflow/components/Editor/plugin/AutocompletePlugin.tsx +++ b/web/src/views/Workflow/components/Editor/plugin/AutocompletePlugin.tsx @@ -1,4 +1,4 @@ -import { useEffect, useState, type FC } from 'react'; +import { useEffect, useState, useRef, type FC } from 'react'; import { useLexicalComposerContext } from '@lexical/react/LexicalComposerContext'; import { $getSelection, $isRangeSelection, $isTextNode, COMMAND_PRIORITY_HIGH, KEY_ENTER_COMMAND, KEY_ARROW_DOWN_COMMAND, KEY_ARROW_UP_COMMAND, KEY_ESCAPE_COMMAND } from 'lexical'; @@ -22,6 +22,26 @@ const AutocompletePlugin: FC<{ options: Suggestion[], enableJinja2?: boolean }> const [showSuggestions, setShowSuggestions] = useState(false); const [selectedIndex, setSelectedIndex] = useState(0); const [popupPosition, setPopupPosition] = useState({ top: 0, left: 0 }); + const popupRef = useRef(null); + + const scrollSelectedIntoView = () => { + if (!popupRef.current) return; + + const selectedElement = popupRef.current.querySelector('[data-selected="true"]'); + if (!selectedElement) return; + + const container = popupRef.current; + const element = selectedElement as HTMLElement; + + const containerRect = container.getBoundingClientRect(); + const elementRect = element.getBoundingClientRect(); + + if (elementRect.bottom > containerRect.bottom) { + container.scrollTop += elementRect.bottom - containerRect.bottom; + } else if (elementRect.top < containerRect.top) { + container.scrollTop -= containerRect.top - elementRect.top; + } + }; useEffect(() => { return editor.registerUpdateListener(({ editorState }) => { @@ -116,7 +136,7 @@ const AutocompletePlugin: FC<{ options: Suggestion[], enableJinja2?: boolean }> setShowSuggestions(false); }; - const groupedSuggestions = options.reduce((groups: Record, suggestion) => { + const groupedSuggestions = options.reduce((groups: Record, suggestion) => { const { nodeData } = suggestion const nodeId = nodeData.id as string; if (!groups[nodeId]) { @@ -163,7 +183,9 @@ const AutocompletePlugin: FC<{ options: Suggestion[], enableJinja2?: boolean }> while (nextIndex < allOptions.length && allOptions[nextIndex].disabled) { nextIndex++; } - return nextIndex >= allOptions.length ? prev : nextIndex; + const newIndex = nextIndex >= allOptions.length ? prev : nextIndex; + setTimeout(() => scrollSelectedIntoView(), 0); + return newIndex; }); return true; } @@ -182,7 +204,9 @@ const AutocompletePlugin: FC<{ options: Suggestion[], enableJinja2?: boolean }> while (prevIndex >= 0 && allOptions[prevIndex].disabled) { prevIndex--; } - return prevIndex < 0 ? prev : prevIndex; + const newIndex = prevIndex < 0 ? prev : prevIndex; + setTimeout(() => scrollSelectedIntoView(), 0); + return newIndex; }); return true; } @@ -218,6 +242,7 @@ const AutocompletePlugin: FC<{ options: Suggestion[], enableJinja2?: boolean }> } return (
e.preventDefault()} style={{ @@ -248,6 +273,7 @@ const AutocompletePlugin: FC<{ options: Suggestion[], enableJinja2?: boolean }> return (
Date: Fri, 27 Feb 2026 18:59:58 +0800 Subject: [PATCH 19/31] feat(web): create space storage type add recommend --- web/src/components/RadioGroupCard/index.tsx | 7 ++++++- web/src/i18n/en.ts | 1 + web/src/i18n/zh.ts | 1 + web/src/views/SpaceManagement/components/SpaceModal.tsx | 8 ++++++-- 4 files changed, 14 insertions(+), 3 deletions(-) diff --git a/web/src/components/RadioGroupCard/index.tsx b/web/src/components/RadioGroupCard/index.tsx index 41924c61..e09466cd 100644 --- a/web/src/components/RadioGroupCard/index.tsx +++ b/web/src/components/RadioGroupCard/index.tsx @@ -20,6 +20,7 @@ import { type FC, type Key, type ReactNode, useEffect } from 'react'; import { type RadioGroupProps } from 'antd'; import clsx from 'clsx' +import { useTranslation } from 'react-i18next'; /** Radio card option interface */ interface RadioCardOption { @@ -33,6 +34,8 @@ interface RadioCardOption { icon?: string; /** Whether the option is disabled */ disabled?: boolean; + /** Whether the option is recommended */ + recommend?: boolean; /** Additional properties */ [key: string]: string | number | boolean | undefined | null | Key; } @@ -63,6 +66,7 @@ const RadioGroupCard: FC = ({ allowClear = true, block = false, }) => { + const { t } = useTranslation(); /** Listen to value changes and trigger side effects via onValueChange callback */ useEffect(() => { if (onValueChange) { @@ -91,12 +95,13 @@ const RadioGroupCard: FC = ({ })}> {/* Render each option as a selectable card */} {options.map(option => ( -
handleChange(option)}> + {option.recommend &&
{t('common.recommend')}
} {/* Use custom render or default card layout */} {itemRender ? itemRender(option) : ( <> diff --git a/web/src/i18n/en.ts b/web/src/i18n/en.ts index 8dfb68db..f2b4eaa4 100644 --- a/web/src/i18n/en.ts +++ b/web/src/i18n/en.ts @@ -452,6 +452,7 @@ export const en = { nextStep: 'Next Step', prevStep: 'Previous Step', exportSuccess: 'Export successful', + recommend: 'Recommend', }, model: { searchPlaceholder: 'search model…', diff --git a/web/src/i18n/zh.ts b/web/src/i18n/zh.ts index feefc843..e2e7082a 100644 --- a/web/src/i18n/zh.ts +++ b/web/src/i18n/zh.ts @@ -1019,6 +1019,7 @@ export const zh = { nextStep: '下一步', prevStep: '上一步', exportSuccess: '导出成功', + recommend: '推荐', }, model: { searchPlaceholder: '搜索模型…', diff --git a/web/src/views/SpaceManagement/components/SpaceModal.tsx b/web/src/views/SpaceManagement/components/SpaceModal.tsx index a0703d81..4f37b246 100644 --- a/web/src/views/SpaceManagement/components/SpaceModal.tsx +++ b/web/src/views/SpaceManagement/components/SpaceModal.tsx @@ -34,8 +34,8 @@ interface SpaceModalProps { } /** Storage types */ const types: StorageType[] = [ - 'rag', 'neo4j', + 'rag', ] /** Type icons mapping */ const typeIcons: Record = { @@ -154,6 +154,9 @@ const SpaceModal = forwardRef(({
(({ value: type, label: t(`space.${type}`), labelDesc: t(`space.${type}Desc`), - icon: typeIcons[type] + icon: typeIcons[type], + recommend: type === 'neo4j', }))} block={true} /> From dc9003f9dbc5cbf14af10a5d8d8907b0a022e596 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Sat, 28 Feb 2026 17:28:55 +0800 Subject: [PATCH 20/31] fix(web): model logo; BasicAuthLayout fix --- web/src/components/Layout/BasicAuthLayout.tsx | 10 +++++----- web/src/store/user.ts | 8 ++++---- .../ModelManagement/components/CustomModelModal.tsx | 6 +++--- 3 files changed, 12 insertions(+), 12 deletions(-) diff --git a/web/src/components/Layout/BasicAuthLayout.tsx b/web/src/components/Layout/BasicAuthLayout.tsx index a73f6c69..f279a48b 100644 --- a/web/src/components/Layout/BasicAuthLayout.tsx +++ b/web/src/components/Layout/BasicAuthLayout.tsx @@ -2,10 +2,10 @@ * @Author: ZhaoYing * @Date: 2026-02-02 15:12:42 * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-04 14:06:28 + * @Last Modified time: 2026-02-28 17:28:41 */ /** - * BasicLayout Component + * BasicAuthLayout Component * * A minimal layout wrapper that provides: * - User information initialization @@ -26,12 +26,12 @@ import { useUser } from '@/store/user'; * Basic layout component for pages without navigation UI. * Fetches user info and storage type on mount, then renders child routes. */ -const BasicLayout: FC = () => { +const BasicAuthLayout: FC = () => { const { getUserInfo } = useUser(); // Fetch user information and storage type on component mount useEffect(() => { - getUserInfo(); + getUserInfo(undefined, true); // Pass true to skip navigation jump }, [getUserInfo]); return ( @@ -42,4 +42,4 @@ const BasicLayout: FC = () => { ) }; -export default BasicLayout; \ No newline at end of file +export default BasicAuthLayout; \ No newline at end of file diff --git a/web/src/store/user.ts b/web/src/store/user.ts index c9231d9c..f5e0cb28 100644 --- a/web/src/store/user.ts +++ b/web/src/store/user.ts @@ -2,7 +2,7 @@ * @Author: ZhaoYing * @Date: 2026-02-02 16:33:54 * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-04 18:30:10 + * @Last Modified time: 2026-02-28 17:21:20 */ /** * User Store @@ -44,7 +44,7 @@ export interface UserState { /** Update login information */ updateLoginInfo: (values: LoginInfo) => void; /** Get user information */ - getUserInfo: (flag?: boolean) => void; + getUserInfo: (flag?: boolean, notNeedJump?: boolean) => void; /** Clear user information */ clearUserInfo: () => void; /** Logout user */ @@ -73,13 +73,13 @@ export const useUser = create((set, get) => ({ cookieUtils.set('refreshToken', values.refresh_token); set({ loginInfo: values }); }, - getUserInfo: async (flag?: boolean) => { + getUserInfo: async (flag?: boolean, notNeedJump?: boolean) => { if (!cookieUtils.get('authToken')) { return } const { checkJump } = get() const localUser = JSON.parse(localStorage.getItem('user') || '{}') as User; - if (localUser.id) { + if (localUser.id && !notNeedJump) { checkJump() return } diff --git a/web/src/views/ModelManagement/components/CustomModelModal.tsx b/web/src/views/ModelManagement/components/CustomModelModal.tsx index fb0db96e..17373a02 100644 --- a/web/src/views/ModelManagement/components/CustomModelModal.tsx +++ b/web/src/views/ModelManagement/components/CustomModelModal.tsx @@ -1,8 +1,8 @@ /* * @Author: ZhaoYing * @Date: 2026-02-03 16:49:28 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-03 16:49:28 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-02-28 17:24:05 */ /** * Custom Model Modal @@ -50,7 +50,7 @@ const CustomModelModal = forwardRef( setModel(model); form.setFieldsValue({ ...model, - logo: model.logo ? { url: model.logo, uid: model.logo, status: 'done', name: 'logo' } : undefined + logo: model.logo && model.logo.startsWith('http') ? { url: model.logo, uid: model.logo, status: 'done', name: 'logo' } : undefined }); } else { setIsEdit(false); From f5185d2e95f036754cc32d4a03f87443d1169def Mon Sep 17 00:00:00 2001 From: zhaoying Date: Tue, 10 Feb 2026 17:42:40 +0800 Subject: [PATCH 21/31] fix(web): FileUpload bugfix --- web/src/views/Conversation/components/FileUpload.tsx | 1 + web/src/views/Workflow/components/Chat/Chat.tsx | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/web/src/views/Conversation/components/FileUpload.tsx