diff --git a/api/app/controllers/__init__.py b/api/app/controllers/__init__.py index a45c701f..2fabbcc8 100644 --- a/api/app/controllers/__init__.py +++ b/api/app/controllers/__init__.py @@ -20,6 +20,8 @@ from . import ( knowledgeshare_controller, memory_agent_controller, memory_dashboard_controller, + memory_episodic_controller, + memory_explicit_controller, memory_forget_controller, memory_reflection_controller, memory_short_term_controller, @@ -67,6 +69,8 @@ manager_router.include_router(memory_agent_controller.router) manager_router.include_router(memory_dashboard_controller.router) manager_router.include_router(memory_storage_controller.router) manager_router.include_router(user_memory_controllers.router) +manager_router.include_router(memory_episodic_controller.router) +manager_router.include_router(memory_explicit_controller.router) manager_router.include_router(api_key_controller.router) manager_router.include_router(release_share_controller.router) manager_router.include_router(public_share_controller.router) # 公开路由（无需认证） diff --git a/api/app/controllers/emotion_controller.py b/api/app/controllers/emotion_controller.py index 90465c95..7f0cb91b 100644 --- a/api/app/controllers/emotion_controller.py +++ b/api/app/controllers/emotion_controller.py @@ -30,7 +30,7 @@ from sqlalchemy.orm import Session api_logger = get_api_logger() router = APIRouter( - prefix="/memory/emotion", + prefix="/memory/emotion-memory", tags=["Emotion Analysis"], dependencies=[Depends(get_current_user)] # 所有路由都需要认证 ) diff --git a/api/app/controllers/home_page_controller.py b/api/app/controllers/home_page_controller.py index 77db9d8f..0b758cd1 100644 --- a/api/app/controllers/home_page_controller.py +++ b/api/app/controllers/home_page_controller.py @@ -32,7 +32,6 @@ def get_workspace_list( @router.get("/version", response_model=ApiResponse) def get_system_version(): """获取系统版本号+说明""" - return success(data={ - "version": settings.SYSTEM_VERSION, - "introduction": settings.SYSTEM_INTRODUCTION - }, msg="系统版本获取成功") \ No newline at end of file + current_version = settings.SYSTEM_VERSION + version_introduction = HomePageService.load_version_introduction(current_version) + return success(data={"version": current_version, "introduction": version_introduction}, msg="系统版本获取成功") \ No newline at end of file diff --git a/api/app/controllers/memory_dashboard_controller.py b/api/app/controllers/memory_dashboard_controller.py index 5166d012..2afff491 100644 --- a/api/app/controllers/memory_dashboard_controller.py +++ b/api/app/controllers/memory_dashboard_controller.py @@ -1,18 +1,15 @@ from fastapi import APIRouter, Depends, HTTPException, status, Query from sqlalchemy.orm import Session -from typing import List, Optional -import uuid -from app.repositories.end_user_repository import update_end_user_other_name -import uuid +from typing import Optional from app.core.response_utils import success from app.db import get_db from app.dependencies import get_current_user from app.models.user_model import User from app.schemas.memory_agent_schema import End_User_Information from app.schemas.response_schema import ApiResponse -from app.schemas.app_schema import App as AppSchema 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.core.logging_config import get_api_logger # 获取API专用日志器 @@ -102,7 +99,8 @@ async def get_workspace_end_users( """ 获取工作空间的宿主列表 - 返回格式与原 memory_list 接口中的 end_users 字段相同 + 返回格式与原 memory_list 接口中的 end_users 字段相同， + 并包含每个用户的记忆配置信息（memory_config_id 和 memory_config_name） """ workspace_id = current_user.current_workspace_id # 获取当前空间类型 @@ -113,6 +111,17 @@ async def get_workspace_end_users( workspace_id=workspace_id, current_user=current_user ) + + # 批量获取所有用户的记忆配置信息（优化：一次查询而非 N 次） + end_user_ids = [str(user.id) for user in end_users] + memory_configs_map = {} + if end_user_ids: + try: + memory_configs_map = get_end_users_connected_configs_batch(end_user_ids, db) + except Exception as e: + api_logger.error(f"批量获取记忆配置失败: {str(e)}") + # 失败时使用空字典，不影响其他数据返回 + result = [] for end_user in end_users: memory_num = {} @@ -123,10 +132,25 @@ async def get_workspace_end_users( memory_num = { "total":memory_dashboard_service.get_current_user_total_chunk(str(end_user.id), db, current_user) } + + # 从批量查询结果中获取配置信息 + user_id = str(end_user.id) + memory_config_info = memory_configs_map.get(user_id, { + "memory_config_id": None, + "memory_config_name": None + }) + + # 只保留需要的字段，移除 error 字段（如果有） + memory_config = { + "memory_config_id": memory_config_info.get("memory_config_id"), + "memory_config_name": memory_config_info.get("memory_config_name") + } + result.append( { - 'end_user':end_user, - 'memory_num':memory_num + 'end_user': end_user, + 'memory_num': memory_num, + 'memory_config': memory_config } ) @@ -465,7 +489,6 @@ async def dashboard_data( if storage_type is None: storage_type = 'neo4j' - user_rag_memory_id = None # 根据 storage_type 决定返回哪个数据对象 # 如果是 'rag'，neo4j_data 为 null；否则 rag_data 为 null diff --git a/api/app/controllers/memory_episodic_controller.py b/api/app/controllers/memory_episodic_controller.py new file mode 100644 index 00000000..331adfd3 --- /dev/null +++ b/api/app/controllers/memory_episodic_controller.py @@ -0,0 +1,125 @@ +""" +情景记忆相关的控制器 +包含情景记忆总览和详情查询接口 +""" + +from fastapi import APIRouter, Depends + +from app.core.error_codes import BizCode +from app.core.logging_config import get_api_logger +from app.core.response_utils import fail, success +from app.dependencies import get_current_user +from app.models.user_model import User +from app.schemas.response_schema import ApiResponse +from app.schemas.memory_episodic_schema import ( + EpisodicMemoryOverviewRequest, + EpisodicMemoryDetailsRequest, +) +from app.services.memory_episodic_service import memory_episodic_service + +# Get API logger +api_logger = get_api_logger() + +router = APIRouter( + prefix="/memory/episodic-memory", + tags=["Episodic Memory"], +) + + +@router.post("/overview", response_model=ApiResponse) +async def get_episodic_memory_overview_api( + request: EpisodicMemoryOverviewRequest, + current_user: User = Depends(get_current_user), +) -> dict: + """ + 获取情景记忆总览 + + 返回指定用户的所有情景记忆列表，包括标题和创建时间。 + 支持通过时间范围、情景类型和标题关键词进行筛选。 + + """ + workspace_id = current_user.current_workspace_id + + # 检查用户是否已选择工作空间 + if workspace_id is None: + api_logger.warning(f"用户 {current_user.username} 尝试查询情景记忆总览但未选择工作空间") + return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") + + # 验证参数 + valid_time_ranges = ["all", "today", "this_week", "this_month"] + valid_episodic_types = ["all", "conversation", "project_work", "learning", "decision", "important_event"] + + if request.time_range not in valid_time_ranges: + return fail(BizCode.INVALID_PARAMETER, f"无效的时间范围参数，可选值：{', '.join(valid_time_ranges)}") + + if request.episodic_type not in valid_episodic_types: + return fail(BizCode.INVALID_PARAMETER, f"无效的情景类型参数，可选值：{', '.join(valid_episodic_types)}") + + # 处理 title_keyword（去除首尾空格） + title_keyword = request.title_keyword.strip() if request.title_keyword else None + + api_logger.info( + f"情景记忆总览查询请求: end_user_id={request.end_user_id}, user={current_user.username}, " + f"workspace={workspace_id}, time_range={request.time_range}, episodic_type={request.episodic_type}, " + f"title_keyword={title_keyword}" + ) + + try: + # 调用Service层方法 + result = await memory_episodic_service.get_episodic_memory_overview( + request.end_user_id, request.time_range, request.episodic_type, title_keyword + ) + + api_logger.info( + f"成功获取情景记忆总览: end_user_id={request.end_user_id}, " + f"total={result['total']}" + ) + return success(data=result, msg="查询成功") + + except Exception as e: + api_logger.error(f"情景记忆总览查询失败: end_user_id={request.end_user_id}, error={str(e)}") + return fail(BizCode.INTERNAL_ERROR, "情景记忆总览查询失败", str(e)) + + +@router.post("/details", response_model=ApiResponse) +async def get_episodic_memory_details_api( + request: EpisodicMemoryDetailsRequest, + current_user: User = Depends(get_current_user), +) -> dict: + """ + 获取情景记忆详情 + + 返回指定情景记忆的详细信息，包括涉及对象、情景类型、内容记录和情绪。 + + """ + workspace_id = current_user.current_workspace_id + + # 检查用户是否已选择工作空间 + if workspace_id is None: + api_logger.warning(f"用户 {current_user.username} 尝试查询情景记忆详情但未选择工作空间") + return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") + + api_logger.info( + f"情景记忆详情查询请求: end_user_id={request.end_user_id}, summary_id={request.summary_id}, " + f"user={current_user.username}, workspace={workspace_id}" + ) + + try: + # 调用Service层方法 + result = await memory_episodic_service.get_episodic_memory_details( + end_user_id=request.end_user_id, + summary_id=request.summary_id + ) + + api_logger.info( + f"成功获取情景记忆详情: end_user_id={request.end_user_id}, summary_id={request.summary_id}" + ) + return success(data=result, msg="查询成功") + + except ValueError as e: + # 处理情景记忆不存在的情况 + api_logger.warning(f"情景记忆不存在: end_user_id={request.end_user_id}, summary_id={request.summary_id}, error={str(e)}") + return fail(BizCode.INVALID_PARAMETER, "情景记忆不存在", str(e)) + except Exception as e: + api_logger.error(f"情景记忆详情查询失败: end_user_id={request.end_user_id}, summary_id={request.summary_id}, error={str(e)}") + return fail(BizCode.INTERNAL_ERROR, "情景记忆详情查询失败", str(e)) diff --git a/api/app/controllers/memory_explicit_controller.py b/api/app/controllers/memory_explicit_controller.py new file mode 100644 index 00000000..c52f308c --- /dev/null +++ b/api/app/controllers/memory_explicit_controller.py @@ -0,0 +1,115 @@ +""" +显性记忆控制器 + +处理显性记忆相关的API接口，包括情景记忆和语义记忆的查询。 +""" + +from fastapi import APIRouter, Depends + +from app.core.logging_config import get_api_logger +from app.core.response_utils import success, fail +from app.core.error_codes import BizCode +from app.services.memory_explicit_service import MemoryExplicitService +from app.schemas.response_schema import ApiResponse +from app.schemas.memory_explicit_schema import ( + ExplicitMemoryOverviewRequest, + ExplicitMemoryDetailsRequest, +) +from app.dependencies import get_current_user +from app.models.user_model import User + +# Get API logger +api_logger = get_api_logger() + +# Initialize service +memory_explicit_service = MemoryExplicitService() + +router = APIRouter( + prefix="/memory/explicit-memory", + tags=["Explicit Memory"], +) + + +@router.post("/overview", response_model=ApiResponse) +async def get_explicit_memory_overview_api( + request: ExplicitMemoryOverviewRequest, + current_user: User = Depends(get_current_user), +) -> dict: + """ + 获取显性记忆总览 + + 返回指定用户的所有显性记忆列表，包括标题、完整内容、创建时间和情绪信息。 + """ + workspace_id = current_user.current_workspace_id + + # 检查用户是否已选择工作空间 + if workspace_id is None: + api_logger.warning(f"用户 {current_user.username} 尝试查询显性记忆总览但未选择工作空间") + return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") + + api_logger.info( + f"显性记忆总览查询请求: end_user_id={request.end_user_id}, user={current_user.username}, " + f"workspace={workspace_id}" + ) + + try: + # 调用Service层方法 + result = await memory_explicit_service.get_explicit_memory_overview( + request.end_user_id + ) + + api_logger.info( + f"成功获取显性记忆总览: end_user_id={request.end_user_id}, " + f"total={result['total']}" + ) + return success(data=result, msg="查询成功") + + except Exception as e: + api_logger.error(f"显性记忆总览查询失败: end_user_id={request.end_user_id}, error={str(e)}") + return fail(BizCode.INTERNAL_ERROR, "显性记忆总览查询失败", str(e)) + + +@router.post("/details", response_model=ApiResponse) +async def get_explicit_memory_details_api( + request: ExplicitMemoryDetailsRequest, + current_user: User = Depends(get_current_user), +) -> dict: + """ + 获取显性记忆详情 + + 根据 memory_id 返回情景记忆或语义记忆的详细信息。 + - 情景记忆：包括标题、内容、情绪、创建时间 + - 语义记忆：包括名称、核心定义、详细笔记、创建时间 + """ + workspace_id = current_user.current_workspace_id + + # 检查用户是否已选择工作空间 + if workspace_id is None: + api_logger.warning(f"用户 {current_user.username} 尝试查询显性记忆详情但未选择工作空间") + return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") + + api_logger.info( + f"显性记忆详情查询请求: end_user_id={request.end_user_id}, memory_id={request.memory_id}, " + f"user={current_user.username}, workspace={workspace_id}" + ) + + try: + # 调用Service层方法 + result = await memory_explicit_service.get_explicit_memory_details( + end_user_id=request.end_user_id, + memory_id=request.memory_id + ) + + api_logger.info( + f"成功获取显性记忆详情: end_user_id={request.end_user_id}, memory_id={request.memory_id}, " + f"memory_type={result.get('memory_type')}" + ) + return success(data=result, msg="查询成功") + + except ValueError as e: + # 处理记忆不存在的情况 + api_logger.warning(f"显性记忆不存在: end_user_id={request.end_user_id}, memory_id={request.memory_id}, error={str(e)}") + return fail(BizCode.INVALID_PARAMETER, "显性记忆不存在", str(e)) + except Exception as e: + api_logger.error(f"显性记忆详情查询失败: end_user_id={request.end_user_id}, memory_id={request.memory_id}, error={str(e)}") + return fail(BizCode.INTERNAL_ERROR, "显性记忆详情查询失败", str(e)) diff --git a/api/app/controllers/memory_forget_controller.py b/api/app/controllers/memory_forget_controller.py index e8a5732f..ca628d0c 100644 --- a/api/app/controllers/memory_forget_controller.py +++ b/api/app/controllers/memory_forget_controller.py @@ -39,7 +39,7 @@ from app.services.memory_forget_service import MemoryForgetService api_logger = get_api_logger() router = APIRouter( - prefix="/memory/forget", + prefix="/memory/forget-memory", tags=["Memory Forgetting Engine"], dependencies=[Depends(get_current_user)] # 所有路由都需要认证 ) diff --git a/api/app/controllers/user_memory_controllers.py b/api/app/controllers/user_memory_controllers.py index 5fd9b841..a96c7a52 100644 --- a/api/app/controllers/user_memory_controllers.py +++ b/api/app/controllers/user_memory_controllers.py @@ -20,12 +20,6 @@ from app.services.user_memory_service import ( from app.services.memory_entity_relationship_service import MemoryEntityService,MemoryEmotion,MemoryInteraction from app.schemas.response_schema import ApiResponse from app.schemas.memory_storage_schema import GenerateCacheRequest -from app.schemas.user_memory_schema import ( - EpisodicMemoryOverviewRequest, - EpisodicMemoryDetailsRequest, - ExplicitMemoryOverviewRequest, - ExplicitMemoryDetailsRequest, -) from app.schemas.end_user_schema import ( EndUserProfileResponse, @@ -440,195 +434,3 @@ async def memory_space_relationship_evolution(id: str, label: str, except Exception as e: api_logger.error(f"关系演变查询失败: id={id}, table={label}, error={str(e)}", exc_info=True) return fail(BizCode.INTERNAL_ERROR, "关系演变查询失败", str(e)) - - -@router.post("/classifications/episodic-memory", response_model=ApiResponse) -async def get_episodic_memory_overview_api( - request: EpisodicMemoryOverviewRequest, - current_user: User = Depends(get_current_user), - db: Session = Depends(get_db), -) -> dict: - """ - 获取情景记忆总览 - - 返回指定用户的所有情景记忆列表，包括标题和创建时间。 - 支持通过时间范围、情景类型和标题关键词进行筛选。 - - """ - workspace_id = current_user.current_workspace_id - - # 检查用户是否已选择工作空间 - if workspace_id is None: - api_logger.warning(f"用户 {current_user.username} 尝试查询情景记忆总览但未选择工作空间") - return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") - - # 验证参数 - valid_time_ranges = ["all", "today", "this_week", "this_month"] - valid_episodic_types = ["all", "conversation", "project_work", "learning", "decision", "important_event"] - - if request.time_range not in valid_time_ranges: - return fail(BizCode.INVALID_PARAMETER, f"无效的时间范围参数，可选值：{', '.join(valid_time_ranges)}") - - if request.episodic_type not in valid_episodic_types: - return fail(BizCode.INVALID_PARAMETER, f"无效的情景类型参数，可选值：{', '.join(valid_episodic_types)}") - - # 处理 title_keyword（去除首尾空格） - title_keyword = request.title_keyword.strip() if request.title_keyword else None - - api_logger.info( - f"情景记忆总览查询请求: end_user_id={request.end_user_id}, user={current_user.username}, " - f"workspace={workspace_id}, time_range={request.time_range}, episodic_type={request.episodic_type}, " - f"title_keyword={title_keyword}" - ) - - try: - # 调用Service层方法 - result = await user_memory_service.get_episodic_memory_overview( - db, request.end_user_id, request.time_range, request.episodic_type, title_keyword - ) - - api_logger.info( - f"成功获取情景记忆总览: end_user_id={request.end_user_id}, " - f"total={result['total']}" - ) - return success(data=result, msg="查询成功") - - except Exception as e: - api_logger.error(f"情景记忆总览查询失败: end_user_id={request.end_user_id}, error={str(e)}") - return fail(BizCode.INTERNAL_ERROR, "情景记忆总览查询失败", str(e)) - - -@router.post("/classifications/episodic-memory-details", response_model=ApiResponse) -async def get_episodic_memory_details_api( - request: EpisodicMemoryDetailsRequest, - current_user: User = Depends(get_current_user), - db: Session = Depends(get_db), -) -> dict: - """ - 获取情景记忆详情 - - 返回指定情景记忆的详细信息，包括涉及对象、情景类型、内容记录和情绪。 - - """ - workspace_id = current_user.current_workspace_id - - # 检查用户是否已选择工作空间 - if workspace_id is None: - api_logger.warning(f"用户 {current_user.username} 尝试查询情景记忆详情但未选择工作空间") - return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") - - api_logger.info( - f"情景记忆详情查询请求: end_user_id={request.end_user_id}, summary_id={request.summary_id}, " - f"user={current_user.username}, workspace={workspace_id}" - ) - - try: - # 调用Service层方法 - result = await user_memory_service.get_episodic_memory_details( - db=db, - end_user_id=request.end_user_id, - summary_id=request.summary_id - ) - - api_logger.info( - f"成功获取情景记忆详情: end_user_id={request.end_user_id}, summary_id={request.summary_id}" - ) - return success(data=result, msg="查询成功") - - except ValueError as e: - # 处理情景记忆不存在的情况 - api_logger.warning(f"情景记忆不存在: end_user_id={request.end_user_id}, summary_id={request.summary_id}, error={str(e)}") - return fail(BizCode.INVALID_PARAMETER, "情景记忆不存在", str(e)) - except Exception as e: - api_logger.error(f"情景记忆详情查询失败: end_user_id={request.end_user_id}, summary_id={request.summary_id}, error={str(e)}") - return fail(BizCode.INTERNAL_ERROR, "情景记忆详情查询失败", str(e)) - - -@router.post("/classifications/explicit-memory", response_model=ApiResponse) -async def get_explicit_memory_overview_api( - request: ExplicitMemoryOverviewRequest, - current_user: User = Depends(get_current_user), - db: Session = Depends(get_db), -) -> dict: - """ - 获取显性记忆总览 - - 返回指定用户的所有显性记忆列表，包括标题、完整内容、创建时间和情绪信息。 - """ - workspace_id = current_user.current_workspace_id - - # 检查用户是否已选择工作空间 - if workspace_id is None: - api_logger.warning(f"用户 {current_user.username} 尝试查询显性记忆总览但未选择工作空间") - return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") - - api_logger.info( - f"显性记忆总览查询请求: end_user_id={request.end_user_id}, user={current_user.username}, " - f"workspace={workspace_id}" - ) - - try: - # 调用Service层方法 - result = await user_memory_service.get_explicit_memory_overview( - db, request.end_user_id - ) - - api_logger.info( - f"成功获取显性记忆总览: end_user_id={request.end_user_id}, " - f"total={result['total']}" - ) - return success(data=result, msg="查询成功") - - except Exception as e: - api_logger.error(f"显性记忆总览查询失败: end_user_id={request.end_user_id}, error={str(e)}") - return fail(BizCode.INTERNAL_ERROR, "显性记忆总览查询失败", str(e)) - - -@router.post("/classifications/explicit-memory-details", response_model=ApiResponse) -async def get_explicit_memory_details_api( - request: ExplicitMemoryDetailsRequest, - current_user: User = Depends(get_current_user), - db: Session = Depends(get_db), -) -> dict: - """ - 获取显性记忆详情 - - 根据 memory_id 返回情景记忆或语义记忆的详细信息。 - - 情景记忆：包括标题、内容、情绪、创建时间 - - 语义记忆：包括名称、核心定义、详细笔记、创建时间 - """ - workspace_id = current_user.current_workspace_id - - # 检查用户是否已选择工作空间 - if workspace_id is None: - api_logger.warning(f"用户 {current_user.username} 尝试查询显性记忆详情但未选择工作空间") - return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None") - - api_logger.info( - f"显性记忆详情查询请求: end_user_id={request.end_user_id}, memory_id={request.memory_id}, " - f"user={current_user.username}, workspace={workspace_id}" - ) - - try: - # 调用Service层方法 - result = await user_memory_service.get_explicit_memory_details( - db=db, - end_user_id=request.end_user_id, - memory_id=request.memory_id - ) - - api_logger.info( - f"成功获取显性记忆详情: end_user_id={request.end_user_id}, memory_id={request.memory_id}, " - f"memory_type={result.get('memory_type')}" - ) - return success(data=result, msg="查询成功") - - except ValueError as e: - # 处理记忆不存在的情况 - api_logger.warning(f"显性记忆不存在: end_user_id={request.end_user_id}, memory_id={request.memory_id}, error={str(e)}") - return fail(BizCode.INVALID_PARAMETER, "显性记忆不存在", str(e)) - except Exception as e: - api_logger.error(f"显性记忆详情查询失败: end_user_id={request.end_user_id}, memory_id={request.memory_id}, error={str(e)}") - return fail(BizCode.INTERNAL_ERROR, "显性记忆详情查询失败", str(e)) - - diff --git a/api/app/core/config.py b/api/app/core/config.py index d9b9cea8..573c4283 100644 --- a/api/app/core/config.py +++ b/api/app/core/config.py @@ -167,7 +167,6 @@ class Settings: # official environment system version SYSTEM_VERSION: str = os.getenv("SYSTEM_VERSION", "v0.2.0") - SYSTEM_INTRODUCTION: str = os.getenv("SYSTEM_INTRODUCTION", "") def get_memory_output_path(self, filename: str = "") -> str: """ diff --git a/api/app/core/memory/storage_services/extraction_engine/knowledge_extraction/memory_summary.py b/api/app/core/memory/storage_services/extraction_engine/knowledge_extraction/memory_summary.py index c72b9a1f..7e75fd2d 100644 --- a/api/app/core/memory/storage_services/extraction_engine/knowledge_extraction/memory_summary.py +++ b/api/app/core/memory/storage_services/extraction_engine/knowledge_extraction/memory_summary.py @@ -1,6 +1,7 @@ import asyncio +import json from datetime import datetime -from typing import List, Optional +from typing import List, Optional, Tuple from uuid import uuid4 from app.core.logging_config import get_memory_logger @@ -28,6 +29,118 @@ class MemorySummaryResponse(RobustLLMResponse): ) +async def generate_title_and_type_for_summary( + content: str, + llm_client +) -> Tuple[str, str]: + """ + 为MemorySummary生成标题和类型 + + 此方法应该在创建MemorySummary节点时调用，生成title和type + + Args: + content: Summary的内容文本 + llm_client: LLM客户端实例 + + Returns: + (标题, 类型)元组 + """ + from app.core.memory.utils.prompt.prompt_utils import render_episodic_title_and_type_prompt + + # 定义有效的类型集合 + VALID_TYPES = { + "conversation", # 对话 + "project_work", # 项目/工作 + "learning", # 学习 + "decision", # 决策 + "important_event" # 重要事件 + } + DEFAULT_TYPE = "conversation" # 默认类型 + + try: + if not content: + logger.warning("content为空，无法生成标题和类型") + return ("空内容", DEFAULT_TYPE) + + # 1. 渲染Jinja2提示词模板 + prompt = await render_episodic_title_and_type_prompt(content) + + # 2. 调用LLM生成标题和类型 + messages = [ + {"role": "user", "content": prompt} + ] + + response = await llm_client.chat(messages=messages) + + # 3. 解析LLM响应 + content_response = response.content + if isinstance(content_response, list): + if len(content_response) > 0: + if isinstance(content_response[0], dict): + text = content_response[0].get('text', content_response[0].get('content', str(content_response[0]))) + full_response = str(text) + else: + full_response = str(content_response[0]) + else: + full_response = "" + elif isinstance(content_response, dict): + full_response = str(content_response.get('text', content_response.get('content', str(content_response)))) + else: + full_response = str(content_response) if content_response is not None else "" + + # 4. 解析JSON响应 + try: + # 尝试从响应中提取JSON + # 移除可能的markdown代码块标记 + json_str = full_response.strip() + if json_str.startswith("```json"): + json_str = json_str[7:] + if json_str.startswith("```"): + json_str = json_str[3:] + if json_str.endswith("```"): + json_str = json_str[:-3] + json_str = json_str.strip() + + result_data = json.loads(json_str) + title = result_data.get("title", "未知标题") + episodic_type_raw = result_data.get("type", DEFAULT_TYPE) + + # 5. 校验和归一化类型 + # 将类型转换为小写并去除空格 + episodic_type_normalized = str(episodic_type_raw).lower().strip() + + # 检查是否在有效类型集合中 + if episodic_type_normalized in VALID_TYPES: + episodic_type = episodic_type_normalized + else: + # 尝试映射常见的中文类型到英文 + type_mapping = { + "对话": "conversation", + "项目": "project_work", + "工作": "project_work", + "项目/工作": "project_work", + "学习": "learning", + "决策": "decision", + "重要事件": "important_event", + "事件": "important_event" + } + episodic_type = type_mapping.get(episodic_type_raw, DEFAULT_TYPE) + logger.warning( + f"LLM返回的类型 '{episodic_type_raw}' 不在有效集合中，" + f"已归一化为 '{episodic_type}'" + ) + + logger.info(f"成功生成标题和类型: title={title}, type={episodic_type}") + return (title, episodic_type) + + except json.JSONDecodeError: + logger.error(f"无法解析LLM响应为JSON: {full_response}") + return ("解析失败", DEFAULT_TYPE) + + except Exception as e: + logger.error(f"生成标题和类型时出错: {str(e)}", exc_info=True) + return ("错误", DEFAULT_TYPE) + async def _process_chunk_summary( dialog: DialogData, chunk, @@ -63,10 +176,9 @@ async def _process_chunk_summary( title = None episodic_type = None try: - from app.services.user_memory_service import UserMemoryService - title, episodic_type = await UserMemoryService.generate_title_and_type_for_summary( + title, episodic_type = await generate_title_and_type_for_summary( content=summary_text, - end_user_id=dialog.group_id + llm_client=llm_client ) logger.info(f"Generated title and type for MemorySummary: title={title}, type={episodic_type}") except Exception as e: diff --git a/api/app/core/memory/storage_services/forgetting_engine/forgetting_strategy.py b/api/app/core/memory/storage_services/forgetting_engine/forgetting_strategy.py index f1802166..ccd8d2ca 100644 --- a/api/app/core/memory/storage_services/forgetting_engine/forgetting_strategy.py +++ b/api/app/core/memory/storage_services/forgetting_engine/forgetting_strategy.py @@ -260,17 +260,32 @@ class ForgettingStrategy: ) # 生成标题和类型（使用LLM） - from app.services.user_memory_service import UserMemoryService + from app.core.memory.storage_services.extraction_engine.knowledge_extraction.memory_summary import generate_title_and_type_for_summary + + # 获取 LLM 客户端 + llm_client = None + if config_id is not None and db is not None: + try: + llm_client = await self._get_llm_client(db, config_id) + except Exception as e: + logger.warning(f"获取 LLM 客户端失败: {str(e)}") + + # 生成标题和类型 try: - title, episodic_type = await UserMemoryService.generate_title_and_type_for_summary( - content=summary_text, - end_user_id=group_id - ) - logger.info(f"成功为MemorySummary生成标题和类型: title={title}, type={episodic_type}") + if llm_client is not None: + title, episodic_type = await generate_title_and_type_for_summary( + content=summary_text, + llm_client=llm_client + ) + logger.info(f"成功为MemorySummary生成标题和类型: title={title}, type={episodic_type}") + else: + logger.warning("LLM 客户端不可用，使用默认标题和类型") + title = "未命名" + episodic_type = "conversation" except Exception as e: logger.error(f"生成标题和类型失败，使用默认值: {str(e)}") title = "未命名" - episodic_type = "其他" + episodic_type = "conversation" # 计算继承的激活值和重要性（取较高值） inherited_activation = max(statement_activation, entity_activation) diff --git a/api/app/core/tools/builtin/baidu_search_tool.py b/api/app/core/tools/builtin/baidu_search_tool.py index e1f80f34..02431aed 100644 --- a/api/app/core/tools/builtin/baidu_search_tool.py +++ b/api/app/core/tools/builtin/baidu_search_tool.py @@ -110,7 +110,7 @@ class BaiduSearchTool(BuiltinTool): execution_time = time.time() - start_time return ToolResult.success_result( - data=result, + data=result["results"], execution_time=execution_time ) diff --git a/api/app/core/tools/builtin/datetime_tool.py b/api/app/core/tools/builtin/datetime_tool.py index 7b6fa8ef..00004dfe 100644 --- a/api/app/core/tools/builtin/datetime_tool.py +++ b/api/app/core/tools/builtin/datetime_tool.py @@ -95,7 +95,7 @@ class DateTimeTool(BuiltinTool): execution_time = time.time() - start_time return ToolResult.success_result( - data=result, + data=result["result_data"], execution_time=execution_time ) @@ -123,12 +123,14 @@ class DateTimeTool(BuiltinTool): utc_now = datetime.now(timezone.utc) return { - "datetime": now.strftime(output_format), - "timestamp": int(now.timestamp()), "timezone": timezone_str, "iso_format": now.isoformat(), - "timestamp_ms": int(now.timestamp() * 1000), - "utc_datetime": utc_now.strftime(output_format) + "result_data": { + "datetime": now.strftime(output_format), + "timestamp": int(now.timestamp()), + "timestamp_ms": int(now.timestamp() * 1000), + "utc_datetime": utc_now.strftime(output_format), + } } @staticmethod @@ -148,7 +150,8 @@ class DateTimeTool(BuiltinTool): "original": input_value, "formatted": dt.strftime(output_format), "timestamp": int(dt.timestamp()), - "iso_format": dt.isoformat() + "iso_format": dt.isoformat(), + "result_data": dt.strftime(output_format) } @staticmethod @@ -189,7 +192,8 @@ class DateTimeTool(BuiltinTool): "original_timezone": from_timezone, "converted": converted_dt.strftime(output_format), "converted_timezone": to_timezone, - "timestamp": int(converted_dt.timestamp()) + "timestamp": int(converted_dt.timestamp()), + "result_data": converted_dt.strftime(output_format) } @staticmethod @@ -219,7 +223,8 @@ class DateTimeTool(BuiltinTool): "timestamp": timestamp, "datetime": dt.strftime(output_format), "timezone": timezone_str, - "iso_format": dt.isoformat() + "iso_format": dt.isoformat(), + "result_data": dt.strftime(output_format) } @staticmethod @@ -249,7 +254,8 @@ class DateTimeTool(BuiltinTool): "datetime": input_value, "timezone": timezone_str, "timestamp": int(dt.timestamp()), - "iso_format": dt.isoformat() + "iso_format": dt.isoformat(), + "result_data": int(dt.timestamp()) } def _calculate_datetime(self, kwargs) -> dict: @@ -287,7 +293,8 @@ class DateTimeTool(BuiltinTool): "calculation": calculation, "result": calculated_dt.strftime(output_format), "timezone": timezone_str, - "timestamp": int(calculated_dt.timestamp()) + "timestamp": int(calculated_dt.timestamp()), + "result_data": calculated_dt.strftime(output_format) } @staticmethod diff --git a/api/app/core/tools/builtin/json_tool.py b/api/app/core/tools/builtin/json_tool.py index f22e9370..57d3130d 100644 --- a/api/app/core/tools/builtin/json_tool.py +++ b/api/app/core/tools/builtin/json_tool.py @@ -69,7 +69,7 @@ class JsonTool(BuiltinTool): ToolParameter( name="json_path", type=ParameterType.STRING, - description="JSON路径表达式（用于extract、insert、replace、delete、parse操作，如：$.user.name或users[0].name）", + description="JSON路径表达式（用于insert、replace、delete、parse操作，如：$.user.name或users[0].name）", required=False ), ToolParameter( @@ -136,7 +136,7 @@ class JsonTool(BuiltinTool): execution_time = time.time() - start_time return ToolResult.success_result( - data=result, + data=result["result_data"], execution_time=execution_time ) @@ -671,7 +671,8 @@ class JsonTool(BuiltinTool): "success": True, "value": current, "value_type": type(current).__name__, - "value_json": json.dumps(current, indent=2, ensure_ascii=False) if isinstance(current, (dict, list)) else str(current) + "value_json": json.dumps(current, indent=2, ensure_ascii=False) if isinstance(current, (dict, list)) else str(current), + "result_data": json.dumps(current, indent=2, ensure_ascii=False) if isinstance(current, (dict, list)) else str(current) } except (KeyError, IndexError, TypeError) as e: @@ -680,7 +681,8 @@ class JsonTool(BuiltinTool): "json_path": json_path, "success": False, "error": str(e), - "value": None + "value": None, + "result_data": None } def _analyze_json_structure(self, data: Any, depth: int = 0) -> Dict[str, Any]: diff --git a/api/app/core/workflow/nodes/tool/node.py b/api/app/core/workflow/nodes/tool/node.py index a83aea9f..3e79b075 100644 --- a/api/app/core/workflow/nodes/tool/node.py +++ b/api/app/core/workflow/nodes/tool/node.py @@ -1,5 +1,7 @@ +import json import logging import re +import uuid from typing import Any from app.core.workflow.nodes.base_node import BaseNode, WorkflowState @@ -25,10 +27,10 @@ class ToolNode(BaseNode): # 获取租户ID和用户ID tenant_id = self.get_variable("sys.tenant_id", state) user_id = self.get_variable("sys.user_id", state) + workspace_id = self.get_variable("sys.workspace_id", state) # 如果没有租户ID，尝试从工作流ID获取 if not tenant_id: - workspace_id = self.get_variable("sys.workspace_id", state) if workspace_id: from app.repositories.tool_repository import ToolRepository with get_db_read() as db: @@ -63,21 +65,21 @@ class ToolNode(BaseNode): tool_id=self.typed_config.tool_id, parameters=rendered_parameters, tenant_id=tenant_id, - user_id=user_id + user_id=uuid.UUID(user_id), + workspace_id=uuid.UUID(workspace_id) ) if result.success: logger.info(f"节点 {self.node_id} 工具执行成功") return { - "success": True, - "data": result.data, + "data": result.data if isinstance(result.data, str) else json.dumps(result.data, ensure_ascii=False), + "error_code": "", "execution_time": result.execution_time } else: logger.error(f"节点 {self.node_id} 工具执行失败: {result.error}") return { - "success": False, - "data": result.error, + "data": result.error if isinstance(result.error, str) else json.dumps(result.error, ensure_ascii=False), "error_code": result.error_code, "execution_time": result.execution_time } \ No newline at end of file diff --git a/api/app/models/tool_model.py b/api/app/models/tool_model.py index aec74ef7..ccd28693 100644 --- a/api/app/models/tool_model.py +++ b/api/app/models/tool_model.py @@ -211,12 +211,11 @@ class ToolExecution(Base): token_usage = Column(JSON) # 用户信息 - user_id = Column(UUID(as_uuid=True), ForeignKey("users.id"), index=True) + user_id = Column(UUID(as_uuid=True), index=True, nullable=True) workspace_id = Column(UUID(as_uuid=True), ForeignKey("workspaces.id"), nullable=False, index=True) # 关联关系 tool_config = relationship("ToolConfig", back_populates="executions") - user = relationship("User") workspace = relationship("Workspace") def __repr__(self): diff --git a/api/app/schemas/user_memory_schema.py b/api/app/schemas/memory_episodic_schema.py similarity index 67% rename from api/app/schemas/user_memory_schema.py rename to api/app/schemas/memory_episodic_schema.py index 796ad72f..7b3f3d2d 100644 --- a/api/app/schemas/user_memory_schema.py +++ b/api/app/schemas/memory_episodic_schema.py @@ -1,5 +1,5 @@ """ -用户记忆相关的请求和响应模型 +情景记忆的请求和响应模型 """ from pydantic import BaseModel, Field from typing import Optional @@ -28,16 +28,3 @@ class EpisodicMemoryDetailsRequest(BaseModel): end_user_id: str = Field(..., description="终端用户ID") summary_id: str = Field(..., description="情景记忆摘要ID") - - -class ExplicitMemoryOverviewRequest(BaseModel): - """显性记忆总览查询请求""" - - end_user_id: str = Field(..., description="终端用户ID") - - -class ExplicitMemoryDetailsRequest(BaseModel): - """显性记忆详情查询请求""" - - end_user_id: str = Field(..., description="终端用户ID") - memory_id: str = Field(..., description="记忆ID（情景记忆或语义记忆的ID）") diff --git a/api/app/schemas/memory_explicit_schema.py b/api/app/schemas/memory_explicit_schema.py new file mode 100644 index 00000000..c2b51a81 --- /dev/null +++ b/api/app/schemas/memory_explicit_schema.py @@ -0,0 +1,15 @@ +""" +显性记忆的请求和响应模型 +""" +from pydantic import BaseModel, Field + +class ExplicitMemoryOverviewRequest(BaseModel): + """显性记忆总览查询请求""" + + end_user_id: str = Field(..., description="终端用户ID") + +class