b/web/src/views/Conversation/components/FileUpload.tsx index 70ee9cf2..f41fff3c 100644 --- a/web/src/views/Conversation/components/FileUpload.tsx +++ b/web/src/views/Conversation/components/FileUpload.tsx @@ -2,6 +2,7 @@ * @Author: ZhaoYing * @Date: 2026-02-06 21:09:42 * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-02-10 17:40:08 * @Last Modified time: 2026-02-11 11:32:48 */ /** diff --git a/web/src/views/Workflow/components/Chat/Chat.tsx b/web/src/views/Workflow/components/Chat/Chat.tsx index 895ade24..aa30fc57 100644 --- a/web/src/views/Workflow/components/Chat/Chat.tsx +++ b/web/src/views/Workflow/components/Chat/Chat.tsx @@ -2,7 +2,7 @@ * @Author: ZhaoYing * @Date: 2026-02-06 21:10:56 * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-27 09:58:30 + * @Last Modified time: 2026-02-10 17:41:24 */ /** * Workflow Chat Component From e00341a4cca3e8df14cc7a8b2525c36a35789ab0 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Wed, 11 Feb 2026 11:34:20 +0800 Subject: [PATCH 22/31] fix(web): file upload bugfix --- web/src/views/Conversation/components/FileUpload.tsx | 1 - 1 file changed, 1 deletion(-) diff --git a/web/src/views/Conversation/components/FileUpload.tsx b/web/src/views/Conversation/components/FileUpload.tsx index f41fff3c..70ee9cf2 100644 --- a/web/src/views/Conversation/components/FileUpload.tsx +++ b/web/src/views/Conversation/components/FileUpload.tsx @@ -2,7 +2,6 @@ * @Author: ZhaoYing * @Date: 2026-02-06 21:09:42 * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-10 17:40:08 * @Last Modified time: 2026-02-11 11:32:48 */ /** From 1524d7b5ce9d5c639fa4cee9996b9d4583daf1d4 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Tue, 3 Mar 2026 15:09:16 +0800 Subject: [PATCH 23/31] fix(web): Implicit detail add check data api --- web/src/api/memory.ts | 9 +++++++-- web/src/i18n/en.ts | 3 ++- web/src/i18n/zh.ts | 3 ++- .../UserMemoryDetail/pages/ImplicitDetail.tsx | 16 ++++++++++++++-- 4 files changed, 25 insertions(+), 6 deletions(-) diff --git a/web/src/api/memory.ts b/web/src/api/memory.ts index 987ef358..cb917ec1 100644 --- a/web/src/api/memory.ts +++ b/web/src/api/memory.ts @@ -1,8 +1,8 @@ /* * @Author: ZhaoYing * @Date: 2026-02-03 14:00:06 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-03 14:00:06 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-03-03 14:58:32 */ import { request } from '@/utils/request' import type { @@ -163,9 +163,14 @@ export const getImplicitInterestAreas = (end_user_id: string) => { export const getImplicitHabits = (end_user_id: string) => { return request.get(`/memory/implicit-memory/habits/${end_user_id}`) } +// Implicit Memory - Generate user portrait export const generateProfile = (end_user_id: string) => { return request.post(`/memory/implicit-memory/generate_profile`, { end_user_id }) } +// Implicit Memory - Check if data exists +export const implicitCheckData = (end_user_id: string) => { + return request.get(`/memory/implicit-memory/check-data/${end_user_id}`) +} // Short-term memory export const getShortTerm = (end_user_id: string) => { return request.get(`/memory/short/short_term`, { end_user_id }) diff --git a/web/src/i18n/en.ts b/web/src/i18n/en.ts index f2b4eaa4..b17ad291 100644 --- a/web/src/i18n/en.ts +++ b/web/src/i18n/en.ts @@ -2522,7 +2522,8 @@ Memory Bear: After the rebellion, regional warlordism intensified for several re context_details: 'Preference Details', supporting_evidence: 'Preference Source', specific_examples: 'Source', - wordEmpty: 'Click on a node in the left chart to view preference details' + wordEmpty: 'Click on a node in the left chart to view preference details', + noData: 'Portrait data does not exist, please click the refresh button in the top right corner to initialize', }, shortTermDetail: { title: 'Short-term memory is the "workbench" of the AI system, connecting instant conversations with long-term knowledge bases. Through real-time capture, deep retrieval, intelligent extraction and filtering transformation, temporary unstructured information is converted into valuable long-term knowledge.', diff --git a/web/src/i18n/zh.ts b/web/src/i18n/zh.ts index e2e7082a..181173ff 100644 --- a/web/src/i18n/zh.ts +++ b/web/src/i18n/zh.ts @@ -2518,7 +2518,8 @@ export const zh = { context_details: '偏好详情', supporting_evidence: '偏好来源', specific_examples: '来源', - wordEmpty: '点击左侧图表中的节点查看偏好详情' + wordEmpty: '点击左侧图表中的节点查看偏好详情', + noData: '画像数据不存在，请点击右上角刷新进行初始化', }, shortTermDetail: { title: '短期记忆是AI系统的"工作台"，连接即时对话与长期知识库。通过实时捕获、深度检索、智能提取和筛选转化，将临时的非结构化信息转化为有价值的长期知识。', diff --git a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx index dfe5c1ee..351e5ed1 100644 --- a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx @@ -1,6 +1,6 @@ -import { forwardRef, useImperativeHandle, useRef } from 'react' +import { forwardRef, useImperativeHandle, useRef, useEffect } from 'react' import { useTranslation } from 'react-i18next' -import { Row, Col } from 'antd' +import { Row, Col, App } from 'antd' import { useParams } from 'react-router-dom' import Preferences from '../components/Preferences' @@ -9,15 +9,27 @@ import InterestAreas from '../components/InterestAreas' import Habits from '../components/Habits' import { generateProfile, + implicitCheckData, } from '@/api/memory' const ImplicitDetail = forwardRef<{ handleRefresh: () => void; }>((_props, ref) => { const { t } = useTranslation() const { id } = useParams() + const { message } = App.useApp() const preferencesRef = useRef<{ handleRefresh: () => void; }>(null) const portraitRef = useRef<{ handleRefresh: () => void; }>(null) const interestAreasRef = useRef<{ handleRefresh: () => void; }>(null) const habitsRef = useRef<{ handleRefresh: () => void; }>(null) + + useEffect(() => { + if (!id) return + implicitCheckData(id) + .then(res => { + if (!(res as { exists: boolean }).exists) { + message.warning(t('implicitDetail.noData')) + } + }) + }, [id]) const handleRefresh = () => { if (!id) { From 6033d37537b595a904f03af19cdbe814c3dd4db4 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 15:33:17 +0800 Subject: [PATCH 24/31] [changes] Implicit and emotional memories are stored in a database. --- api/app/cache/memory/emotion_memory.py | 134 ----------- api/app/cache/memory/implicit_memory.py | 136 ----------- api/app/celery_app.py | 7 + api/app/controllers/emotion_controller.py | 114 ++++++---- .../controllers/implicit_memory_controller.py | 59 ++++- api/app/models/__init__.py | 4 +- .../models/implicit_emotions_storage_model.py | 46 ++++ .../implicit_emotions_storage_repository.py | 169 ++++++++++++++ api/app/services/emotion_analytics_service.py | 58 +++-- api/app/services/implicit_memory_service.py | 58 +++-- api/app/tasks.py | 211 +++++++++++++++++- 11 files changed, 603 insertions(+), 393 deletions(-) delete mode 100644 api/app/cache/memory/emotion_memory.py delete mode 100644 api/app/cache/memory/implicit_memory.py create mode 100644 api/app/models/implicit_emotions_storage_model.py create mode 100644 api/app/repositories/implicit_emotions_storage_repository.py diff --git a/api/app/cache/memory/emotion_memory.py b/api/app/cache/memory/emotion_memory.py deleted file mode 100644 index 45ea90de..00000000 --- a/api/app/cache/memory/emotion_memory.py +++ /dev/null @@ -1,134 +0,0 @@ -""" -Emotion Suggestions Cache - -情绪个性化建议缓存模块 -用于缓存用户的情绪个性化建议数据 -""" -import json -import logging -from typing import Optional, Dict, Any -from datetime import datetime - -from app.aioRedis import aio_redis - -logger = logging.getLogger(__name__) - - -class EmotionMemoryCache: - """情绪建议缓存类""" - - # Key 前缀 - PREFIX = "cache:memory:emotion_memory" - - @classmethod - def _get_key(cls, *parts: str) -> str: - """生成 Redis key - - Args: - *parts: key 的各个部分 - - Returns: - 完整的 Redis key - """ - return ":".join([cls.PREFIX] + list(parts)) - - @classmethod - async def set_emotion_suggestions( - cls, - user_id: str, - suggestions_data: Dict[str, Any], - expire: int = 86400 - ) -> bool: - """设置用户情绪建议缓存 - - Args: - user_id: 用户ID（end_user_id） - suggestions_data: 建议数据字典，包含： - - health_summary: 健康状态摘要 - - suggestions: 建议列表 - - generated_at: 生成时间（可选） - expire: 过期时间（秒），默认24小时（86400秒） - - Returns: - 是否设置成功 - """ - try: - key = cls._get_key("suggestions", user_id) - - # 添加生成时间戳 - if "generated_at" not in suggestions_data: - suggestions_data["generated_at"] = datetime.now().isoformat() - - # 添加缓存标记 - suggestions_data["cached"] = True - - value = json.dumps(suggestions_data, ensure_ascii=False) - await aio_redis.set(key, value, ex=expire) - logger.info(f"设置情绪建议缓存成功: {key}, 过期时间: {expire}秒") - return True - except Exception as e: - logger.error(f"设置情绪建议缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_emotion_suggestions(cls, user_id: str) -> Optional[Dict[str, Any]]: - """获取用户情绪建议缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 建议数据字典，如果不存在或已过期返回 None - """ - try: - key = cls._get_key("suggestions", user_id) - value = await aio_redis.get(key) - - if value: - data = json.loads(value) - logger.info(f"成功获取情绪建议缓存: {key}") - return data - - logger.info(f"情绪建议缓存不存在或已过期: {key}") - return None - except Exception as e: - logger.error(f"获取情绪建议缓存失败: {e}", exc_info=True) - return None - - @classmethod - async def delete_emotion_suggestions(cls, user_id: str) -> bool: - """删除用户情绪建议缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 是否删除成功 - """ - try: - key = cls._get_key("suggestions", user_id) - result = await aio_redis.delete(key) - logger.info(f"删除情绪建议缓存: {key}, 结果: {result}") - return result > 0 - except Exception as e: - logger.error(f"删除情绪建议缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_suggestions_ttl(cls, user_id: str) -> int: - """获取情绪建议缓存的剩余过期时间 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 剩余秒数，-1表示永不过期，-2表示key不存在 - """ - try: - key = cls._get_key("suggestions", user_id) - ttl = await aio_redis.ttl(key) - logger.debug(f"情绪建议缓存TTL: {key} = {ttl}秒") - return ttl - except Exception as e: - logger.error(f"获取情绪建议缓存TTL失败: {e}") - return -2 diff --git a/api/app/cache/memory/implicit_memory.py b/api/app/cache/memory/implicit_memory.py deleted file mode 100644 index 21f08e9a..00000000 --- a/api/app/cache/memory/implicit_memory.py +++ /dev/null @@ -1,136 +0,0 @@ -""" -Implicit Memory Profile Cache - -隐式记忆用户画像缓存模块 -用于缓存用户的完整画像数据（偏好标签、四维画像、兴趣领域、行为习惯） -""" -import json -import logging -from typing import Optional, Dict, Any -from datetime import datetime - -from app.aioRedis import aio_redis - -logger = logging.getLogger(__name__) - - -class ImplicitMemoryCache: - """隐式记忆用户画像缓存类""" - - # Key 前缀 - PREFIX = "cache:memory:implicit_memory" - - @classmethod - def _get_key(cls, *parts: str) -> str: - """生成 Redis key - - Args: - *parts: key 的各个部分 - - Returns: - 完整的 Redis key - """ - return ":".join([cls.PREFIX] + list(parts)) - - @classmethod - async def set_user_profile( - cls, - user_id: str, - profile_data: Dict[str, Any], - expire: int = 86400 - ) -> bool: - """设置用户完整画像缓存 - - Args: - user_id: 用户ID（end_user_id） - profile_data: 画像数据字典，包含： - - preferences: 偏好标签列表 - - portrait: 四维画像对象 - - interest_areas: 兴趣领域分布对象 - - habits: 行为习惯列表 - - generated_at: 生成时间（可选） - expire: 过期时间（秒），默认24小时（86400秒） - - Returns: - 是否设置成功 - """ - try: - key = cls._get_key("profile", user_id) - - # 添加生成时间戳 - if "generated_at" not in profile_data: - profile_data["generated_at"] = datetime.now().isoformat() - - # 添加缓存标记 - profile_data["cached"] = True - - value = json.dumps(profile_data, ensure_ascii=False) - await aio_redis.set(key, value, ex=expire) - logger.info(f"设置用户画像缓存成功: {key}, 过期时间: {expire}秒") - return True - except Exception as e: - logger.error(f"设置用户画像缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_user_profile(cls, user_id: str) -> Optional[Dict[str, Any]]: - """获取用户完整画像缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 画像数据字典，如果不存在或已过期返回 None - """ - try: - key = cls._get_key("profile", user_id) - value = await aio_redis.get(key) - - if value: - data = json.loads(value) - logger.info(f"成功获取用户画像缓存: {key}") - return data - - logger.info(f"用户画像缓存不存在或已过期: {key}") - return None - except Exception as e: - logger.error(f"获取用户画像缓存失败: {e}", exc_info=True) - return None - - @classmethod - async def delete_user_profile(cls, user_id: str) -> bool: - """删除用户完整画像缓存 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 是否删除成功 - """ - try: - key = cls._get_key("profile", user_id) - result = await aio_redis.delete(key) - logger.info(f"删除用户画像缓存: {key}, 结果: {result}") - return result > 0 - except Exception as e: - logger.error(f"删除用户画像缓存失败: {e}", exc_info=True) - return False - - @classmethod - async def get_profile_ttl(cls, user_id: str) -> int: - """获取用户画像缓存的剩余过期时间 - - Args: - user_id: 用户ID（end_user_id） - - Returns: - 剩余秒数，-1表示永不过期，-2表示key不存在 - """ - try: - key = cls._get_key("profile", user_id) - ttl = await aio_redis.ttl(key) - logger.debug(f"用户画像缓存TTL: {key} = {ttl}秒") - return ttl - except Exception as e: - logger.error(f"获取用户画像缓存TTL失败: {e}") - return -2 diff --git a/api/app/celery_app.py b/api/app/celery_app.py index f422f4a0..33fa1703 100644 --- a/api/app/celery_app.py +++ b/api/app/celery_app.py @@ -83,6 +83,7 @@ celery_app.conf.update( 'app.tasks.regenerate_memory_cache': {'queue': 'periodic_tasks'}, 'app.tasks.run_forgetting_cycle_task': {'queue': 'periodic_tasks'}, 'app.tasks.write_all_workspaces_memory_task': {'queue': 'periodic_tasks'}, + 'app.tasks.update_implicit_emotions_storage': {'queue': 'periodic_tasks'}, }, ) @@ -95,6 +96,7 @@ memory_cache_regeneration_schedule = timedelta(hours=settings.MEMORY_CACHE_REGEN # 这个30秒的设计不合理 workspace_reflection_schedule = timedelta(seconds=30) # 每30秒运行一次settings.REFLECTION_INTERVAL_TIME forgetting_cycle_schedule = timedelta(hours=24) # 每24小时运行一次遗忘周期 +implicit_emotions_update_schedule = timedelta(hours=24) # 每24小时更新一次隐性记忆和情绪数据 #构建定时任务配置 beat_schedule_config = { @@ -120,6 +122,11 @@ beat_schedule_config = { "schedule": memory_increment_schedule, "args": (), }, + "update-implicit-emotions-storage": { + "task": "app.tasks.update_implicit_emotions_storage", + "schedule": implicit_emotions_update_schedule, + "args": (), + }, } celery_app.conf.beat_schedule = beat_schedule_config diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index eb2436d2..02ce7862 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -208,6 +208,57 @@ async def get_emotion_health( +@router.post("/check-data", response_model=ApiResponse) +async def check_emotion_data_exists( + request: EmotionSuggestionsRequest, + db: Session = Depends(get_db), + current_user: User = Depends(get_current_user), +): + """检查用户情绪建议数据是否存在 + + Args: + request: 包含 end_user_id + db: 数据库会话 + current_user: 当前用户 + + Returns: + 数据存在状态 + """ + try: + api_logger.info( + f"检查用户情绪建议数据是否存在: {request.end_user_id}", + extra={"end_user_id": request.end_user_id} + ) + + # 从数据库获取建议 + data = await emotion_service.get_cached_suggestions( + end_user_id=request.end_user_id, + db=db + ) + + if data is None: + api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据不存在") + return fail( + BizCode.NOT_FOUND, + "情绪建议数据不存在，请点击右上角刷新进行初始化", + {"exists": False} + ) + + api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据存在") + return success(data={"exists": True}, msg="情绪建议数据已存在") + + except Exception as e: + api_logger.error( + f"检查情绪建议数据失败: {str(e)}", + extra={"end_user_id": request.end_user_id}, + exc_info=True + ) + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail=f"检查情绪建议数据失败: {str(e)}" + ) + + @router.post("/suggestions", response_model=ApiResponse) async def get_emotion_suggestions( request: EmotionSuggestionsRequest, @@ -215,7 +266,7 @@ async def get_emotion_suggestions( db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): - """获取个性化情绪建议（从缓存读取） + """获取个性化情绪建议（从数据库读取） Args: request: 包含 end_user_id 和可选的 config_id @@ -223,77 +274,47 @@ async def get_emotion_suggestions( current_user: 当前用户 Returns: - 缓存的个性化情绪建议响应 + 存储的个性化情绪建议响应 """ try: # 使用集中化的语言校验 language = get_language_from_header(language_type) api_logger.info( - f"用户 {current_user.username} 请求获取个性化情绪建议（缓存）", + f"用户 {current_user.username} 请求获取个性化情绪建议", extra={ "end_user_id": request.end_user_id, "config_id": request.config_id } ) - # 从缓存获取建议 + # 从数据库获取建议 data = await emotion_service.get_cached_suggestions( end_user_id=request.end_user_id, db=db ) if data is None: - # 缓存不存在或已过期，自动触发生成 + # 数据不存在，返回提示信息 api_logger.info( - f"用户 {request.end_user_id} 的建议缓存不存在或已过期，自动生成新建议", + f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - try: - data = await emotion_service.generate_emotion_suggestions( - end_user_id=request.end_user_id, - db=db, - language=language - ) - # 保存到缓存 - await emotion_service.save_suggestions_cache( - end_user_id=request.end_user_id, - suggestions_data=data, - db=db, - expires_hours=24 - ) - except (ValueError, KeyError) as gen_e: - # 预期内的业务异常：配置缺失、数据格式问题等 - api_logger.warning( - f"自动生成建议失败（业务异常）: {str(gen_e)}", - extra={"end_user_id": request.end_user_id} - ) - return fail( - BizCode.NOT_FOUND, - f"自动生成建议失败: {str(gen_e)}", - "" - ) - except Exception as gen_e: - # 非预期异常：记录完整 traceback 便于排查 - api_logger.error( - f"自动生成建议时发生未预期异常: {str(gen_e)}", - extra={"end_user_id": request.end_user_id}, - exc_info=True - ) - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail=f"生成建议时发生内部错误: {str(gen_e)}" - ) + return fail( + BizCode.NOT_FOUND, + "情绪建议数据不存在，请点击右上角刷新进行初始化", + "" + ) api_logger.info( - "个性化建议获取成功（缓存）", + "个性化建议获取成功", extra={ "end_user_id": request.end_user_id, "suggestions_count": len(data.get("suggestions", [])) } ) - return success(data=data, msg="个性化建议获取成功（缓存）") + return success(data=data, msg="个性化建议获取成功") except Exception as e: api_logger.error( @@ -314,7 +335,7 @@ async def generate_emotion_suggestions( db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): - """生成个性化情绪建议（调用LLM并缓存） + """生成个性化情绪建议（调用LLM并保存到数据库） Args: request: 包含 end_user_id @@ -342,12 +363,11 @@ async def generate_emotion_suggestions( language=language ) - # 保存到缓存 + # 保存到数据库 await emotion_service.save_suggestions_cache( end_user_id=request.end_user_id, suggestions_data=data, - db=db, - expires_hours=24 + db=db ) api_logger.info( diff --git a/api/app/controllers/implicit_memory_controller.py b/api/app/controllers/implicit_memory_controller.py index 96e437d6..91e634c9 100644 --- a/api/app/controllers/implicit_memory_controller.py +++ b/api/app/controllers/implicit_memory_controller.py @@ -122,6 +122,49 @@ def validate_confidence_threshold(threshold: float) -> None: raise ValueError("confidence_threshold must be between 0.0 and 1.0") +@router.get("/check-data/{end_user_id}", response_model=ApiResponse) +@cur_workspace_access_guard() +async def check_user_data_exists( + end_user_id: str, + db: Session = Depends(get_db), + current_user: User = Depends(get_current_user) +) -> ApiResponse: + """ + 检查用户画像数据是否存在 + + Args: + end_user_id: 目标用户ID + + Returns: + 数据存在状态 + """ + api_logger.info(f"检查用户画像数据是否存在: {end_user_id}") + + try: + # Validate inputs + validate_user_id(end_user_id) + + # Create service with user-specific config + service = ImplicitMemoryService(db=db, end_user_id=end_user_id) + + # Get cached profile + cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) + + if cached_profile is None: + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") + return fail( + BizCode.NOT_FOUND, + "画像数据不存在，请点击右上角刷新进行初始化", + {"exists": False} + ) + + api_logger.info(f"用户 {end_user_id} 的画像数据存在") + return success(data={"exists": True}, msg="画像数据已存在") + + except Exception as e: + return handle_implicit_memory_error(e, "检查画像数据", end_user_id) + + @router.get("/preferences/{end_user_id}", response_model=ApiResponse) @cur_workspace_access_guard() async def get_preference_tags( @@ -159,10 +202,10 @@ async def get_preference_tags( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) @@ -230,10 +273,10 @@ async def get_dimension_portrait( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) @@ -278,10 +321,10 @@ async def get_interest_area_distribution( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) @@ -330,10 +373,10 @@ async def get_behavior_habits( cached_profile = await service.get_cached_profile(end_user_id=end_user_id, db=db) if cached_profile is None: - api_logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + api_logger.info(f"用户 {end_user_id} 的画像数据不存在") return