ExplicitMemoryDetailsRequest(BaseModel): + """显性记忆详情查询请求""" + + end_user_id: str = Field(..., description="终端用户ID") + memory_id: str = Field(..., description="记忆ID（情景记忆或语义记忆的ID）") diff --git a/api/app/services/draft_run_service.py b/api/app/services/draft_run_service.py index 75e87d0a..acea60b7 100644 --- a/api/app/services/draft_run_service.py +++ b/api/app/services/draft_run_service.py @@ -55,7 +55,7 @@ def create_long_term_memory_tool(memory_config: Dict[str, Any], end_user_id: str 长期记忆工具 """ # search_switch = memory_config.get("search_switch", "2") - config_id= memory_config.get("memory_content",'17') + config_id= memory_config.get("memory_content",None) logger.info(f"创建长期记忆工具，配置: end_user_id={end_user_id}, config_id={config_id}, storage_type={storage_type}") @tool(args_schema=LongTermMemoryInput) def long_term_memory(question: str) -> str: @@ -94,7 +94,7 @@ def create_long_term_memory_tool(memory_config: Dict[str, Any], end_user_id: str group_id=end_user_id, message=question, history=[], - search_switch="1", + search_switch="2", config_id=config_id, db=db, storage_type=storage_type, diff --git a/api/app/services/home_page_service.py b/api/app/services/home_page_service.py index 87419cb2..a84a8214 100644 --- a/api/app/services/home_page_service.py +++ b/api/app/services/home_page_service.py @@ -1,6 +1,11 @@ +import json +from pathlib import Path from datetime import datetime, timedelta + +from fastapi import HTTPException from sqlalchemy.orm import Session from uuid import UUID +from typing import Dict, Any from app.repositories.home_page_repository import HomePageRepository from app.schemas.home_page_schema import HomeStatistics, WorkspaceInfo @@ -68,4 +73,69 @@ class HomePageService: ) workspace_list.append(workspace_info) - return workspace_list \ No newline at end of file + return workspace_list + + @staticmethod + def load_version_introduction(version: str) -> Dict[str, Any]: + """ + 从 JSON 文件加载对应版本的介绍 + :param version: 系统版本号（如 "0.2.0"） + :return: 对应版本的详细介绍 + """ + # 1. 定义 JSON 文件路径（使用 Path 处理跨平台路径问题） + json_file_path = Path(__file__).parent.parent / "version_info.json" + # 转换为绝对路径，便于调试 + json_abs_path = json_file_path.resolve() + + try: + # 2. 读取 JSON 文件 + if not json_abs_path.exists(): + return { + "message": f"版本介绍文件不存在：{json_abs_path}", + "codeName": "", + "releaseDate": "", + "upgradePosition": "", + "coreUpgrades": [] + } + + with open(json_abs_path, "r", encoding="utf-8") as f: + changelogs = json.load(f) + + # 3. 匹配对应版本的介绍，若版本不存在返回默认提示 + if version not in changelogs: + return { + "message": f"暂未查询到 {version} 版本的详细介绍", + "codeName": "", + "releaseDate": "", + "upgradePosition": "", + "coreUpgrades": [] + } + return changelogs[version] + + except FileNotFoundError as e: + # 处理文件不存在异常 + return { + "message": f"系统内部错误：{str(e)}", + "codeName": "", + "releaseDate": "", + "upgradePosition": "", + "coreUpgrades": [] + } + except json.JSONDecodeError: + # 处理 JSON 格式错误 + return { + "message": "版本介绍文件格式错误，无法解析 JSON", + "codeName": "", + "releaseDate": "", + "upgradePosition": "", + "coreUpgrades": [] + } + except Exception as e: + # 处理其他未知异常 + return { + "message": f"加载版本介绍失败：{str(e)}", + "codeName": "", + "releaseDate": "", + "upgradePosition": "", + "coreUpgrades": [] + } \ No newline at end of file diff --git a/api/app/services/memory_agent_service.py b/api/app/services/memory_agent_service.py index 71eda535..10f53ed7 100644 --- a/api/app/services/memory_agent_service.py +++ b/api/app/services/memory_agent_service.py @@ -4,7 +4,6 @@ Memory Agent Service Handles business logic for memory agent operations including read/write services, health checks, and message type classification. """ -import datetime import json import os import re @@ -27,7 +26,7 @@ from app.db import get_db_context from app.models.knowledge_model import Knowledge, KnowledgeType from app.repositories.memory_short_repository import ShortTermMemoryRepository from app.repositories.neo4j.neo4j_connector import Neo4jConnector -from app.schemas.memory_config_schema import ConfigurationError, MemoryConfig +from app.schemas.memory_config_schema import ConfigurationError from app.services.memory_config_service import MemoryConfigService from app.services.memory_konwledges_server import ( write_rag, @@ -610,7 +609,7 @@ class MemoryAgentService: reranked_results=raw_results.get('reranked_results',[]) try: statements=[statement['statement'] for statement in reranked_results.get('statements', [])] - except Exception as e: + except Exception: statements=[] statements=list(set(statements)) retrieved_content.append({query:statements}) @@ -832,7 +831,6 @@ class MemoryAgentService: # 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) @@ -1175,19 +1173,21 @@ def get_end_user_connected_config(end_user_id: str, db: Session) -> Dict[str, An 1. 根据 end_user_id 获取用户的 app_id 2. 获取该应用的最新发布版本 3. 从发布版本的 config 字段中提取 memory_config_id + 4. 根据 memory_config_id 查询配置名称 Args: end_user_id: 终端用户ID db: 数据库会话 Returns: - 包含 memory_config_id 和相关信息的字典 + 包含 memory_config_id、config_name 和相关信息的字典 Raises: ValueError: 当终端用户不存在或应用未发布时 """ from app.models.app_release_model import AppRelease from app.models.end_user_model import EndUser + from app.models.data_config_model import DataConfig from sqlalchemy import select logger.info(f"Getting connected config for end_user: {end_user_id}") @@ -1220,13 +1220,158 @@ def get_end_user_connected_config(end_user_id: str, db: Session) -> Dict[str, An memory_obj = config.get('memory', {}) memory_config_id = memory_obj.get('memory_content') if isinstance(memory_obj, dict) else None + # 4. 根据 memory_config_id 查询配置名称 + config_name = None + if memory_config_id: + try: + # memory_config_id 可能是整数或字符串，需要转换 + config_id = int(memory_config_id) if isinstance(memory_config_id, str) else memory_config_id + data_config = db.query(DataConfig).filter(DataConfig.config_id == config_id).first() + if data_config: + config_name = data_config.config_name + logger.debug(f"Found config_name: {config_name} for config_id: {config_id}") + else: + logger.warning(f"DataConfig not found for config_id: {config_id}") + except (ValueError, TypeError) as e: + logger.warning(f"Invalid memory_config_id format: {memory_config_id}, error: {str(e)}") + result = { "end_user_id": str(end_user_id), "app_id": str(app_id), "release_id": str(latest_release.id), "release_version": latest_release.version, - "memory_config_id": memory_config_id + "memory_config_id": memory_config_id, + "memory_config_name": config_name } - logger.info(f"Successfully retrieved connected config: memory_config_id={memory_config_id}") + logger.info(f"Successfully retrieved connected config: memory_config_id={memory_config_id}, config_name={config_name}") + return result + + +def get_end_users_connected_configs_batch(end_user_ids: List[str], db: Session) -> Dict[str, Dict[str, Any]]: + """ + 批量获取多个终端用户关联的记忆配置 + + 通过优化的查询减少数据库往返次数： + 1. 一次性查询所有 end_user 及其 app_id + 2. 批量查询所有相关的 app_release + 3. 批量查询所有相关的 data_config + + Args: + end_user_ids: 终端用户ID列表 + db: 数据库会话 + + Returns: + 字典，key 为 end_user_id，value 为配置信息字典 + 对于查询失败的用户，value 包含 error 字段 + """ + from app.models.app_release_model import AppRelease + from app.models.end_user_model import EndUser + from app.models.data_config_model import DataConfig + from sqlalchemy import select + + logger.info(f"Batch getting connected configs for {len(end_user_ids)} end users") + + result = {} + + # 1. 批量查询所有 end_user 及其 app_id + end_users = db.query(EndUser).filter(EndUser.id.in_(end_user_ids)).all() + + # 构建 end_user_id -> end_user 的映射 + end_user_map = {str(user.id): user for user in end_users} + + # 记录不存在的用户 + for user_id in end_user_ids: + if user_id not in end_user_map: + result[user_id] = { + "end_user_id": user_id, + "memory_config_id": None, + "memory_config_name": None, + "error": f"终端用户不存在: {user_id}" + } + + if not end_users: + logger.warning("No valid end users found") + return result + + # 2. 批量查询所有相关应用的最新发布版本 + app_ids = [user.app_id for user in end_users] + + # 使用子查询找到每个 app 的最新版本 + from sqlalchemy import and_ + + # 查询所有相关的活跃发布版本 + releases = db.query(AppRelease).filter( + and_( + AppRelease.app_id.in_(app_ids), + AppRelease.is_active.is_(True) + ) + ).order_by(AppRelease.app_id, AppRelease.version.desc()).all() + + # 构建 app_id -> latest_release 的映射（每个 app 只保留最新版本） + app_release_map = {} + for release in releases: + app_id_str = str(release.app_id) + if app_id_str not in app_release_map: + app_release_map[app_id_str] = release + + # 3. 收集所有 memory_config_id + memory_config_ids = [] + for release in app_release_map.values(): + config = release.config or {} + memory_obj = config.get('memory', {}) + memory_config_id = memory_obj.get('memory_content') if isinstance(memory_obj, dict) else None + if memory_config_id: + try: + config_id = int(memory_config_id) if isinstance(memory_config_id, str) else memory_config_id + memory_config_ids.append(config_id) + except (ValueError, TypeError): + pass + + # 4. 批量查询所有 data_config + config_name_map = {} + if memory_config_ids: + data_configs = db.query(DataConfig).filter( + DataConfig.config_id.in_(memory_config_ids) + ).all() + config_name_map = {config.config_id: config.config_name for config in data_configs} + + # 5. 组装结果 + for user in end_users: + user_id = str(user.id) + app_id = str(user.app_id) + + # 检查是否有发布版本 + if app_id not in app_release_map: + result[user_id] = { + "end_user_id": user_id, + "memory_config_id": None, + "memory_config_name": None, + "error": f"应用未发布: {app_id}" + } + continue + + release = app_release_map[app_id] + + # 提取 memory_config_id + config = release.config or {} + memory_obj = config.get('memory', {}) + memory_config_id = memory_obj.get('memory_content') if isinstance(memory_obj, dict) else None + + # 获取 config_name + config_name = None + if memory_config_id: + try: + config_id = int(memory_config_id) if isinstance(memory_config_id, str) else memory_config_id + config_name = config_name_map.get(config_id) + except (ValueError, TypeError): + pass + + result[user_id] = { + "end_user_id": user_id, + "memory_config_id": memory_config_id, + "memory_config_name": config_name + } + + logger.info(f"Successfully retrieved batch configs: total={len(result)}, with_config={sum(1 for v in result.values() if v.get('memory_config_id'))}") return result \ No newline at end of file diff --git a/api/app/services/memory_base_service.py b/api/app/services/memory_base_service.py new file mode 100644 index 00000000..6f844ae9 --- /dev/null +++ b/api/app/services/memory_base_service.py @@ -0,0 +1,297 @@ +""" +Memory Base Service + +提供记忆服务的基础功能和共享辅助方法。 +""" + +from datetime import datetime +from typing import Optional + +from app.core.logging_config import get_logger +from app.repositories.neo4j.neo4j_connector import Neo4jConnector +from app.services.emotion_analytics_service import EmotionAnalyticsService + +logger = get_logger(__name__) + + +class MemoryBaseService: + """记忆服务基类，提供共享的辅助方法""" + + def __init__(self): + self.neo4j_connector = Neo4jConnector() + + @staticmethod + def parse_timestamp(timestamp_value) -> Optional[int]: + """ + 将时间戳转换为毫秒级时间戳 + + 支持多种输入格式： + - Neo4j DateTime 对象 + - ISO格式的时间戳字符串 + - Python datetime 对象 + + Args: + timestamp_value: 时间戳值（可以是多种类型） + + Returns: + 毫秒级时间戳，如果解析失败则返回None + """ + if not timestamp_value: + return None + + try: + # 处理 Neo4j DateTime 对象 + if hasattr(timestamp_value, 'to_native'): + dt_object = timestamp_value.to_native() + return int(dt_object.timestamp() * 1000) + + # 处理 Python datetime 对象 + if isinstance(timestamp_value, datetime): + return int(timestamp_value.timestamp() * 1000) + + # 处理字符串格式 + if isinstance(timestamp_value, str): + dt_object = datetime.fromisoformat(timestamp_value.replace("Z", "+00:00")) + return int(dt_object.timestamp() * 1000) + + # 其他情况尝试转换为字符串再解析 + dt_object = datetime.fromisoformat(str(timestamp_value).replace("Z", "+00:00")) + return int(dt_object.timestamp() * 1000) + + except (ValueError, TypeError, AttributeError) as e: + logger.warning(f"无法解析时间戳: {timestamp_value}, error={str(e)}") + return None + + async def extract_episodic_emotion( + self, + summary_id: str, + end_user_id: str + ) -> Optional[str]: + """ + 提取情景记忆的主要情绪 + + 查询MemorySummary节点关联的Statement节点， + 返回emotion_intensity最大的emotion_type。 + + Args: + summary_id: Summary节点的ID + end_user_id: 终端用户ID (group_id) + + Returns: + 最大emotion_intensity对应的emotion_type，如果没有则返回None + """ + try: + query = """ + MATCH (s:MemorySummary) + WHERE elementId(s) = $summary_id AND s.group_id = $group_id + MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) + WHERE stmt.emotion_type IS NOT NULL + AND stmt.emotion_intensity IS NOT NULL + RETURN stmt.emotion_type AS emotion_type, + stmt.emotion_intensity AS emotion_intensity + ORDER BY emotion_intensity DESC + LIMIT 1 + """ + + result = await self.neo4j_connector.execute_query( + query, + summary_id=summary_id, + group_id=end_user_id + ) + + if result and len(result) > 0: + emotion_type = result[0].get("emotion_type") + logger.info(f"成功提取 summary_id={summary_id} 的情绪: {emotion_type}") + return emotion_type + else: + logger.info(f"summary_id={summary_id} 没有情绪信息") + return None + + except Exception as e: + logger.error(f"提取情景记忆情绪时出错: {str(e)}", exc_info=True) + return None + + async def get_episodic_memory_count( + self, + end_user_id: Optional[str] = None + ) -> int: + """ + 获取情景记忆数量 + + 查询 MemorySummary 节点的数量。 + + Args: + end_user_id: 可选的终端用户ID，用于过滤特定用户的节点 + + Returns: + 情景记忆的数量 + """ + try: + if end_user_id: + query = """ + MATCH (n:MemorySummary) + WHERE n.group_id = $group_id + RETURN count(n) as count + """ + result = await self.neo4j_connector.execute_query(query, group_id=end_user_id) + else: + query = """ + MATCH (n:MemorySummary) + RETURN count(n) as count + """ + result = await self.neo4j_connector.execute_query(query) + + count = result[0]["count"] if result and len(result) > 0 else 0 + logger.debug(f"情景记忆数量: {count} (end_user_id={end_user_id})") + return count + + except Exception as e: + logger.error(f"获取情景记忆数量时出错: {str(e)}", exc_info=True) + return 0 + + async def get_explicit_memory_count( + self, + end_user_id: Optional[str] = None + ) -> int: + """ + 获取显性记忆数量 + + 显性记忆 = 情景记忆（MemorySummary）+ 语义记忆（ExtractedEntity with is_explicit_memory=true） + + Args: + end_user_id: 可选的终端用户ID，用于过滤特定用户的节点 + + Returns: + 显性记忆的数量 + """ + try: + # 1. 获取情景记忆数量 + episodic_count = await self.get_episodic_memory_count(end_user_id) + + # 2. 获取语义记忆数量（ExtractedEntity 且 is_explicit_memory = true） + if end_user_id: + semantic_query = """ + MATCH (e:ExtractedEntity) + WHERE e.group_id = $group_id AND e.is_explicit_memory = true + RETURN count(e) as count + """ + semantic_result = await self.neo4j_connector.execute_query( + semantic_query, + group_id=end_user_id + ) + else: + semantic_query = """ + MATCH (e:ExtractedEntity) + WHERE e.is_explicit_memory = true + RETURN count(e) as count + """ + semantic_result = await self.neo4j_connector.execute_query(semantic_query) + + semantic_count = semantic_result[0]["count"] if semantic_result and len(semantic_result) > 0 else 0 + + # 3. 计算总数 + explicit_count = episodic_count + semantic_count + logger.debug( + f"显性记忆数量: {explicit_count} " + f"(情景={episodic_count}, 语义={semantic_count}, end_user_id={end_user_id})" + ) + return explicit_count + + except Exception as e: + logger.error(f"获取显性记忆数量时出错: {str(e)}", exc_info=True) + return 0 + + async def get_emotional_memory_count( + self, + end_user_id: Optional[str] = None, + statement_count_fallback: int = 0 + ) -> int: + """ + 获取情绪记忆数量 + + 通过 EmotionAnalyticsService 获取情绪标签统计总数。 + 如果获取失败或没有指定 end_user_id，使用 statement_count_fallback 作为后备。 + + Args: + end_user_id: 可选的终端用户ID + statement_count_fallback: 后备方案的数量（通常是 statement 节点数量） + + Returns: + 情绪记忆的数量 + """ + try: + if end_user_id: + emotion_service = EmotionAnalyticsService() + + emotion_data = await emotion_service.get_emotion_tags( + end_user_id=end_user_id, + emotion_type=None, + start_date=None, + end_date=None, + limit=10 + ) + emotion_count = emotion_data.get("total_count", 0) + logger.debug(f"情绪记忆数量: {emotion_count} (end_user_id={end_user_id})") + return emotion_count + else: + # 如果没有指定 end_user_id，使用后备方案 + logger.debug(f"情绪记忆数量: {statement_count_fallback} (使用后备方案)") + return statement_count_fallback + + except Exception as e: + logger.warning(f"获取情绪记忆数量失败，使用后备方案: {str(e)}") + return statement_count_fallback + + async def get_forget_memory_count( + self, + end_user_id: Optional[str] = None, + forgetting_threshold: float = 0.3 + ) -> int: + """ + 获取遗忘记忆数量 + + 统计激活值低于遗忘阈值的节点数量（low_activation_nodes）。 + 查询范围包括：Statement、ExtractedEntity、MemorySummary、Chunk 节点。 + + Args: + end_user_id: 可选的终端用户ID，用于过滤特定用户的节点 + forgetting_threshold: 遗忘阈值，默认 0.3 + + Returns: + 遗忘记忆的数量（激活值低于阈值的节点数） + """ + try: + # 构建查询语句 + query = """ + MATCH (n) + WHERE (n:Statement OR n:ExtractedEntity OR n:MemorySummary OR n:Chunk) + """ + + if end_user_id: + query += " AND n.group_id = $group_id" + + query += """ + RETURN sum(CASE WHEN n.activation_value IS NOT NULL AND n.activation_value < $threshold THEN 1 ELSE 0 END) as low_activation_nodes + """ + + # 设置查询参数 + params = {'threshold': forgetting_threshold} + if end_user_id: + params['group_id'] = end_user_id + + # 执行查询 + result = await self.neo4j_connector.execute_query(query, **params) + + # 提取结果 + forget_count = result[0]['low_activation_nodes'] if result and len(result) > 0 else 0 + forget_count = forget_count or 0 # 处理 None 值 + + logger.debug( + f"遗忘记忆数量: {forget_count} " + f"(threshold={forgetting_threshold}, end_user_id={end_user_id})" + ) + return forget_count + + except Exception as e: + logger.error(f"获取遗忘记忆数量时出错: {str(e)}", exc_info=True) + return 0 diff --git a/api/app/services/memory_episodic_service.py b/api/app/services/memory_episodic_service.py new file mode 100644 index 00000000..12eeff6e --- /dev/null +++ b/api/app/services/memory_episodic_service.py @@ -0,0 +1,405 @@ +""" +Episodic Memory Service + +处理情景记忆相关的业务逻辑，包括情景记忆总览、详情查询等。 +""" + +from datetime import datetime, timedelta +from typing import Any, Dict, List, Optional, Tuple + +import pytz +from app.core.logging_config import get_logger +from app.services.memory_base_service import MemoryBaseService + +logger = get_logger(__name__) + + +class MemoryEpisodicService(MemoryBaseService): + """情景记忆服务类""" + + def __init__(self): + super().__init__() + logger.info("MemoryEpisodicService initialized") + + async def _get_title_and_type( + self, + summary_id: str, + end_user_id: str + ) -> Tuple[str, str]: + """ + 读取情景记忆的标题(title)和类型(type) + + 仅负责读取已存在的title和type，不进行生成 + title从name属性读取，type从memory_type属性读取 + + Args: + summary_id: Summary节点的ID + end_user_id: 终端用户ID (group_id) + + Returns: + (标题, 类型)元组，如果不存在则返回默认值 + """ + try: + # 查询Summary节点的name(作为title)和memory_type(作为type) + query = """ + MATCH (s:MemorySummary) + WHERE elementId(s) = $summary_id AND s.group_id = $group_id + RETURN s.name AS title, s.memory_type AS type + """ + + result = await self.neo4j_connector.execute_query( + query, + summary_id=summary_id, + group_id=end_user_id + ) + + if not result or len(result) == 0: + logger.warning(f"未找到 summary_id={summary_id} 的节点") + return ("未知标题", "其他") + + record = result[0] + title = record.get("title") or "未命名" + episodic_type = record.get("type") or "其他" + + return (title, episodic_type) + + except Exception as e: + logger.error(f"读取标题和类型时出错: {str(e)}", exc_info=True) + return ("错误", "其他") + + async def _extract_involved_objects( + self, + summary_id: str, + end_user_id: str + ) -> List[str]: + """ + 提取情景记忆涉及的前3个最重要实体 + + Args: + summary_id: Summary节点的ID + end_user_id: 终端用户ID (group_id) + + Returns: + 前3个实体的name属性列表 + """ + try: + # 查询Summary节点指向的Statement节点,再查询Statement指向的ExtractedEntity节点 + # 按activation_value降序排序,返回前3个 + query = """ + MATCH (s:MemorySummary) + WHERE elementId(s) = $summary_id AND s.group_id = $group_id + MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) + MATCH (stmt)-[:REFERENCES_ENTITY]->(entity:ExtractedEntity) + WHERE entity.activation_value IS NOT NULL + RETURN DISTINCT entity.name AS name, entity.activation_value AS activation + ORDER BY activation DESC + LIMIT 3 + """ + + result = await self.neo4j_connector.execute_query( + query, + summary_id=summary_id, + group_id=end_user_id + ) + + # 提取实体名称 + involved_objects = [record["name"] for record in result if record.get("name")] + + logger.info(f"成功提取 summary_id={summary_id} 的涉及对象: {involved_objects}") + + return involved_objects + + except Exception as e: + logger.error(f"提取涉及对象时出错: {str(e)}", exc_info=True) + return [] + + async def _extract_content_records( + self, + summary_id: str, + end_user_id: str + ) -> List[str]: + """ + 提取情景记忆的内容记录 + + Args: + summary_id: Summary节点的ID + end_user_id: 终端用户ID (group_id) + + Returns: + 所有Statement节点的statement属性内容列表 + """ + try: + # 查询Summary节点指向的所有Statement节点 + query = """ + MATCH (s:MemorySummary) + WHERE elementId(s) = $summary_id AND s.group_id = $group_id + MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) + WHERE stmt.statement IS NOT NULL AND stmt.statement <> '' + RETURN stmt.statement AS statement + """ + + result = await self.neo4j_connector.execute_query( + query, + summary_id=summary_id, + group_id=end_user_id + ) + + # 提取statement内容 + content_records = [record["statement"] for record in result if record.get("statement")] + + logger.info(f"成功提取 summary_id={summary_id} 的内容记录,共 {len(content_records)} 条") + + return content_records + + except Exception as e: + logger.error(f"提取内容记录时出错: {str(e)}", exc_info=True) + return [] + + def _calculate_time_filter(self, time_range: str) -> Optional[str]: + """ + 根据时间范围计算过滤的起始时间 + + Args: + time_range: 时间范围 (all/today/this_week/this_month) + + Returns: + ISO格式的时间字符串，如果是"all"则返回None + """ + if time_range == "all": + return None + + # 获取当前时间（UTC） + now = datetime.now(pytz.UTC) + + if time_range == "today": + # 今天的开始时间（00:00:00） + start_time = now.replace(hour=0, minute=0, second=0, microsecond=0) + elif time_range == "this_week": + # 本周的开始时间（周一00:00:00） + days_since_monday = now.weekday() + start_time = (now - timedelta(days=days_since_monday)).replace( + hour=0, minute=0, second=0, microsecond=0 + ) + elif time_range == "this_month": + # 本月的开始时间（1号00:00:00） + start_time = now.replace(day=1, hour=0, minute=0, second=0, microsecond=0) + else: + return None + + # 返回ISO格式字符串 + return start_time.isoformat() + + async def get_episodic_memory_overview( + self, + end_user_id: str, + time_range: str = "all", + episodic_type: str = "all", + title_keyword: Optional[str] = None + ) -> Dict[str, Any]: + """ + 获取情景记忆总览信息 + + Args: + end_user_id: 终端用户ID + time_range: 时间范围筛选 + episodic_type: 情景类型筛选 + title_keyword: 标题关键词（可选，用于模糊搜索） + """ + try: + logger.info( + f"开始查询 end_user_id={end_user_id} 的情景记忆总览, " + f"time_range={time_range}, episodic_type={episodic_type}, title_keyword={title_keyword}" + ) + + # 1. 先查询所有情景记忆的总数（不受筛选条件限制） + total_all_query = """ + MATCH (s:MemorySummary) + WHERE s.group_id = $group_id + RETURN count(s) AS total_all + """ + total_all_result = await self.neo4j_connector.execute_query( + total_all_query, + group_id=end_user_id + ) + total_all = total_all_result[0]["total_all"] if total_all_result else 0 + + # 2. 计算时间范围的起始时间戳 + time_filter = self._calculate_time_filter(time_range) + + # 3. 