fail( BizCode.NOT_FOUND, - "画像缓存不存在或已过期，请右上角刷新生成新画像", + "画像数据不存在，请点击右上角刷新进行初始化", "" ) diff --git a/api/app/models/__init__.py b/api/app/models/__init__.py index b1b723e9..c6098a6d 100644 --- a/api/app/models/__init__.py +++ b/api/app/models/__init__.py @@ -35,6 +35,7 @@ from .ontology_scene import OntologyScene from .ontology_class import OntologyClass from .ontology_scene import OntologyScene from .ontology_class import OntologyClass +from .implicit_emotions_storage_model import ImplicitEmotionsStorage __all__ = [ "Tenants", @@ -90,5 +91,6 @@ __all__ = [ "MemoryPerceptualModel", "ModelBase", "LoadBalanceStrategy", - "Skill" + "Skill", + "ImplicitEmotionsStorage" ] diff --git a/api/app/models/implicit_emotions_storage_model.py b/api/app/models/implicit_emotions_storage_model.py new file mode 100644 index 00000000..57c0fd61 --- /dev/null +++ b/api/app/models/implicit_emotions_storage_model.py @@ -0,0 +1,46 @@ +""" +Implicit Emotions Storage Model + +数据库模型：存储用户的隐性记忆画像和情绪建议数据 +替代原有的Redis缓存方式 +""" +import uuid +from datetime import datetime +from sqlalchemy import Column, String, Text, DateTime, Index +from sqlalchemy.dialects.postgresql import UUID, JSONB +from app.db import Base + + +class ImplicitEmotionsStorage(Base): + """隐性记忆和情绪存储表""" + + __tablename__ = "implicit_emotions_storage" + + # 主键 + id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, comment="主键ID") + + # 用户标识 + end_user_id = Column(String(255), nullable=False, unique=True, index=True, comment="终端用户ID") + + # 隐性记忆画像数据（JSON格式） + implicit_profile = Column(JSONB, nullable=True, comment="隐性记忆用户画像数据") + + # 情绪建议数据（JSON格式） + emotion_suggestions = Column(JSONB, nullable=True, comment="情绪个性化建议数据") + + # 时间戳 + created_at = Column(DateTime, nullable=False, default=datetime.utcnow, comment="创建时间") + updated_at = Column(DateTime, nullable=False, default=datetime.utcnow, onupdate=datetime.utcnow, comment="更新时间") + + # 数据生成时间（用于业务逻辑） + implicit_generated_at = Column(DateTime, nullable=True, comment="隐性记忆画像生成时间") + emotion_generated_at = Column(DateTime, nullable=True, comment="情绪建议生成时间") + + # 索引 + __table_args__ = ( + Index('idx_end_user_id', 'end_user_id'), + Index('idx_updated_at', 'updated_at'), + ) + + def __repr__(self): + return f"" diff --git a/api/app/repositories/implicit_emotions_storage_repository.py b/api/app/repositories/implicit_emotions_storage_repository.py new file mode 100644 index 00000000..fd4b10ce --- /dev/null +++ b/api/app/repositories/implicit_emotions_storage_repository.py @@ -0,0 +1,169 @@ +""" +Implicit Emotions Storage Repository + +数据访问层：处理隐性记忆和情绪数据的数据库操作 +""" +import logging +from datetime import datetime +from typing import Optional, List +from sqlalchemy.orm import Session +from sqlalchemy import select + +from app.models.implicit_emotions_storage_model import ImplicitEmotionsStorage + +logger = logging.getLogger(__name__) + + +class ImplicitEmotionsStorageRepository: + """隐性记忆和情绪存储仓储类""" + + def __init__(self, db: Session): + self.db = db + + def get_by_end_user_id(self, end_user_id: str) -> Optional[ImplicitEmotionsStorage]: + """根据终端用户ID获取存储记录 + + Args: + end_user_id: 终端用户ID + + Returns: + 存储记录，如果不存在返回None + """ + try: + stmt = select(ImplicitEmotionsStorage).where( + ImplicitEmotionsStorage.end_user_id == end_user_id + ) + result = self.db.execute(stmt).scalar_one_or_none() + return result + except Exception as e: + logger.error(f"获取用户存储记录失败: end_user_id={end_user_id}, error={e}") + return None + + def create(self, end_user_id: str) -> ImplicitEmotionsStorage: + """创建新的存储记录 + + Args: + end_user_id: 终端用户ID + + Returns: + 新创建的存储记录 + """ + try: + storage = ImplicitEmotionsStorage( + end_user_id=end_user_id, + created_at=datetime.utcnow(), + updated_at=datetime.utcnow() + ) + self.db.add(storage) + self.db.commit() + self.db.refresh(storage) + logger.info(f"创建用户存储记录成功: end_user_id={end_user_id}") + return storage + except Exception as e: + self.db.rollback() + logger.error(f"创建用户存储记录失败: end_user_id={end_user_id}, error={e}") + raise + + def update_implicit_profile( + self, + end_user_id: str, + profile_data: dict + ) -> Optional[ImplicitEmotionsStorage]: + """更新隐性记忆画像数据 + + Args: + end_user_id: 终端用户ID + profile_data: 画像数据 + + Returns: + 更新后的存储记录 + """ + try: + storage = self.get_by_end_user_id(end_user_id) + + if storage is None: + # 如果记录不存在，创建新记录 + storage = self.create(end_user_id) + + storage.implicit_profile = profile_data + storage.implicit_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.commit() + self.db.refresh(storage) + logger.info(f"更新隐性记忆画像成功: end_user_id={end_user_id}") + return storage + except Exception as e: + self.db.rollback() + logger.error(f"更新隐性记忆画像失败: end_user_id={end_user_id}, error={e}") + raise + + def update_emotion_suggestions( + self, + end_user_id: str, + suggestions_data: dict + ) -> Optional[ImplicitEmotionsStorage]: + """更新情绪建议数据 + + Args: + end_user_id: 终端用户ID + suggestions_data: 建议数据 + + Returns: + 更新后的存储记录 + """ + try: + storage = self.get_by_end_user_id(end_user_id) + + if storage is None: + # 如果记录不存在，创建新记录 + storage = self.create(end_user_id) + + storage.emotion_suggestions = suggestions_data + storage.emotion_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.commit() + self.db.refresh(storage) + logger.info(f"更新情绪建议成功: end_user_id={end_user_id}") + return storage + except Exception as e: + self.db.rollback() + logger.error(f"更新情绪建议失败: end_user_id={end_user_id}, error={e}") + raise + + def get_all_user_ids(self) -> List[str]: + """获取所有已存储数据的用户ID列表 + + Returns: + 用户ID列表 + """ + try: + stmt = select(ImplicitEmotionsStorage.end_user_id) + result = self.db.execute(stmt).scalars().all() + return list(result) + except Exception as e: + logger.error(f"获取所有用户ID失败: error={e}") + return [] + + def delete_by_end_user_id(self, end_user_id: str) -> bool: + """删除用户的存储记录 + + Args: + end_user_id: 终端用户ID + + Returns: + 是否删除成功 + """ + try: + storage = self.get_by_end_user_id(end_user_id) + if storage: + self.db.delete(storage) + self.db.commit() + logger.info(f"删除用户存储记录成功: end_user_id={end_user_id}") + return True + return False + except Exception as e: + self.db.rollback() + logger.error(f"删除用户存储记录失败: end_user_id={end_user_id}, error={e}") + return False diff --git a/api/app/services/emotion_analytics_service.py b/api/app/services/emotion_analytics_service.py index 89e3cab9..099cbfb7 100644 --- a/api/app/services/emotion_analytics_service.py +++ b/api/app/services/emotion_analytics_service.py @@ -843,32 +843,33 @@ class EmotionAnalyticsService: end_user_id: str, db: Session, ) -> Optional[Dict[str, Any]]: - """从 Redis 缓存获取个性化情绪建议 + """从数据库获取个性化情绪建议 Args: end_user_id: 宿主ID（用户组ID） - db: 数据库会话（保留参数以保持接口兼容性） + db: 数据库会话 Returns: - Dict: 缓存的建议数据，如果不存在或已过期返回 None + Dict: 存储的建议数据，如果不存在返回 None """ try: - from app.cache.memory.emotion_memory import EmotionMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"尝试从 Redis 缓存获取情绪建议: user={end_user_id}") + logger.info(f"尝试从数据库获取情绪建议: user={end_user_id}") - # 从 Redis 获取缓存 - cached_data = await EmotionMemoryCache.get_emotion_suggestions(end_user_id) + # 从数据库获取存储记录 + repo = ImplicitEmotionsStorageRepository(db) + storage = repo.get_by_end_user_id(end_user_id) - if cached_data is None: - logger.info(f"用户 {end_user_id} 的建议缓存不存在或已过期") + if storage is None or storage.emotion_suggestions is None: + logger.info(f"用户 {end_user_id} 的建议数据不存在") return None - logger.info(f"成功从 Redis 缓存获取建议: user={end_user_id}") - return cached_data + logger.info(f"成功从数据库获取建议: user={end_user_id}") + return storage.emotion_suggestions except Exception as e: - logger.error(f"从 Redis 缓存获取建议失败: {str(e)}", exc_info=True) + logger.error(f"从数据库获取建议失败: {str(e)}", exc_info=True) return None async def save_suggestions_cache( @@ -876,36 +877,27 @@ class EmotionAnalyticsService: end_user_id: str, suggestions_data: Dict[str, Any], db: Session, - expires_hours: int = 24 + expires_hours: int = 24 # 参数保留以保持接口兼容性 ) -> None: - """保存建议到 Redis 缓存 + """保存建议到数据库 Args: end_user_id: 宿主ID（用户组ID） suggestions_data: 建议数据 - db: 数据库会话（保留参数以保持接口兼容性） - expires_hours: 过期时间（小时），默认24小时 + db: 数据库会话 + expires_hours: 保留参数（兼容性） """ try: - from app.cache.memory.emotion_memory import EmotionMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"保存建议到 Redis 缓存: user={end_user_id}, expires={expires_hours}小时") + logger.info(f"保存建议到数据库: user={end_user_id}") - # 计算过期时间（秒） - expire_seconds = expires_hours * 3600 + # 保存到数据库 + repo = ImplicitEmotionsStorageRepository(db) + repo.update_emotion_suggestions(end_user_id, suggestions_data) - # 保存到 Redis - success = await EmotionMemoryCache.set_emotion_suggestions( - user_id=end_user_id, - suggestions_data=suggestions_data, - expire=expire_seconds - ) - - if success: - logger.info(f"建议缓存保存成功: user={end_user_id}") - else: - logger.warning(f"建议缓存保存失败: user={end_user_id}") + logger.info(f"建议保存成功: user={end_user_id}") except Exception as e: - logger.error(f"保存建议缓存失败: {str(e)}", exc_info=True) - # 不抛出异常，缓存失败不应影响主流程 \ No newline at end of file + logger.error(f"保存建议失败: {str(e)}", exc_info=True) + # 不抛出异常，存储失败不应影响主流程 \ No newline at end of file diff --git a/api/app/services/implicit_memory_service.py b/api/app/services/implicit_memory_service.py index 34ebe880..534f138c 100644 --- a/api/app/services/implicit_memory_service.py +++ b/api/app/services/implicit_memory_service.py @@ -422,32 +422,33 @@ class ImplicitMemoryService: end_user_id: str, db: Session ) -> Optional[dict]: - """从 Redis 缓存获取完整用户画像 + """从数据库获取完整用户画像 Args: end_user_id: 终端用户ID - db: 数据库会话（保留参数以保持接口兼容性） + db: 数据库会话 Returns: - Dict: 缓存的画像数据，如果不存在或已过期返回 None + Dict: 存储的画像数据，如果不存在返回 None """ try: - from app.cache.memory.implicit_memory import ImplicitMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"尝试从 Redis 缓存获取用户画像: user={end_user_id}") + logger.info(f"尝试从数据库获取用户画像: user={end_user_id}") - # 从 Redis 获取缓存 - cached_data = await ImplicitMemoryCache.get_user_profile(end_user_id) + # 从数据库获取存储记录 + repo = ImplicitEmotionsStorageRepository(db) + storage = repo.get_by_end_user_id(end_user_id) - if cached_data is None: - logger.info(f"用户 {end_user_id} 的画像缓存不存在或已过期") + if storage is None or storage.implicit_profile is None: + logger.info(f"用户 {end_user_id} 的画像数据不存在") return None - logger.info(f"成功从 Redis 缓存获取用户画像: user={end_user_id}") - return cached_data + logger.info(f"成功从数据库获取用户画像: user={end_user_id}") + return storage.implicit_profile except Exception as e: - logger.error(f"从 Redis 缓存获取用户画像失败: {str(e)}", exc_info=True) + logger.error(f"从数据库获取用户画像失败: {str(e)}", exc_info=True) return None async def save_profile_cache( @@ -455,36 +456,27 @@ class ImplicitMemoryService: end_user_id: str, profile_data: dict, db: Session, - expires_hours: int = 168 # 默认7天 + expires_hours: int = 168 # 参数保留以保持接口兼容性 ) -> None: - """保存用户画像到 Redis 缓存 + """保存用户画像到数据库 Args: end_user_id: 终端用户ID profile_data: 画像数据 - db: 数据库会话（保留参数以保持接口兼容性） - expires_hours: 过期时间（小时），默认168小时（7天） + db: 数据库会话 + expires_hours: 保留参数（兼容性） """ try: - from app.cache.memory.implicit_memory import ImplicitMemoryCache + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository - logger.info(f"保存用户画像到 Redis 缓存: user={end_user_id}, expires={expires_hours}小时") + logger.info(f"保存用户画像到数据库: user={end_user_id}") - # 计算过期时间（秒） - expire_seconds = expires_hours * 3600 + # 保存到数据库 + repo = ImplicitEmotionsStorageRepository(db) + repo.update_implicit_profile(end_user_id, profile_data) - # 保存到 Redis - success = await ImplicitMemoryCache.set_user_profile( - user_id=end_user_id, - profile_data=profile_data, - expire=expire_seconds - ) - - if success: - logger.info(f"用户画像缓存保存成功: user={end_user_id}") - else: - logger.warning(f"用户画像缓存保存失败: user={end_user_id}") + logger.info(f"用户画像保存成功: user={end_user_id}") except Exception as e: - logger.error(f"保存用户画像缓存失败: {str(e)}", exc_info=True) - # 不抛出异常，缓存失败不应影响主流程 + logger.error(f"保存用户画像失败: {str(e)}", exc_info=True) + # 不抛出异常，存储失败不应影响主流程 diff --git a/api/app/tasks.py b/api/app/tasks.py index 8e3aea85..67498b85 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -2121,4 +2121,213 @@ def run_forgetting_cycle_task(self, config_id: Optional[uuid.UUID] = None) -> Di # "config_id": config_id, # "elapsed_time": elapsed_time, # "task_id": self.request.id -# } \ No newline at end of file +# } + + +# ============================================================================= +# 隐性记忆和情绪数据更新定时任务 +# ============================================================================= + +@celery_app.task( + name="app.tasks.update_implicit_emotions_storage", + bind=True, + ignore_result=True, + max_retries=0, + acks_late=False, + time_limit=7200, # 2小时硬超时 + soft_time_limit=6900, # 1小时55分钟软超时 +) +def update_implicit_emotions_storage(self) -> Dict[str, Any]: + """定时任务：更新所有用户的隐性记忆画像和情绪建议数据 + + 遍历数据库中所有已存在数据的用户，为每个用户重新生成隐性记忆画像和情绪建议。 + 实现错误隔离，单个用户失败不影响其他用户的处理。 + + Returns: + 包含任务执行结果的字典，包括： + - status: 任务状态 (SUCCESS/FAILURE) + - message: 执行消息 + - total_users: 总用户数 + - successful_implicit: 成功更新隐性记忆的用户数 + - successful_emotion: 成功更新情绪建议的用户数 + - failed: 失败的用户数 + - user_results: 每个用户的详细结果 + - elapsed_time: 执行耗时（秒） + - task_id: 任务ID + """ + start_time = time.time() + + async def _run() -> Dict[str, Any]: + from app.core.logging_config import get_logger + from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository + from app.services.implicit_memory_service import ImplicitMemoryService + from app.services.emotion_analytics_service import EmotionAnalyticsService + + logger = get_logger(__name__) + logger.info("开始执行隐性记忆和情绪数据更新定时任务") + + total_users = 0 + successful_implicit = 0 + successful_emotion = 0 + failed = 0 + user_results = [] + + with get_db_context() as db: + try: + # 获取所有已存储数据的用户ID + repo = ImplicitEmotionsStorageRepository(db) + user_ids = repo.get_all_user_ids() + total_users = len(user_ids) + + logger.info(f"找到 {total_users} 个需要更新的用户") + + # 遍历每个用户并更新数据 + for end_user_id in user_ids: + logger.info(f"开始处理用户: {end_user_id}") + user_start_time = time.time() + + implicit_success = False + emotion_success = False + errors = [] + + try: + # 更新隐性记忆画像 + try: + implicit_service = ImplicitMemoryService(db=db, end_user_id=end_user_id) + profile_data = await implicit_service.generate_complete_profile(user_id=end_user_id) + await implicit_service.save_profile_cache( + end_user_id=end_user_id, + profile_data=profile_data, + db=db + ) + implicit_success = True + logger.info(f"成功更新用户 {end_user_id} 的隐性记忆画像") + except Exception as e: + error_msg = f"隐性记忆更新失败: {str(e)}" + errors.append(error_msg) + logger.error(f"用户 {end_user_id} {error_msg}") + + # 更新情绪建议 + try: + emotion_service = EmotionAnalyticsService(db=db, end_user_id=end_user_id) + suggestions_data = await emotion_service.generate_emotion_suggestions( + end_user_id=end_user_id, + db=db, + language="zh" + ) + await emotion_service.save_suggestions_cache( + end_user_id=end_user_id, + suggestions_data=suggestions_data, + db=db + ) + emotion_success = True + logger.info(f"成功更新用户 {end_user_id} 的情绪建议") + except Exception as e: + error_msg = f"情绪建议更新失败: {str(e)}" + errors.append(error_msg) + logger.error(f"用户 {end_user_id} {error_msg}") + + # 统计结果 + if implicit_success: + successful_implicit += 1 + if emotion_success: + successful_emotion += 1 + if not implicit_success and not emotion_success: + failed += 1 + + user_elapsed = time.time() - user_start_time + + # 记录用户处理结果 + user_result = { + "end_user_id": end_user_id, + "implicit_success": implicit_success, + "emotion_success": emotion_success, + "errors": errors, + "elapsed_time": user_elapsed + } + user_results.append(user_result) + + logger.info( + f"用户 {end_user_id} 处理完成: " + f"隐性记忆={'成功' if implicit_success else '失败'}, " + f"情绪建议={'成功' if emotion_success else '失败'}, " + f"耗时={user_elapsed:.2f}秒" + ) + + except Exception as e: + # 单个用户失败不影响其他用户（错误隔离） + failed += 1 + user_elapsed = time.time() - user_start_time + error_info = { + "end_user_id": end_user_id, + "implicit_success": False, + "emotion_success": False, + "errors": [str(e)], + "elapsed_time": user_elapsed + } + user_results.append(error_info) + logger.error(f"处理用户 {end_user_id} 时出错: {str(e)}") + + # 记录总体统计信息 + logger.info( + f"隐性记忆和情绪数据更新定时任务完成: " + f"总用户数={total_users}, " + f"隐性记忆成功={successful_implicit}, " + f"情绪建议成功={successful_emotion}, " + f"失败={failed}" + ) + + return { + "status": "SUCCESS", + "message": f"成功处理 {total_users} 个用户，隐性记忆 {successful_implicit} 个成功，情绪建议 {successful_emotion} 个成功", + "total_users": total_users, + "successful_implicit": successful_implicit, + "successful_emotion": successful_emotion, + "failed": failed, + "user_results": user_results[:50] # 只保留前50个用户的详细结果 + } + + except Exception as e: + logger.error(f"隐性记忆和情绪数据更新定时任务执行失败: {str(e)}") + return { + "status": "FAILURE", + "error": str(e), + "total_users": total_users, + "successful_implicit": successful_implicit, + "successful_emotion": successful_emotion, + "failed": failed, + "user_results": user_results[:50] + } + + try: + # 使用 nest_asyncio 来避免事件循环冲突 + try: + import nest_asyncio + nest_asyncio.apply() + except ImportError: + pass + + # 尝试获取现有事件循环，如果不存在则创建新的 + 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) + + result = loop.run_until_complete(_run()) + elapsed_time = time.time() - start_time + result["elapsed_time"] = elapsed_time + result["task_id"] = self.request.id + + return result + except Exception as e: + elapsed_time = time.time() - start_time + return { + "status": "FAILURE", + "error": str(e), + "elapsed_time": elapsed_time, + "task_id": self.request.id + } From 7446241735f7df69e58e119c6512596cfe338a15 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 15:16:47 +0800 Subject: [PATCH 25/31] [changes] AI reviews and modifies the code --- api/app/cache/__init__.py | 7 +- api/app/cache/memory/__init__.py | 8 +- api/app/controllers/emotion_controller.py | 12 +- .../controllers/implicit_memory_controller.py | 31 +-- .../models/implicit_emotions_storage_model.py | 7 +- .../implicit_emotions_storage_repository.py | 212 +++++++----------- api/app/services/emotion_analytics_service.py | 6 +- api/app/services/implicit_memory_service.py | 4 +- api/app/tasks.py | 15 +- 9 files changed, 114 insertions(+), 188 deletions(-) diff --git a/api/app/cache/__init__.py b/api/app/cache/__init__.py index a79d4cb2..748ce8ae 100644 --- a/api/app/cache/__init__.py +++ b/api/app/cache/__init__.py @@ -2,10 +2,7 @@ Cache 缓存模块 提供各种缓存功能的统一入口 +注意：隐性记忆和情绪建议已迁移到数据库存储，不再使用Redis缓存 """ -from .memory import EmotionMemoryCache, ImplicitMemoryCache -__all__ = [ - "EmotionMemoryCache", - "ImplicitMemoryCache", -] +__all__ = [] diff --git a/api/app/cache/memory/__init__.py b/api/app/cache/memory/__init__.py index 4ada3153..35f45aad 100644 --- a/api/app/cache/memory/__init__.py +++ b/api/app/cache/memory/__init__.py @@ -2,11 +2,7 @@ Memory 缓存模块 提供记忆系统相关的缓存功能 +注意：隐性记忆和情绪建议已迁移到数据库存储，不再使用Redis缓存 """ -from .emotion_memory import EmotionMemoryCache -from .implicit_memory import ImplicitMemoryCache -__all__ = [ - "EmotionMemoryCache", - "ImplicitMemoryCache", -] +__all__ = [] diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 02ce7862..0a8b5fc8 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -262,7 +262,6 @@ async def check_emotion_data_exists( @router.post("/suggestions", response_model=ApiResponse) async def get_emotion_suggestions( request: EmotionSuggestionsRequest, - language_type: str = Header(default=None, alias="X-Language-Type"), db: Session = Depends(get_db), current_user: User = Depends(get_current_user), ): @@ -277,9 +276,6 @@ async def get_emotion_suggestions( 存储的个性化情绪建议响应 """ try: - # 使用集中化的语言校验 - language = get_language_from_header(language_type) - api_logger.info( f"用户 {current_user.username} 请求获取个性化情绪建议", extra={ @@ -295,15 +291,13 @@ async def get_emotion_suggestions( ) if data is None: - # 数据不存在，返回提示信息 api_logger.info( f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - return fail( - BizCode.NOT_FOUND, - "情绪建议数据不存在，请点击右上角刷新进行初始化", - "" + return success( + data={"exists": False}, + msg="情绪建议数据不存在，请点击右上角刷新进行初始化" ) api_logger.info( diff --git a/api/app/controllers/implicit_memory_controller.py b/api/app/controllers/implicit_memory_controller.py index 91e634c9..76a87c5f 100644 --- a/api/app/controllers/implicit_memory_controller.py +++ b/api/app/controllers/implicit_memory_controller.py @@ -152,10 +152,9 @@ async def check_user_data_exists( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - {"exists": False} + return success( + data={"exists": False}, + msg="画像数据不存在，请点击右上角刷新进行初始化" ) api_logger.info(f"用户 {end_user_id} 的画像数据存在") @@ -203,11 +202,7 @@ async def get_preference_tags( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract preferences from cache preferences = cached_profile.get("preferences", []) @@ -274,11 +269,7 @@ async def get_dimension_portrait( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract portrait from cache portrait = cached_profile.get("portrait", {}) @@ -322,11 +313,7 @@ async def get_interest_area_distribution( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract interest areas from cache interest_areas = cached_profile.get("interest_areas", {}) @@ -374,11 +361,7 @@ async def get_behavior_habits( if cached_profile is None: api_logger.info(f"用户 {end_user_id} 的画像数据不存在") - return fail( - BizCode.NOT_FOUND, - "画像数据不存在，请点击右上角刷新进行初始化", - "" - ) + return fail(BizCode.NOT_FOUND, "", "") # Extract habits from cache habits = cached_profile.get("habits", []) diff --git a/api/app/models/implicit_emotions_storage_model.py b/api/app/models/implicit_emotions_storage_model.py index 57c0fd61..cf654950 100644 --- a/api/app/models/implicit_emotions_storage_model.py +++ b/api/app/models/implicit_emotions_storage_model.py @@ -19,8 +19,8 @@ class ImplicitEmotionsStorage(Base): # 主键 id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, comment="主键ID") - # 用户标识 - end_user_id = Column(String(255), nullable=False, unique=True, index=True, comment="终端用户ID") + # 用户标识（unique=True会自动创建唯一索引） + end_user_id = Column(String(255), nullable=False, unique=True, comment="终端用户ID") # 隐性记忆画像数据（JSON格式） implicit_profile = Column(JSONB, nullable=True, comment="隐性记忆用户画像数据") @@ -36,9 +36,8 @@ class ImplicitEmotionsStorage(Base): implicit_generated_at = Column(DateTime, nullable=True, comment="隐性记忆画像生成时间") emotion_generated_at = Column(DateTime, nullable=True, comment="情绪建议生成时间") - # 索引 + # 索引（只为updated_at创建索引，end_user_id的unique约束已自动创建索引） __table_args__ = ( - Index('idx_end_user_id', 'end_user_id'), Index('idx_updated_at', 'updated_at'), ) diff --git a/api/app/repositories/implicit_emotions_storage_repository.py b/api/app/repositories/implicit_emotions_storage_repository.py index fd4b10ce..176012b7 100644 --- a/api/app/repositories/implicit_emotions_storage_repository.py +++ b/api/app/repositories/implicit_emotions_storage_repository.py @@ -2,10 +2,11 @@ Implicit Emotions Storage Repository 数据访问层：处理隐性记忆和情绪数据的数据库操作 +事务由调用方控制，仓储层只使用 flush/refresh """ import logging from datetime import datetime -from typing import Optional, List +from typing import Optional, Generator from sqlalchemy.orm import Session from sqlalchemy import select @@ -16,154 +17,105 @@ logger = logging.getLogger(__name__) class ImplicitEmotionsStorageRepository: """隐性记忆和情绪存储仓储类""" - + def __init__(self, db: Session): self.db = db - + def get_by_end_user_id(self, end_user_id: str) -> Optional[ImplicitEmotionsStorage]: - """根据终端用户ID获取存储记录 - - Args: - end_user_id: 终端用户ID - - Returns: - 存储记录，如果不存在返回None - """ + """根据终端用户ID获取存储记录""" try: stmt = select(ImplicitEmotionsStorage).where( ImplicitEmotionsStorage.end_user_id == end_user_id ) - result = self.db.execute(stmt).scalar_one_or_none() - return result + return self.db.execute(stmt).scalar_one_or_none() except Exception as e: logger.error(f"获取用户存储记录失败: end_user_id={end_user_id}, error={e}") return None - + def create(self, end_user_id: str) -> ImplicitEmotionsStorage: - """创建新的存储记录 - - Args: - end_user_id: 终端用户ID - - Returns: - 新创建的存储记录 - """ - try: - storage = ImplicitEmotionsStorage( - end_user_id=end_user_id, - created_at=datetime.utcnow(), - updated_at=datetime.utcnow() - ) - self.db.add(storage) - self.db.commit() - self.db.refresh(storage) - logger.info(f"创建用户存储记录成功: end_user_id={end_user_id}") - return storage - except Exception as e: - self.db.rollback() - logger.error(f"创建用户存储记录失败: end_user_id={end_user_id}, error={e}") - raise - + """创建新的存储记录（事务由调用方提交）""" + storage = ImplicitEmotionsStorage( + end_user_id=end_user_id, + created_at=datetime.utcnow(), + updated_at=datetime.utcnow() + ) + self.db.add(storage) + self.db.flush() + self.db.refresh(storage) + logger.info(f"创建用户存储记录成功: end_user_id={end_user_id}") + return storage + def update_implicit_profile( self, end_user_id: str, profile_data: dict - ) -> Optional[ImplicitEmotionsStorage]: - """更新隐性记忆画像数据 - - Args: - end_user_id: 终端用户ID - profile_data: 画像数据 - - Returns: - 更新后的存储记录 - """ - try: - storage = self.get_by_end_user_id(end_user_id) - - if storage is None: - # 如果记录不存在，创建新记录 - storage = self.create(end_user_id) - - storage.implicit_profile = profile_data - storage.implicit_generated_at = datetime.utcnow() - storage.updated_at = datetime.utcnow() - - self.db.commit() - self.db.refresh(storage) - logger.info(f"更新隐性记忆画像成功: end_user_id={end_user_id}") - return storage - except Exception as e: - self.db.rollback() - logger.error(f"更新隐性记忆画像失败: end_user_id={end_user_id}, error={e}") - raise - + ) -> ImplicitEmotionsStorage: + """更新隐性记忆画像数据（事务由调用方提交）""" + storage = self.get_by_end_user_id(end_user_id) + if storage is None: + storage = self.create(end_user_id) + + storage.implicit_profile = profile_data + storage.implicit_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.flush() + self.db.refresh(storage) + logger.info(f"更新隐性记忆画像成功: end_user_id={end_user_id}") + return storage + def update_emotion_suggestions( self, end_user_id: str, suggestions_data: dict - ) -> Optional[ImplicitEmotionsStorage]: - """更新情绪建议数据 - + ) -> ImplicitEmotionsStorage: + """更新情绪建议数据（事务由调用方提交）""" + storage = self.get_by_end_user_id(end_user_id) + if storage is None: + storage = self.create(end_user_id) + + storage.emotion_suggestions = suggestions_data + storage.emotion_generated_at = datetime.utcnow() + storage.updated_at = datetime.utcnow() + + self.db.flush() + self.db.refresh(storage) + logger.info(f"更新情绪建议成功: end_user_id={end_user_id}") + return storage + + def get_all_user_ids(self, batch_size: int = 100) -> Generator[str, None, None]: + """分批次获取所有已存储数据的用户ID（避免大数据量内存溢出） + Args: - end_user_id: 终端用户ID - suggestions_data: 建议数据 - - Returns: - 更新后的存储记录 + batch_size: 每批次加载的数量，默认100 + + Yields: + 用户ID字符串 """ - try: - storage = self.get_by_end_user_id(end_user_id) - - if storage is None: - # 如果记录不存在，创建新记录 - storage = self.create(end_user_id) - - storage.emotion_suggestions = suggestions_data - storage.emotion_generated_at = datetime.utcnow() - storage.updated_at = datetime.utcnow() - - self.db.commit() - self.db.refresh(storage) - logger.info(f"更新情绪建议成功: end_user_id={end_user_id}") - return storage - except Exception as e: - self.db.rollback() - logger.error(f"更新情绪建议失败: end_user_id={end_user_id}, error={e}") - raise - - def get_all_user_ids(self) -> List[str]: - """获取所有已存储数据的用户ID列表 - - Returns: - 用户ID列表 - """ - try: - stmt = select(ImplicitEmotionsStorage.end_user_id) - result = self.db.execute(stmt).scalars().all() - return list(result) - except Exception as e: - logger.error(f"获取所有用户ID失败: error={e}") - return [] - + offset = 0 + while True: + try: + stmt = ( + select(ImplicitEmotionsStorage.end_user_id) + .order_by(ImplicitEmotionsStorage.end_user_id) + .limit(batch_size) + .offset(offset) + ) + batch = self.db.execute(stmt).scalars().all() + if not batch: + break + yield from batch + offset += batch_size + except Exception as e: + logger.error(f"分批获取用户ID失败: offset={offset}, error={e}") + break + def delete_by_end_user_id(self, end_user_id: str) -> bool: - """删除用户的存储记录 - - Args: - end_user_id: 终端用户ID - - Returns: - 是否删除成功 - """ - try: - storage = self.get_by_end_user_id(end_user_id) - if storage: - self.db.delete(storage) - self.db.commit() - logger.info(f"删除用户存储记录成功: end_user_id={end_user_id}") - return True - return False - except Exception as e: - self.db.rollback() - logger.error(f"删除用户存储记录失败: end_user_id={end_user_id}, error={e}") - return False + """删除用户的存储记录（事务由调用方提交）""" + storage = self.get_by_end_user_id(end_user_id) + if storage: + self.db.delete(storage) + self.db.flush() + logger.info(f"删除用户存储记录成功: end_user_id={end_user_id}") + return True + return False diff --git a/api/app/services/emotion_analytics_service.py b/api/app/services/emotion_analytics_service.py index 099cbfb7..c226348e 100644 --- a/api/app/services/emotion_analytics_service.py +++ b/api/app/services/emotion_analytics_service.py @@ -892,12 +892,12 @@ class EmotionAnalyticsService: logger.info(f"保存建议到数据库: user={end_user_id}") - # 保存到数据库 repo = ImplicitEmotionsStorageRepository(db) repo.update_emotion_suggestions(end_user_id, suggestions_data) + db.commit() logger.info(f"建议保存成功: user={end_user_id}") except Exception as e: - logger.error(f"保存建议失败: {str(e)}", exc_info=True) - # 不抛出异常，存储失败不应影响主流程 \ No newline at end of file + db.rollback() + logger.error(f"保存建议失败: {str(e)}", exc_info=True) \ No newline at end of file diff --git a/api/app/services/implicit_memory_service.py b/api/app/services/implicit_memory_service.py index 534f138c..4bd11deb 100644 --- a/api/app/services/implicit_memory_service.py +++ b/api/app/services/implicit_memory_service.py @@ -471,12 +471,12 @@ class ImplicitMemoryService: logger.info(f"保存用户画像到数据库: user={end_user_id}") - # 保存到数据库 repo = ImplicitEmotionsStorageRepository(db) repo.update_implicit_profile(end_user_id, profile_data) + db.commit() logger.info(f"用户画像保存成功: user={end_user_id}") except Exception as e: + db.rollback() logger.error(f"保存用户画像失败: {str(e)}", exc_info=True) - # 不抛出异常，存储失败不应影响主流程 diff --git a/api/app/tasks.py b/api/app/tasks.py index 67498b85..877224b7 100644 --- a/api/app/tasks.py +++ b/api/app/tasks.py @@ -2160,6 +2160,8 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: async def _run() -> Dict[str, Any]: from app.core.logging_config import get_logger from app.repositories.implicit_emotions_storage_repository import ImplicitEmotionsStorageRepository + from app.models.implicit_emotions_storage_model import ImplicitEmotionsStorage + from sqlalchemy import select, func from app.services.implicit_memory_service import ImplicitMemoryService from app.services.emotion_analytics_service