构建Cypher查询 + query = """ + MATCH (s:MemorySummary) + WHERE s.group_id = $group_id + """ + + # 添加时间范围过滤 + if time_filter: + query += " AND s.created_at >= $time_filter" + + # 添加标题关键词过滤（如果提供了title_keyword） + if title_keyword: + query += " AND toLower(s.name) CONTAINS toLower($title_keyword)" + + query += """ + RETURN elementId(s) AS id, + s.created_at AS created_at, + s.memory_type AS type, + s.name AS title + ORDER BY s.created_at DESC + """ + + params = {"group_id": end_user_id} + if time_filter: + params["time_filter"] = time_filter + if title_keyword: + params["title_keyword"] = title_keyword + + result = await self.neo4j_connector.execute_query(query, **params) + + # 4. 如果没有数据，返回空列表 + if not result: + logger.info(f"end_user_id={end_user_id} 没有情景记忆数据") + return { + "total": 0, + "total_all": total_all, + "episodic_memories": [] + } + + # 5. 对每个节点读取标题和类型，并应用类型筛选 + episodic_memories = [] + for record in result: + summary_id = record["id"] + created_at_str = record.get("created_at") + memory_type = record.get("type", "其他") + title = record.get("title") or "未命名" # 直接从查询结果获取标题 + + # 应用情景类型筛选 + if episodic_type != "all": + # 检查类型是否匹配 + # 注意：Neo4j 中存储的 memory_type 现在应该是英文格式（如 "conversation", "project_work"） + # 但为了兼容旧数据，我们也支持中文格式的匹配 + type_mapping = { + "conversation": "对话", + "project_work": "项目/工作", + "learning": "学习", + "decision": "决策", + "important_event": "重要事件" + } + + # 获取对应的中文类型（用于兼容旧数据） + chinese_type = type_mapping.get(episodic_type) + + # 检查类型是否匹配（支持新的英文格式和旧的中文格式） + if memory_type != episodic_type and memory_type != chinese_type: + continue + + # 使用基类方法转换时间戳 + created_at_timestamp = self.parse_timestamp(created_at_str) + + episodic_memories.append({ + "id": summary_id, + "title": title, + "type": memory_type, + "created_at": created_at_timestamp + }) + + logger.info( + f"成功获取 end_user_id={end_user_id} 的情景记忆总览," + f"筛选后 {len(episodic_memories)} 条，总共 {total_all} 条" + ) + + return { + "total": len(episodic_memories), + "total_all": total_all, + "episodic_memories": episodic_memories + } + + except Exception as e: + logger.error(f"获取情景记忆总览时出错: {str(e)}", exc_info=True) + raise + + async def get_episodic_memory_details( + self, + end_user_id: str, + summary_id: str + ) -> Dict[str, Any]: + """ + 获取单个情景记忆的详细信息 + + """ + try: + logger.info(f"开始查询 end_user_id={end_user_id}, summary_id={summary_id} 的情景记忆详情") + + # 1. 查询指定的MemorySummary节点 + query = """ + MATCH (s:MemorySummary) + WHERE elementId(s) = $summary_id AND s.group_id = $group_id + RETURN elementId(s) AS id, s.created_at AS created_at + """ + + result = await self.neo4j_connector.execute_query( + query, + summary_id=summary_id, + group_id=end_user_id + ) + + # 2. 如果节点不存在，返回错误 + if not result or len(result) == 0: + logger.warning(f"未找到 summary_id={summary_id} 的情景记忆") + raise ValueError(f"情景记忆不存在: summary_id={summary_id}") + + # 3. 获取基本信息 + record = result[0] + created_at_str = record.get("created_at") + + # 使用基类方法转换时间戳 + created_at_timestamp = self.parse_timestamp(created_at_str) + + # 4. 调用_get_title_and_type读取标题和类型 + title, episodic_type = await self._get_title_and_type( + summary_id=summary_id, + end_user_id=end_user_id + ) + + # 5. 调用_extract_involved_objects提取涉及对象 + involved_objects = await self._extract_involved_objects( + summary_id=summary_id, + end_user_id=end_user_id + ) + + # 6. 调用_extract_content_records提取内容记录 + content_records = await self._extract_content_records( + summary_id=summary_id, + end_user_id=end_user_id + ) + + # 7. 使用基类方法提取情绪 + emotion = await self.extract_episodic_emotion( + summary_id=summary_id, + end_user_id=end_user_id + ) + + # 8. 返回完整的详情信息 + details = { + "id": summary_id, + "created_at": created_at_timestamp, + "involved_objects": involved_objects, + "episodic_type": episodic_type, + "content_records": content_records, + "emotion": emotion + } + + logger.info(f"成功获取 summary_id={summary_id} 的情景记忆详情") + + return details + + except ValueError: + # 重新抛出ValueError，让Controller层处理 + raise + except Exception as e: + logger.error(f"获取情景记忆详情时出错: {str(e)}", exc_info=True) + raise + + +# 创建全局服务实例（供控制器层使用） +memory_episodic_service = MemoryEpisodicService() diff --git a/api/app/services/memory_explicit_service.py b/api/app/services/memory_explicit_service.py new file mode 100644 index 00000000..713215c3 --- /dev/null +++ b/api/app/services/memory_explicit_service.py @@ -0,0 +1,274 @@ +""" +显性记忆服务 + +处理显性记忆相关的业务逻辑，包括情景记忆和语义记忆的查询。 +""" + +from typing import Any, Dict + +from app.core.logging_config import get_logger +from app.services.memory_base_service import MemoryBaseService + +logger = get_logger(__name__) + + +class MemoryExplicitService(MemoryBaseService): + """显性记忆服务类""" + + def __init__(self): + super().__init__() + logger.info("MemoryExplicitService initialized") + + async def get_explicit_memory_overview( + self, + end_user_id: str + ) -> Dict[str, Any]: + """ + 获取显性记忆总览信息 + + 返回两部分： + 1. 情景记忆（episodic_memories）- 来自MemorySummary节点 + 2. 语义记忆（semantic_memories）- 来自ExtractedEntity节点（is_explicit_memory=true） + + Args: + end_user_id: 终端用户ID + + Returns: + { + "total": int, + "episodic_memories": [ + { + "id": str, + "title": str, + "content": str, + "created_at": int + } + ], + "semantic_memories": [ + { + "id": str, + "name": str, + "entity_type": str, + "core_definition": str + } + ] + } + """ + try: + logger.info(f"开始查询 end_user_id={end_user_id} 的显性记忆总览（情景记忆+语义记忆）") + + # ========== 1. 查询情景记忆（MemorySummary节点） ========== + episodic_query = """ + MATCH (s:MemorySummary) + WHERE s.group_id = $group_id + RETURN elementId(s) AS id, + s.name AS title, + s.content AS content, + s.created_at AS created_at + ORDER BY s.created_at DESC + """ + + episodic_result = await self.neo4j_connector.execute_query( + episodic_query, + group_id=end_user_id + ) + + # 处理情景记忆数据 + episodic_memories = [] + if episodic_result: + for record in episodic_result: + summary_id = record["id"] + title = record.get("title") or "未命名" + content = record.get("content") or "" + created_at_str = record.get("created_at") + + # 使用基类方法转换时间戳 + created_at_timestamp = self.parse_timestamp(created_at_str) + + # 注意：总览接口不返回 emotion 字段 + episodic_memories.append({ + "id": summary_id, + "title": title, + "content": content, + "created_at": created_at_timestamp + }) + + # ========== 2. 查询语义记忆（ExtractedEntity节点） ========== + semantic_query = """ + MATCH (e:ExtractedEntity) + WHERE e.group_id = $group_id + AND e.is_explicit_memory = true + RETURN elementId(e) AS id, + e.name AS name, + e.entity_type AS entity_type, + e.description AS core_definition + ORDER BY e.name ASC + """ + + semantic_result = await self.neo4j_connector.execute_query( + semantic_query, + group_id=end_user_id + ) + + # 处理语义记忆数据 + semantic_memories = [] + if semantic_result: + for record in semantic_result: + entity_id = record["id"] + name = record.get("name") or "未命名" + entity_type = record.get("entity_type") or "未分类" + core_definition = record.get("core_definition") or "" + + # 注意：总览接口不返回 detailed_notes 和 created_at 字段 + semantic_memories.append({ + "id": entity_id, + "name": name, + "entity_type": entity_type, + "core_definition": core_definition + }) + + # ========== 3. 返回结果 ========== + total_count = len(episodic_memories) + len(semantic_memories) + + logger.info( + f"成功获取 end_user_id={end_user_id} 的显性记忆总览，" + f"情景记忆={len(episodic_memories)} 条，语义记忆={len(semantic_memories)} 条，" + f"总计 {total_count} 条" + ) + + return { + "total": total_count, + "episodic_memories": episodic_memories, + "semantic_memories": semantic_memories + } + + except Exception as e: + logger.error(f"获取显性记忆总览时出错: {str(e)}", exc_info=True) + raise + + async def get_explicit_memory_details( + self, + end_user_id: str, + memory_id: str + ) -> Dict[str, Any]: + """ + 获取显性记忆详情 + + 根据 memory_id 查询情景记忆或语义记忆的详细信息。 + 先尝试查询情景记忆，如果找不到再查询语义记忆。 + + Args: + end_user_id: 终端用户ID + memory_id: 记忆ID（可以是情景记忆或语义记忆的ID） + + Returns: + 情景记忆返回： + { + "memory_type": "episodic", + "title": str, + "content": str, + "emotion": Dict, + "created_at": int + } + + 语义记忆返回： + { + "memory_type": "semantic", + "name": str, + "core_definition": str, + "detailed_notes": str, + "created_at": int + } + + Raises: + ValueError: 当记忆不存在时 + """ + try: + logger.info(f"开始查询显性记忆详情: end_user_id={end_user_id}, memory_id={memory_id}") + + # ========== 1. 先尝试查询情景记忆 ========== + episodic_query = """ + MATCH (s:MemorySummary) + WHERE elementId(s) = $memory_id AND s.group_id = $group_id + RETURN s.name AS title, + s.content AS content, + s.created_at AS created_at + """ + + episodic_result = await self.neo4j_connector.execute_query( + episodic_query, + memory_id=memory_id, + group_id=end_user_id + ) + + if episodic_result and len(episodic_result) > 0: + record = episodic_result[0] + title = record.get("title") or "未命名" + content = record.get("content") or "" + created_at_str = record.get("created_at") + + # 使用基类方法转换时间戳 + created_at_timestamp = self.parse_timestamp(created_at_str) + + # 使用基类方法获取情绪信息 + emotion = await self.extract_episodic_emotion( + summary_id=memory_id, + end_user_id=end_user_id + ) + + logger.info(f"成功获取情景记忆详情: memory_id={memory_id}") + return { + "memory_type": "episodic", + "title": title, + "content": content, + "emotion": emotion, + "created_at": created_at_timestamp + } + + # ========== 2. 如果不是情景记忆，尝试查询语义记忆 ========== + semantic_query = """ + MATCH (e:ExtractedEntity) + WHERE elementId(e) = $memory_id + AND e.group_id = $group_id + AND e.is_explicit_memory = true + RETURN e.name AS name, + e.description AS core_definition, + e.example AS detailed_notes, + e.created_at AS created_at + """ + + semantic_result = await self.neo4j_connector.execute_query( + semantic_query, + memory_id=memory_id, + group_id=end_user_id + ) + + if semantic_result and len(semantic_result) > 0: + record = semantic_result[0] + name = record.get("name") or "未命名" + core_definition = record.get("core_definition") or "" + detailed_notes = record.get("detailed_notes") or "" + created_at_str = record.get("created_at") + + # 使用基类方法转换时间戳 + created_at_timestamp = self.parse_timestamp(created_at_str) + + logger.info(f"成功获取语义记忆详情: memory_id={memory_id}") + return { + "memory_type": "semantic", + "name": name, + "core_definition": core_definition, + "detailed_notes": detailed_notes, + "created_at": created_at_timestamp + } + + # ========== 3. 两种记忆都找不到 ========== + logger.warning(f"记忆不存在: memory_id={memory_id}, end_user_id={end_user_id}") + raise ValueError(f"记忆不存在: memory_id={memory_id}") + + except ValueError: + # 重新抛出 ValueError（记忆不存在） + raise + except Exception as e: + logger.error(f"获取显性记忆详情时出错: {str(e)}", exc_info=True) + raise diff --git a/api/app/services/user_memory_service.py b/api/app/services/user_memory_service.py index b77a4ada..67a6ab2c 100644 --- a/api/app/services/user_memory_service.py +++ b/api/app/services/user_memory_service.py @@ -15,6 +15,7 @@ from app.core.memory.utils.llm.llm_utils import MemoryClientFactory from app.db import get_db_context from app.repositories.end_user_repository import EndUserRepository from app.repositories.neo4j.neo4j_connector import Neo4jConnector +from app.services.memory_base_service import MemoryBaseService from app.services.memory_config_service import MemoryConfigService from pydantic import BaseModel, Field from sqlalchemy.orm import Session @@ -883,866 +884,6 @@ class UserMemoryService: "failed": failed, "errors": errors + [{"error": f"批量处理失败: {str(e)}"}] } - - async def _get_title_and_type( - self, - summary_id: str, - end_user_id: str - ) -> Tuple[str, str]: - """ - 读取情景记忆的标题(title)和类型(type) - - 仅负责读取已存在的title和type，不进行生成 - title从name属性读取，type从memory_type属性读取 - - Args: - summary_id: Summary节点的ID - end_user_id: 终端用户ID (group_id) - - Returns: - (标题, 类型)元组，如果不存在则返回默认值 - """ - try: - # 查询Summary节点的name(作为title)和memory_type(作为type) - query = """ - MATCH (s:MemorySummary) - WHERE elementId(s) = $summary_id AND s.group_id = $group_id - RETURN s.name AS title, s.memory_type AS type - """ - - result = await self.neo4j_connector.execute_query( - query, - summary_id=summary_id, - group_id=end_user_id - ) - - if not result or len(result) == 0: - logger.warning(f"未找到 summary_id={summary_id} 的节点") - return ("未知标题", "其他") - - record = result[0] - title = record.get("title") or "未命名" - episodic_type = record.get("type") or "其他" - - return (title, episodic_type) - - except Exception as e: - logger.error(f"读取标题和类型时出错: {str(e)}", exc_info=True) - return ("错误", "其他") - - @staticmethod - async def generate_title_and_type_for_summary( - content: str, - end_user_id: str - ) -> Tuple[str, str]: - """ - 为MemorySummary生成标题和类型（静态方法，用于创建节点时调用） - - 此方法应该在创建MemorySummary节点时调用，生成title和type - - Args: - content: Summary的内容文本 - end_user_id: 终端用户ID (group_id) - - Returns: - (标题, 类型)元组 - """ - from app.core.memory.utils.prompt.prompt_utils import render_episodic_title_and_type_prompt - import json - - # 定义有效的类型集合 - VALID_TYPES = { - "conversation", # 对话 - "project_work", # 项目/工作 - "learning", # 学习 - "decision", # 决策 - "important_event" # 重要事件 - } - DEFAULT_TYPE = "conversation" # 默认类型 - - try: - if not content: - logger.warning("content为空，无法生成标题和类型") - return ("空内容", DEFAULT_TYPE) - - # 1. 