import EmotionAnalyticsService @@ -2174,15 +2176,18 @@ def update_implicit_emotions_storage(self) -> Dict[str, Any]: with get_db_context() as db: try: - # 获取所有已存储数据的用户ID + # 获取所有已存储数据的用户ID（分批次处理） repo = ImplicitEmotionsStorageRepository(db) - user_ids = repo.get_all_user_ids() - total_users = len(user_ids) + # 先统计总数用于日志 + from sqlalchemy import func + total_users = db.execute( + select(func.count()).select_from(ImplicitEmotionsStorage) + ).scalar() or 0 logger.info(f"找到 {total_users} 个需要更新的用户") - # 遍历每个用户并更新数据 - for end_user_id in user_ids: + # 遍历每个用户并更新数据（分批次，避免一次性加载所有ID） + for end_user_id in repo.get_all_user_ids(batch_size=100): logger.info(f"开始处理用户: {end_user_id}") user_start_time = time.time() From a3f05220d3bd49ab318d12ec48ef2a47cba4bd4d Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 16:16:16 +0800 Subject: [PATCH 26/31] [changes] Test the scheduled task --- api/app/controllers/emotion_controller.py | 88 +++++++++++------------ 1 file changed, 44 insertions(+), 44 deletions(-) diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 0a8b5fc8..8cfc5014 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -208,55 +208,55 @@ async def get_emotion_health( -@router.post("/check-data", response_model=ApiResponse) -async def check_emotion_data_exists( - request: EmotionSuggestionsRequest, - db: Session = Depends(get_db), - current_user: User = Depends(get_current_user), -): - """检查用户情绪建议数据是否存在 +# @router.post("/check-data", response_model=ApiResponse) +# async def check_emotion_data_exists( +# request: EmotionSuggestionsRequest, +# db: Session = Depends(get_db), +# current_user: User = Depends(get_current_user), +# ): +# """检查用户情绪建议数据是否存在 - Args: - request: 包含 end_user_id - db: 数据库会话 - current_user: 当前用户 +# Args: +# request: 包含 end_user_id +# db: 数据库会话 +# current_user: 当前用户 - Returns: - 数据存在状态 - """ - try: - api_logger.info( - f"检查用户情绪建议数据是否存在: {request.end_user_id}", - extra={"end_user_id": request.end_user_id} - ) +# Returns: +# 数据存在状态 +# """ +# try: +# api_logger.info( +# f"检查用户情绪建议数据是否存在: {request.end_user_id}", +# extra={"end_user_id": request.end_user_id} +# ) - # 从数据库获取建议 - data = await emotion_service.get_cached_suggestions( - end_user_id=request.end_user_id, - db=db - ) +# # 从数据库获取建议 +# data = await emotion_service.get_cached_suggestions( +# end_user_id=request.end_user_id, +# db=db +# ) - if data is None: - api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据不存在") - return fail( - BizCode.NOT_FOUND, - "情绪建议数据不存在，请点击右上角刷新进行初始化", - {"exists": False} - ) +# if data is None: +# api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据不存在") +# return fail( +# BizCode.NOT_FOUND, +# "情绪建议数据不存在，请点击右上角刷新进行初始化", +# {"exists": False} +# ) - api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据存在") - return success(data={"exists": True}, msg="情绪建议数据已存在") +# api_logger.info(f"用户 {request.end_user_id} 的情绪建议数据存在") +# return success(data={"exists": True}, msg="情绪建议数据已存在") - except Exception as e: - api_logger.error( - f"检查情绪建议数据失败: {str(e)}", - extra={"end_user_id": request.end_user_id}, - exc_info=True - ) - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail=f"检查情绪建议数据失败: {str(e)}" - ) +# except Exception as e: +# api_logger.error( +# f"检查情绪建议数据失败: {str(e)}", +# extra={"end_user_id": request.end_user_id}, +# exc_info=True +# ) +# raise HTTPException( +# status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, +# detail=f"检查情绪建议数据失败: {str(e)}" +# ) @router.post("/suggestions", response_model=ApiResponse) @@ -383,4 +383,4 @@ async def generate_emotion_suggestions( raise HTTPException( status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=f"生成个性化建议失败: {str(e)}" - ) + ) \ No newline at end of file From 941527e7ee82fcbd80b1eb012e70aaa057e68589 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Tue, 3 Mar 2026 16:47:50 +0800 Subject: [PATCH 27/31] [changes] Modify the pop-up window for emotional suggestions at the backend --- api/app/controllers/emotion_controller.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 8cfc5014..ea7b719f 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -295,8 +295,8 @@ async def get_emotion_suggestions( f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - return success( - data={"exists": False}, + return fail( + code=404, msg="情绪建议数据不存在，请点击右上角刷新进行初始化" ) From a726a81224b7f5dca86ee6471c8741d74525c4dc Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Wed, 4 Mar 2026 13:39:21 +0800 Subject: [PATCH 28/31] [changes]Specifies the time zone divisions --- .../repositories/implicit_emotions_storage_repository.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/api/app/repositories/implicit_emotions_storage_repository.py b/api/app/repositories/implicit_emotions_storage_repository.py index 1d11f89e..97405ab6 100644 --- a/api/app/repositories/implicit_emotions_storage_repository.py +++ b/api/app/repositories/implicit_emotions_storage_repository.py @@ -5,7 +5,7 @@ Implicit Emotions Storage Repository 事务由调用方控制，仓储层只使用 flush/refresh """ import logging -from datetime import datetime, date +from datetime import datetime, date, timezone, timedelta from typing import Optional, Generator from sqlalchemy.orm import Session from sqlalchemy import select, not_, exists @@ -125,7 +125,10 @@ class ImplicitEmotionsStorageRepository: 用户ID字符串 """ from sqlalchemy import cast, String as SAString - today_start = datetime.combine(date.today(), datetime.min.time()) + CST = timezone(timedelta(hours=8)) + now_cst = datetime.now(CST) + today_start = now_cst.replace(hour=0, minute=0, second=0, microsecond=0).astimezone(timezone.utc).replace(tzinfo=None) + tomorrow_start = today_start + timedelta(days=1) offset = 0 while True: try: @@ -133,6 +136,7 @@ class ImplicitEmotionsStorageRepository: select(EndUser.id) .where( EndUser.created_at >= today_start, + EndUser.created_at < tomorrow_start, not_( exists( select(ImplicitEmotionsStorage.end_user_id).where( From 5929072b76b7bd3b4daefa5ed14f39cc32bf7071 Mon Sep 17 00:00:00 2001 From: lanceyq <1982376970@qq.com> Date: Wed, 4 Mar 2026 16:24:00 +0800 Subject: [PATCH 29/31] [changes] Emotional suggestions should not return error messages. --- api/app/controllers/emotion_controller.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index ea7b719f..8cfc5014 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -295,8 +295,8 @@ async def get_emotion_suggestions( f"用户 {request.end_user_id} 的建议数据不存在", extra={"end_user_id": request.end_user_id} ) - return fail( - code=404, + return success( + data={"exists": False}, msg="情绪建议数据不存在，请点击右上角刷新进行初始化" ) From 34de0bb9c5b7d11b6012a0b958d1f16185cef605 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Wed, 4 Mar 2026 16:28:28 +0800 Subject: [PATCH 30/31] fix(web): memory use modal replace --- web/src/i18n/en.ts | 3 ++- web/src/i18n/zh.ts | 3 ++- .../components/Suggestions.tsx | 23 +++++++++++++--- .../UserMemoryDetail/pages/ImplicitDetail.tsx | 27 ++++++++++++++++--- .../pages/StatementDetail.tsx | 18 +++++++++++-- .../views/UserMemoryDetail/pages/index.tsx | 24 ++++++++++++++--- 6 files changed, 84 insertions(+), 14 deletions(-) diff --git a/web/src/i18n/en.ts b/web/src/i18n/en.ts index b17ad291..352fc4b6 100644 --- a/web/src/i18n/en.ts +++ b/web/src/i18n/en.ts @@ -2276,6 +2276,7 @@ Memory Bear: After the rebellion, regional warlordism intensified for several re suggestions: 'Personalized Suggestions', suggestionLoading: 'Your personalized suggestions are being generated', item: 'item', + noData: 'Emotion suggestion data does not exist, please click the refresh button to initialize', }, reflectionEngine: { reflectionEngineConfig: 'Reflection Engine Configuration', @@ -2523,7 +2524,7 @@ Memory Bear: After the rebellion, regional warlordism intensified for several re supporting_evidence: 'Preference Source', specific_examples: 'Source', wordEmpty: 'Click on a node in the left chart to view preference details', - noData: 'Portrait data does not exist, please click the refresh button in the top right corner to initialize', + noData: 'Portrait data does not exist, please click the refresh button to initialize', }, shortTermDetail: { title: 'Short-term memory is the "workbench" of the AI system, connecting instant conversations with long-term knowledge bases. Through real-time capture, deep retrieval, intelligent extraction and filtering transformation, temporary unstructured information is converted into valuable long-term knowledge.', diff --git a/web/src/i18n/zh.ts b/web/src/i18n/zh.ts index 181173ff..92f0710c 100644 --- a/web/src/i18n/zh.ts +++ b/web/src/i18n/zh.ts @@ -2272,6 +2272,7 @@ export const zh = { suggestions: '个性化建议', suggestionLoading: '您的个性化建议正在生成中', item: '个', + noData: '情绪建议数据不存在，请点击刷新按钮进行初始化', }, reflectionEngine: { reflectionEngineConfig: '反思引擎配置', @@ -2519,7 +2520,7 @@ export const zh = { supporting_evidence: '偏好来源', specific_examples: '来源', wordEmpty: '点击左侧图表中的节点查看偏好详情', - noData: '画像数据不存在，请点击右上角刷新进行初始化', + noData: '画像数据不存在，请点击刷新按钮进行初始化', }, shortTermDetail: { title: '短期记忆是AI系统的"工作台"，连接即时对话与长期知识库。