渲染Jinja2提示词模板 - prompt = await render_episodic_title_and_type_prompt(content) - - # 2. 调用LLM生成标题和类型 - llm_client = _get_llm_client_for_user(end_user_id) - messages = [ - {"role": "user", "content": prompt} - ] - - response = await llm_client.chat(messages=messages) - - # 3. 解析LLM响应 - content_response = response.content - if isinstance(content_response, list): - if len(content_response) > 0: - if isinstance(content_response[0], dict): - text = content_response[0].get('text', content_response[0].get('content', str(content_response[0]))) - full_response = str(text) - else: - full_response = str(content_response[0]) - else: - full_response = "" - elif isinstance(content_response, dict): - full_response = str(content_response.get('text', content_response.get('content', str(content_response)))) - else: - full_response = str(content_response) if content_response is not None else "" - - # 4. 解析JSON响应 - try: - # 尝试从响应中提取JSON - # 移除可能的markdown代码块标记 - json_str = full_response.strip() - if json_str.startswith("```json"): - json_str = json_str[7:] - if json_str.startswith("```"): - json_str = json_str[3:] - if json_str.endswith("```"): - json_str = json_str[:-3] - json_str = json_str.strip() - - result_data = json.loads(json_str) - title = result_data.get("title", "未知标题") - episodic_type_raw = result_data.get("type", DEFAULT_TYPE) - - # 5. 校验和归一化类型 - # 将类型转换为小写并去除空格 - episodic_type_normalized = str(episodic_type_raw).lower().strip() - - # 检查是否在有效类型集合中 - if episodic_type_normalized in VALID_TYPES: - episodic_type = episodic_type_normalized - else: - # 尝试映射常见的中文类型到英文 - type_mapping = { - "对话": "conversation", - "项目": "project_work", - "工作": "project_work", - "项目/工作": "project_work", - "学习": "learning", - "决策": "decision", - "重要事件": "important_event", - "事件": "important_event" - } - episodic_type = type_mapping.get(episodic_type_raw, DEFAULT_TYPE) - logger.warning( - f"LLM返回的类型 '{episodic_type_raw}' 不在有效集合中，" - f"已归一化为 '{episodic_type}'" - ) - - logger.info(f"成功生成标题和类型: title={title}, type={episodic_type}") - return (title, episodic_type) - - except json.JSONDecodeError: - logger.error(f"无法解析LLM响应为JSON: {full_response}") - return ("解析失败", DEFAULT_TYPE) - - except Exception as e: - logger.error(f"生成标题和类型时出错: {str(e)}", exc_info=True) - return ("错误", DEFAULT_TYPE) - - async def _extract_involved_objects( - self, - summary_id: str, - end_user_id: str - ) -> List[str]: - """ - 提取情景记忆涉及的前3个最重要实体 - - Args: - summary_id: Summary节点的ID - end_user_id: 终端用户ID (group_id) - - Returns: - 前3个实体的name属性列表 - """ - try: - # 查询Summary节点指向的Statement节点,再查询Statement指向的ExtractedEntity节点 - # 按activation_value降序排序,返回前3个 - query = """ - MATCH (s:MemorySummary) - WHERE elementId(s) = $summary_id AND s.group_id = $group_id - MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) - MATCH (stmt)-[:REFERENCES_ENTITY]->(entity:ExtractedEntity) - WHERE entity.activation_value IS NOT NULL - RETURN DISTINCT entity.name AS name, entity.activation_value AS activation - ORDER BY activation DESC - LIMIT 3 - """ - - result = await self.neo4j_connector.execute_query( - query, - summary_id=summary_id, - group_id=end_user_id - ) - - # 提取实体名称 - involved_objects = [record["name"] for record in result if record.get("name")] - - logger.info(f"成功提取 summary_id={summary_id} 的涉及对象: {involved_objects}") - - return involved_objects - - except Exception as e: - logger.error(f"提取涉及对象时出错: {str(e)}", exc_info=True) - return [] - - async def _extract_content_records( - self, - summary_id: str, - end_user_id: str - ) -> List[str]: - """ - 提取情景记忆的内容记录 - - Args: - summary_id: Summary节点的ID - end_user_id: 终端用户ID (group_id) - - Returns: - 所有Statement节点的statement属性内容列表 - """ - try: - # 查询Summary节点指向的所有Statement节点 - query = """ - MATCH (s:MemorySummary) - WHERE elementId(s) = $summary_id AND s.group_id = $group_id - MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) - WHERE stmt.statement IS NOT NULL AND stmt.statement <> '' - RETURN stmt.statement AS statement - """ - - result = await self.neo4j_connector.execute_query( - query, - summary_id=summary_id, - group_id=end_user_id - ) - - # 提取statement内容 - content_records = [record["statement"] for record in result if record.get("statement")] - - logger.info(f"成功提取 summary_id={summary_id} 的内容记录,共 {len(content_records)} 条") - - return content_records - - except Exception as e: - logger.error(f"提取内容记录时出错: {str(e)}", exc_info=True) - return [] - - async def _extract_episodic_emotion( - self, - summary_id: str, - end_user_id: str - ) -> Optional[str]: - """ - 提取情景记忆的主要情绪 - - Args: - summary_id: Summary节点的ID - end_user_id: 终端用户ID (group_id) - - Returns: - 最大emotion_intensity对应的emotion_type,如果没有则返回None - """ - try: - # 查询Summary节点指向的所有Statement节点 - # 筛选具有emotion_type属性的节点 - # 按emotion_intensity降序排序,返回第一个 - query = """ - MATCH (s:MemorySummary) - WHERE elementId(s) = $summary_id AND s.group_id = $group_id - MATCH (s)-[:DERIVED_FROM_STATEMENT]->(stmt:Statement) - WHERE stmt.emotion_type IS NOT NULL - AND stmt.emotion_intensity IS NOT NULL - RETURN stmt.emotion_type AS emotion_type, - stmt.emotion_intensity AS emotion_intensity - ORDER BY emotion_intensity DESC - LIMIT 1 - """ - - result = await self.neo4j_connector.execute_query( - query, - summary_id=summary_id, - group_id=end_user_id - ) - - # 提取emotion_type - if result and len(result) > 0: - emotion_type = result[0].get("emotion_type") - logger.info(f"成功提取 summary_id={summary_id} 的情绪: {emotion_type}") - return emotion_type - else: - logger.info(f"summary_id={summary_id} 没有情绪信息") - return None - - except Exception as e: - logger.error(f"提取情景记忆情绪时出错: {str(e)}", exc_info=True) - return None - - async def get_episodic_memory_overview( - self, - db: Session, - end_user_id: str, - time_range: str = "all", - episodic_type: str = "all", - title_keyword: Optional[str] = None - ) -> Dict[str, Any]: - """ - 获取情景记忆总览信息 - - Args: - db: 数据库会话 - end_user_id: 终端用户ID - time_range: 时间范围筛选 - episodic_type: 情景类型筛选 - title_keyword: 标题关键词（可选，用于模糊搜索） - """ - try: - logger.info( - f"开始查询 end_user_id={end_user_id} 的情景记忆总览, " - f"time_range={time_range}, episodic_type={episodic_type}, title_keyword={title_keyword}" - ) - - # 1. 先查询所有情景记忆的总数（不受筛选条件限制） - total_all_query = """ - MATCH (s:MemorySummary) - WHERE s.group_id = $group_id - RETURN count(s) AS total_all - """ - total_all_result = await self.neo4j_connector.execute_query( - total_all_query, - group_id=end_user_id - ) - total_all = total_all_result[0]["total_all"] if total_all_result else 0 - - # 2. 计算时间范围的起始时间戳 - time_filter = self._calculate_time_filter(time_range) - - # 3. 构建Cypher查询 - query = """ - MATCH (s:MemorySummary) - WHERE s.group_id = $group_id - """ - - # 添加时间范围过滤 - if time_filter: - query += " AND s.created_at >= $time_filter" - - # 添加标题关键词过滤（如果提供了title_keyword） - if title_keyword: - query += " AND toLower(s.name) CONTAINS toLower($title_keyword)" - - query += """ - RETURN elementId(s) AS id, - s.created_at AS created_at, - s.memory_type AS type, - s.name AS title - ORDER BY s.created_at DESC - """ - - params = {"group_id": end_user_id} - if time_filter: - params["time_filter"] = time_filter - if title_keyword: - params["title_keyword"] = title_keyword - - result = await self.neo4j_connector.execute_query(query, **params) - - # 4. 如果没有数据，返回空列表 - if not result: - logger.info(f"end_user_id={end_user_id} 没有情景记忆数据") - return { - "total": 0, - "total_all": total_all, - "episodic_memories": [] - } - - # 5. 对每个节点读取标题和类型，并应用类型筛选 - episodic_memories = [] - for record in result: - summary_id = record["id"] - created_at_str = record.get("created_at") - memory_type = record.get("type", "其他") - title = record.get("title") or "未命名" # 直接从查询结果获取标题 - - # 应用情景类型筛选 - if episodic_type != "all": - # 检查类型是否匹配 - # 注意：Neo4j 中存储的 memory_type 现在应该是英文格式（如 "conversation", "project_work"） - # 但为了兼容旧数据，我们也支持中文格式的匹配 - type_mapping = { - "conversation": "对话", - "project_work": "项目/工作", - "learning": "学习", - "decision": "决策", - "important_event": "重要事件" - } - - # 获取对应的中文类型（用于兼容旧数据） - chinese_type = type_mapping.get(episodic_type) - - # 检查类型是否匹配（支持新的英文格式和旧的中文格式） - if memory_type != episodic_type and memory_type != chinese_type: - continue - - # 转换时间戳 - created_at_timestamp = None - if created_at_str: - try: - from datetime import datetime - dt_object = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) - created_at_timestamp = int(dt_object.timestamp() * 1000) - except (ValueError, TypeError, AttributeError) as e: - logger.warning(f"无法解析时间戳: {created_at_str}, error={str(e)}") - - episodic_memories.append({ - "id": summary_id, - "title": title, - "type": memory_type, - "created_at": created_at_timestamp - }) - - logger.info( - f"成功获取 end_user_id={end_user_id} 的情景记忆总览," - f"筛选后 {len(episodic_memories)} 条，总共 {total_all} 条" - ) - - return { - "total": len(episodic_memories), - "total_all": total_all, - "episodic_memories": episodic_memories - } - - except Exception as e: - logger.error(f"获取情景记忆总览时出错: {str(e)}", exc_info=True) - raise - - def _calculate_time_filter(self, time_range: str) -> Optional[str]: - """ - 根据时间范围计算过滤的起始时间 - - Args: - time_range: 时间范围 (all/today/this_week/this_month) - - Returns: - ISO格式的时间字符串，如果是"all"则返回None - """ - from datetime import datetime, timedelta - import pytz - - if time_range == "all": - return None - - # 获取当前时间（UTC） - now = datetime.now(pytz.UTC) - - if time_range == "today": - # 今天的开始时间（00:00:00） - start_time = now.replace(hour=0, minute=0, second=0, microsecond=0) - elif time_range == "this_week": - # 本周的开始时间（周一00:00:00） - days_since_monday = now.weekday() - start_time = (now - timedelta(days=days_since_monday)).replace( - hour=0, minute=0, second=0, microsecond=0 - ) - elif time_range == "this_month": - # 本月的开始时间（1号00:00:00） - start_time = now.replace(day=1, hour=0, minute=0, second=0, microsecond=0) - else: - return None - - # 返回ISO格式字符串 - return start_time.isoformat() - - async def get_episodic_memory_details( - self, - db: Session, - end_user_id: str, - summary_id: str - ) -> Dict[str, Any]: - """ - 获取单个情景记忆的详细信息 - - """ - try: - logger.info(f"开始查询 end_user_id={end_user_id}, summary_id={summary_id} 的情景记忆详情") - - # 1. 查询指定的MemorySummary节点 - query = """ - MATCH (s:MemorySummary) - WHERE elementId(s) = $summary_id AND s.group_id = $group_id - RETURN elementId(s) AS id, s.created_at AS created_at - """ - - result = await self.neo4j_connector.execute_query( - query, - summary_id=summary_id, - group_id=end_user_id - ) - - # 2. 