通过实时捕获、深度检索、智能提取和筛选转化，将临时的非结构化信息转化为有价值的长期知识。', diff --git a/web/src/views/UserMemoryDetail/components/Suggestions.tsx b/web/src/views/UserMemoryDetail/components/Suggestions.tsx index 55bfbf14..c67c0d80 100644 --- a/web/src/views/UserMemoryDetail/components/Suggestions.tsx +++ b/web/src/views/UserMemoryDetail/components/Suggestions.tsx @@ -1,12 +1,13 @@ /* * @Author: ZhaoYing * @Date: 2026-02-03 18:31:50 - * @Last Modified by: ZhaoYing - * @Last Modified time: 2026-02-03 18:31:50 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-03-04 16:22:03 */ import { useEffect, useState, forwardRef, useImperativeHandle } from 'react' import { useTranslation } from 'react-i18next' import { useParams } from 'react-router-dom' +import { App } from 'antd' import Empty from '@/components/Empty' import RbCard from '@/components/RbCard/Card' @@ -20,6 +21,7 @@ import RbAlert from '@/components/RbAlert' * @property {Array} suggestions - List of suggestions with actionable steps */ interface Suggestions { + exists?: boolean; health_summary: string; suggestions: Array<{ type: string; @@ -35,9 +37,10 @@ interface Suggestions { * Displays emotional health suggestions with actionable steps * Shows health summary and prioritized recommendations */ -const Suggestions = forwardRef<{ handleRefresh: () => void; }>((_props, ref) => { +const Suggestions = forwardRef<{ handleRefresh: () => void; }, { refresh: () => void; }>(({ refresh }, ref) => { const { t } = useTranslation() const { id } = useParams() + const { modal } = App.useApp() const [loading, setLoading] = useState(false) const [suggestions, setSuggestions] = useState(null) @@ -52,7 +55,19 @@ const Suggestions = forwardRef<{ handleRefresh: () => void; }>((_props, ref) => setLoading(true) getEmotionSuggestions(id) .then((res) => { - setSuggestions(res as Suggestions) + const response = res as Suggestions + if (!response.exists && (!response.suggestions || !response.suggestions?.length)) { + modal.confirm({ + title: t('statementDetail.noData'), + okText: t('common.refresh'), + cancelText: t('common.cancel'), + onOk: () => { + refresh() + } + }) + } else { + setSuggestions(res as Suggestions) + } }) .finally(() => { setLoading(false) diff --git a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx index 351e5ed1..aa6f40c7 100644 --- a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx @@ -1,3 +1,9 @@ +/* + * @Author: ZhaoYing + * @Date: 2026-01-08 19:46:02 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-03-04 16:26:55 + */ import { forwardRef, useImperativeHandle, useRef, useEffect } from 'react' import { useTranslation } from 'react-i18next' import { Row, Col, App } from 'antd' @@ -12,25 +18,40 @@ import { implicitCheckData, } from '@/api/memory' -const ImplicitDetail = forwardRef<{ handleRefresh: () => void; }>((_props, ref) => { +/** + * ImplicitDetail Component - Displays user's implicit memory profile + * Shows unconscious preferences, personality traits, interests and habits + */ +const ImplicitDetail = forwardRef<{ handleRefresh: () => void; }, { refresh: () => void; }>(({ + refresh +}, ref) => { const { t } = useTranslation() const { id } = useParams() - const { message } = App.useApp() + const { modal } = App.useApp() const preferencesRef = useRef<{ handleRefresh: () => void; }>(null) const portraitRef = useRef<{ handleRefresh: () => void; }>(null) const interestAreasRef = useRef<{ handleRefresh: () => void; }>(null) const habitsRef = useRef<{ handleRefresh: () => void; }>(null) + // Check if implicit data exists, prompt user to initialize if not useEffect(() => { if (!id) return implicitCheckData(id) .then(res => { if (!(res as { exists: boolean }).exists) { - message.warning(t('implicitDetail.noData')) + modal.confirm({ + title: t('implicitDetail.noData'), + okText: t('common.refresh'), + cancelText: t('common.cancel'), + onOk: () => { + refresh() + } + }) } }) }, [id]) + // Refresh all implicit memory components by regenerating profile const handleRefresh = () => { if (!id) { return Promise.resolve() diff --git a/web/src/views/UserMemoryDetail/pages/StatementDetail.tsx b/web/src/views/UserMemoryDetail/pages/StatementDetail.tsx index 72d35c60..cddf95ad 100644 --- a/web/src/views/UserMemoryDetail/pages/StatementDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/StatementDetail.tsx @@ -1,3 +1,9 @@ +/* + * @Author: ZhaoYing + * @Date: 2025-12-19 16:54:52 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-03-04 16:28:00 + */ import { forwardRef, useImperativeHandle, useRef } from 'react' import { Row, Col, Space } from 'antd'; import { useParams } from 'react-router-dom' @@ -9,9 +15,17 @@ import Suggestions from '../components/Suggestions' import { generateSuggestions } from '@/api/memory' -const StatementDetail = forwardRef((_props, ref) => { +/** + * StatementDetail - Displays emotional memory analysis for a user + * Shows word cloud, emotion tags, health index, and personalized suggestions + */ +const StatementDetail = forwardRef<{ handleRefresh: () => void },{ refresh: () => void; }>(({ + refresh +}, ref) => { const { id } = useParams() const suggestionsRef = useRef<{ handleRefresh: () => void; }>(null) + + // Regenerate suggestions and refresh the Suggestions child component const handleRefresh = () => { if (!id) { return Promise.resolve() @@ -41,7 +55,7 @@ const StatementDetail = forwardRef((_props, ref) => { - + ) diff --git a/web/src/views/UserMemoryDetail/pages/index.tsx b/web/src/views/UserMemoryDetail/pages/index.tsx index c5dea163..71cada89 100644 --- a/web/src/views/UserMemoryDetail/pages/index.tsx +++ b/web/src/views/UserMemoryDetail/pages/index.tsx @@ -1,8 +1,13 @@ +/* + * @Author: ZhaoYing + * @Date: 2026-01-07 20:37:34 + * @Last Modified by: ZhaoYing + * @Last Modified time: 2026-03-04 16:27:14 + */ import { type FC, useEffect, useState, useMemo, useRef } from 'react' import { useParams, useNavigate } from 'react-router-dom' import { useTranslation } from 'react-i18next' import { Dropdown, Button } from 'antd' -import { LoadingOutlined } from '@ant-design/icons'; import PageHeader from '../components/PageHeader' import StatementDetail from './StatementDetail' @@ -19,11 +24,16 @@ import { import refreshIcon from '@/assets/images/refresh_hover.svg' import GraphDetail from './GraphDetail' +/** + * Detail page for user memory - renders different memory type views + * based on the `type` route param + */ const Detail: FC = () => { const { t } = useTranslation() const { id, type } = useParams() const navigate = useNavigate() const [name, setName] = useState('') + // Refs for child components that support imperative refresh const forgetDetailRef = useRef<{ handleRefresh: () => void }>(null) const statementDetailRef = useRef<{ handleRefresh: () => void }>(null) const implicitDetailRef = useRef<{ handleRefresh: () => void }>(null) @@ -33,6 +43,7 @@ const Detail: FC = () => { getData() }, [id]) + // Fetch end user profile to display the user's name in the header const getData = () => { if (!id) return getEndUserProfile(id).then((res) => { @@ -40,15 +51,21 @@ const Detail: FC = () => { setName(response.other_name || response.id) }) } + + // Build dropdown menu items for switching between memory types const items = useMemo(() => { return ['PERCEPTUAL_MEMORY', 'WORKING_MEMORY', 'EMOTIONAL_MEMORY', 'SHORT_TERM_MEMORY', 'IMPLICIT_MEMORY', 'EPISODIC_MEMORY', 'EXPLICIT_MEMORY', 'FORGET_MEMORY'] .map(key => ({ key, label: t(`userMemory.${key}`) })) }, [t]) + + // Navigate to the selected memory type detail page const onClick = ({ key }: { key: string }) => { navigate(`/user-memory/detail/${id}/${key}`, { replace: true }) } const [loading, setLoading] = useState(false) + + // Trigger refresh on the active memory type's child component const handleRefresh = () => { setLoading(true) let response: any = null @@ -64,6 +81,7 @@ const Detail: FC = () => { break } + // If the child returns a Promise, wait for it before clearing loading state if (response instanceof Promise) { response.finally(() => { setLoading(false) @@ -99,9 +117,9 @@ const Detail: FC = () => { } />
- {type === 'EMOTIONAL_MEMORY' && } + {type === 'EMOTIONAL_MEMORY' && } {type === 'FORGET_MEMORY' && } - {type === 'IMPLICIT_MEMORY' && } + {type === 'IMPLICIT_MEMORY' && } {type === 'SHORT_TERM_MEMORY' && } {type === 'PERCEPTUAL_MEMORY' && } {type === 'EPISODIC_MEMORY' && } From cf571cf02ba75d0702aa8b603efc3a7db47c87e1 Mon Sep 17 00:00:00 2001 From: zhaoying Date: Thu, 5 Mar 2026 10:01:11 +0800 Subject: [PATCH 31/31] fix(web): use modal.warning replace modal.confirm --- .../UserMemoryDetail/components/Suggestions.tsx | 7 ++++--- .../UserMemoryDetail/pages/ImplicitDetail.tsx | 17 +++++++++-------- 2 files changed, 13 insertions(+), 11 deletions(-) diff --git a/web/src/views/UserMemoryDetail/components/Suggestions.tsx b/web/src/views/UserMemoryDetail/components/Suggestions.tsx index c67c0d80..3b7c1800 100644 --- a/web/src/views/UserMemoryDetail/components/Suggestions.tsx +++ b/web/src/views/UserMemoryDetail/components/Suggestions.tsx @@ -4,7 +4,7 @@ * @Last Modified by: ZhaoYing * @Last Modified time: 2026-03-04 16:22:03 */ -import { useEffect, useState, forwardRef, useImperativeHandle } from 'react' +import { useEffect, useState, useRef, forwardRef, useImperativeHandle } from 'react' import { useTranslation } from 'react-i18next' import { useParams } from 'react-router-dom' import { App } from 'antd' @@ -43,9 +43,11 @@ const Suggestions = forwardRef<{ handleRefresh: () => void; }, { refresh: () => const { modal } = App.useApp() const [loading, setLoading] = useState(false) const [suggestions, setSuggestions] = useState(null) + const modalInstanceRef = useRef<{ destroy: () => void } | null>(null) useEffect(() => { getSuggestionData() + return () => modalInstanceRef.current?.destroy() }, [id]) const getSuggestionData = () => { @@ -57,10 +59,9 @@ const Suggestions = forwardRef<{ handleRefresh: () => void; }, { refresh: () => .then((res) => { const response = res as Suggestions if (!response.exists && (!response.suggestions || !response.suggestions?.length)) { - modal.confirm({ + modalInstanceRef.current = modal.warning({ title: t('statementDetail.noData'), okText: t('common.refresh'), - cancelText: t('common.cancel'), onOk: () => { refresh() } diff --git a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx index aa6f40c7..46286fff 100644 --- a/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/ImplicitDetail.tsx @@ -36,19 +36,20 @@ const ImplicitDetail = forwardRef<{ handleRefresh: () => void; }, { refresh: () // Check if implicit data exists, prompt user to initialize if not useEffect(() => { if (!id) return + let modalInstance: { destroy: () => void } | null = null implicitCheckData(id) .then(res => { if (!(res as { exists: boolean }).exists) { - modal.confirm({ - title: t('implicitDetail.noData'), - okText: t('common.refresh'), - cancelText: t('common.cancel'), - onOk: () => { - refresh() - } - }) + modalInstance = modal.warning({ + title: t('implicitDetail.noData'), + okText: t('common.refresh'), + onOk: () => { + refresh() + } + }) } }) + return () => modalInstance?.destroy() }, [id]) // Refresh all implicit memory components by regenerating profile