如果节点不存在，返回错误 - if not result or len(result) == 0: - logger.warning(f"未找到 summary_id={summary_id} 的情景记忆") - raise ValueError(f"情景记忆不存在: summary_id={summary_id}") - - # 3. 获取基本信息 - record = result[0] - created_at_str = record.get("created_at") - - # 转换时间戳 - created_at_timestamp = None - if created_at_str: - try: - from datetime import datetime - dt_object = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) - created_at_timestamp = int(dt_object.timestamp() * 1000) - except (ValueError, TypeError, AttributeError) as e: - logger.warning(f"无法解析时间戳: {created_at_str}, error={str(e)}") - - # 4. 调用_get_title_and_type读取标题和类型 - title, episodic_type = await self._get_title_and_type( - summary_id=summary_id, - end_user_id=end_user_id - ) - - # 5. 调用_extract_involved_objects提取涉及对象 - involved_objects = await self._extract_involved_objects( - summary_id=summary_id, - end_user_id=end_user_id - ) - - # 6. 调用_extract_content_records提取内容记录 - content_records = await self._extract_content_records( - summary_id=summary_id, - end_user_id=end_user_id - ) - - # 7. 调用_extract_episodic_emotion提取情绪 - emotion = await self._extract_episodic_emotion( - summary_id=summary_id, - end_user_id=end_user_id - ) - - # 8. 返回完整的详情信息 - details = { - "id": summary_id, - "created_at": created_at_timestamp, - "involved_objects": involved_objects, - "episodic_type": episodic_type, - "content_records": content_records, - "emotion": emotion - } - - logger.info(f"成功获取 summary_id={summary_id} 的情景记忆详情") - - return details - - except ValueError: - # 重新抛出ValueError，让Controller层处理 - raise - except Exception as e: - logger.error(f"获取情景记忆详情时出错: {str(e)}", exc_info=True) - raise - - async def get_explicit_memory_overview( - self, - db: Session, - end_user_id: str - ) -> Dict[str, Any]: - """ - 获取显性记忆总览信息 - - 返回两部分： - 1. 情景记忆（episodic_memories）- 来自MemorySummary节点 - 2. 语义记忆（semantic_memories）- 来自ExtractedEntity节点（is_explicit_memory=true） - - Args: - db: 数据库会话 - end_user_id: 终端用户ID - - Returns: - { - "total": int, - "episodic_memories": [ - { - "id": str, - "title": str, - "content": str, - "created_at": int, - "emotion": Dict - } - ], - "semantic_memories": [ - { - "id": str, - "name": str, - "entity_type": str, - "core_definition": str, - "detailed_notes": str, - "created_at": int - } - ] - } - """ - try: - logger.info(f"开始查询 end_user_id={end_user_id} 的显性记忆总览（情景记忆+语义记忆）") - - # ========== 1. 查询情景记忆（MemorySummary节点） ========== - episodic_query = """ - MATCH (s:MemorySummary) - WHERE s.group_id = $group_id - RETURN elementId(s) AS id, - s.name AS title, - s.content AS content, - s.created_at AS created_at - ORDER BY s.created_at DESC - """ - - episodic_result = await self.neo4j_connector.execute_query( - episodic_query, - group_id=end_user_id - ) - - # 处理情景记忆数据 - episodic_memories = [] - if episodic_result: - for record in episodic_result: - summary_id = record["id"] - title = record.get("title") or "未命名" - content = record.get("content") or "" - created_at_str = record.get("created_at") - - # 转换时间戳 - created_at_timestamp = None - if created_at_str: - try: - from datetime import datetime - dt_object = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) - created_at_timestamp = int(dt_object.timestamp() * 1000) - except (ValueError, TypeError, AttributeError) as e: - logger.warning(f"无法解析时间戳: {created_at_str}, error={str(e)}") - - # 注意：总览接口不返回 emotion 字段 - episodic_memories.append({ - "id": summary_id, - "title": title, - "content": content, - "created_at": created_at_timestamp - }) - - # ========== 2. 查询语义记忆（ExtractedEntity节点） ========== - semantic_query = """ - MATCH (e:ExtractedEntity) - WHERE e.group_id = $group_id - AND e.is_explicit_memory = true - RETURN elementId(e) AS id, - e.name AS name, - e.entity_type AS entity_type, - e.description AS core_definition, - e.example AS detailed_notes, - e.created_at AS created_at - ORDER BY e.created_at DESC - """ - - semantic_result = await self.neo4j_connector.execute_query( - semantic_query, - group_id=end_user_id - ) - - # 处理语义记忆数据 - semantic_memories = [] - if semantic_result: - for record in semantic_result: - entity_id = record["id"] - name = record.get("name") or "未命名" - entity_type = record.get("entity_type") or "未分类" - core_definition = record.get("core_definition") or "" - created_at_str = record.get("created_at") - - # 转换时间戳 - created_at_timestamp = None - if created_at_str: - try: - from datetime import datetime - dt_object = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) - created_at_timestamp = int(dt_object.timestamp() * 1000) - except (ValueError, TypeError, AttributeError) as e: - logger.warning(f"无法解析时间戳: {created_at_str}, error={str(e)}") - - # 注意：总览接口不返回 detailed_notes 字段 - semantic_memories.append({ - "id": entity_id, - "name": name, - "entity_type": entity_type, - "core_definition": core_definition, - "created_at": created_at_timestamp - }) - - # ========== 3. 返回结果 ========== - total_count = len(episodic_memories) + len(semantic_memories) - - logger.info( - f"成功获取 end_user_id={end_user_id} 的显性记忆总览，" - f"情景记忆={len(episodic_memories)} 条，语义记忆={len(semantic_memories)} 条，" - f"总计 {total_count} 条" - ) - - return { - "total": total_count, - "episodic_memories": episodic_memories, - "semantic_memories": semantic_memories - } - - except Exception as e: - logger.error(f"获取显性记忆总览时出错: {str(e)}", exc_info=True) - raise - - async def get_explicit_memory_details( - self, - db: Session, - end_user_id: str, - memory_id: str - ) -> Dict[str, Any]: - """ - 获取显性记忆详情 - - 根据 memory_id 查询情景记忆或语义记忆的详细信息。 - 先尝试查询情景记忆，如果找不到再查询语义记忆。 - - Args: - db: 数据库会话 - end_user_id: 终端用户ID - memory_id: 记忆ID（可以是情景记忆或语义记忆的ID） - - Returns: - 情景记忆返回： - { - "memory_type": "episodic", - "title": str, - "content": str, - "emotion": Dict, - "created_at": int - } - - 语义记忆返回： - { - "memory_type": "semantic", - "name": str, - "core_definition": str, - "detailed_notes": str, - "created_at": int - } - - Raises: - ValueError: 当记忆不存在时 - """ - try: - logger.info(f"开始查询显性记忆详情: end_user_id={end_user_id}, memory_id={memory_id}") - - # ========== 1. 先尝试查询情景记忆 ========== - episodic_query = """ - MATCH (s:MemorySummary) - WHERE elementId(s) = $memory_id AND s.group_id = $group_id - RETURN s.name AS title, - s.content AS content, - s.created_at AS created_at - """ - - episodic_result = await self.neo4j_connector.execute_query( - episodic_query, - memory_id=memory_id, - group_id=end_user_id - ) - - if episodic_result and len(episodic_result) > 0: - record = episodic_result[0] - title = record.get("title") or "未命名" - content = record.get("content") or "" - created_at_str = record.get("created_at") - - # 转换时间戳 - created_at_timestamp = None - if created_at_str: - try: - from datetime import datetime - dt_object = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) - created_at_timestamp = int(dt_object.timestamp() * 1000) - except (ValueError, TypeError, AttributeError) as e: - logger.warning(f"无法解析时间戳: {created_at_str}, error={str(e)}") - - # 获取情绪信息 - emotion = await self._extract_episodic_emotion( - summary_id=memory_id, - end_user_id=end_user_id - ) - - logger.info(f"成功获取情景记忆详情: memory_id={memory_id}") - return { - "memory_type": "episodic", - "title": title, - "content": content, - "emotion": emotion, - "created_at": created_at_timestamp - } - - # ========== 2. 如果不是情景记忆，尝试查询语义记忆 ========== - semantic_query = """ - MATCH (e:ExtractedEntity) - WHERE elementId(e) = $memory_id - AND e.group_id = $group_id - AND e.is_explicit_memory = true - RETURN e.name AS name, - e.description AS core_definition, - e.example AS detailed_notes, - e.created_at AS created_at - """ - - semantic_result = await self.neo4j_connector.execute_query( - semantic_query, - memory_id=memory_id, - group_id=end_user_id - ) - - if semantic_result and len(semantic_result) > 0: - record = semantic_result[0] - name = record.get("name") or "未命名" - core_definition = record.get("core_definition") or "" - detailed_notes = record.get("detailed_notes") or "" - created_at_str = record.get("created_at") - - # 转换时间戳 - created_at_timestamp = None - if created_at_str: - try: - from datetime import datetime - dt_object = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) - created_at_timestamp = int(dt_object.timestamp() * 1000) - except (ValueError, TypeError, AttributeError) as e: - logger.warning(f"无法解析时间戳: {created_at_str}, error={str(e)}") - - logger.info(f"成功获取语义记忆详情: memory_id={memory_id}") - return { - "memory_type": "semantic", - "name": name, - "core_definition": core_definition, - "detailed_notes": detailed_notes, - "created_at": created_at_timestamp - } - - # ========== 3. 两种记忆都找不到 ========== - logger.warning(f"记忆不存在: memory_id={memory_id}, end_user_id={end_user_id}") - raise ValueError(f"记忆不存在: memory_id={memory_id}") - - except ValueError: - # 重新抛出 ValueError（记忆不存在） - raise - except Exception as e: - logger.error(f"获取显性记忆详情时出错: {str(e)}", exc_info=True) - raise # 独立的分析函数 @@ -2055,17 +1196,18 @@ async def analytics_memory_types( end_user_id: Optional[str] = None ) -> List[Dict[str, Any]]: """ - 统计8种记忆类型的数量和百分比 + 统计9种记忆类型的数量和百分比 计算规则： 1. 感知记忆 (PERCEPTUAL_MEMORY) = statement + entity 2. 工作记忆 (WORKING_MEMORY) = chunk + entity 3. 短期记忆 (SHORT_TERM_MEMORY) = chunk 4. 长期记忆 (LONG_TERM_MEMORY) = entity - 5. 显性记忆 (EXPLICIT_MEMORY) = 1/2 * entity + 5. 显性记忆 (EXPLICIT_MEMORY) = 情景记忆 + 语义记忆（通过 MemoryBaseService.get_explicit_memory_count 获取） 6. 隐性记忆 (IMPLICIT_MEMORY) = 1/3 * entity - 7. 情绪记忆 (EMOTIONAL_MEMORY) = statement - 8. 情景记忆 (EPISODIC_MEMORY) = memory_summary + 7. 情绪记忆 (EMOTIONAL_MEMORY) = 情绪标签统计总数（通过 MemoryBaseService.get_emotional_memory_count 获取） + 8. 情景记忆 (EPISODIC_MEMORY) = memory_summary（通过 MemoryBaseService.get_episodic_memory_count 获取） + 9. 遗忘记忆 (FORGET_MEMORY) = 激活值低于阈值的节点数（通过 MemoryBaseService.get_forget_memory_count 获取） Args: db: 数据库会话 @@ -2090,13 +1232,16 @@ async def analytics_memory_types( - IMPLICIT_MEMORY: 隐性记忆 - EMOTIONAL_MEMORY: 情绪记忆 - EPISODIC_MEMORY: 情景记忆 + - FORGET_MEMORY: 遗忘记忆 """ - # 定义需要查询的节点类型 + # 初始化基础服务 + base_service = MemoryBaseService() + + # 定义需要查询的基础节点类型 node_types = { "Statement": "Statement", "Entity": "ExtractedEntity", - "Chunk": "Chunk", - "MemorySummary": "MemorySummary" + "Chunk": "Chunk" } # 存储每种节点类型的计数 @@ -2126,18 +1271,45 @@ async def analytics_memory_types( statement_count = node_counts.get("Statement", 0) entity_count = node_counts.get("Entity", 0) chunk_count = node_counts.get("Chunk", 0) - memory_summary_count = node_counts.get("MemorySummary", 0) - # 按规则计算8种记忆类型的数量（使用英文枚举作为key） + # 获取用户的遗忘阈值配置 + forgetting_threshold = 0.3 # 默认值 + if end_user_id: + try: + from app.services.memory_agent_service import get_end_user_connected_config + from app.core.memory.storage_services.forgetting_engine.config_utils import load_actr_config_from_db + + # 获取用户关联的 config_id + connected_config = get_end_user_connected_config(end_user_id, db) + config_id = connected_config.get('memory_config_id') + + if config_id: + # 从数据库加载配置 + config = load_actr_config_from_db(db, config_id) + forgetting_threshold = config.get('forgetting_threshold', 0.3) + logger.debug(f"使用用户配置的遗忘阈值: {forgetting_threshold} (end_user_id={end_user_id}, config_id={config_id})") + else: + logger.debug(f"用户未关联配置，使用默认遗忘阈值: {forgetting_threshold} (end_user_id={end_user_id})") + except Exception as e: + logger.warning(f"获取用户遗忘阈值配置失败，使用默认值 {forgetting_threshold}: {str(e)}") + + # 使用 MemoryBaseService 的共享方法获取特殊记忆类型的数量 + episodic_count = await base_service.get_episodic_memory_count(end_user_id) + explicit_count = await base_service.get_explicit_memory_count(end_user_id) + emotion_count = await base_service.get_emotional_memory_count(end_user_id, statement_count) + forget_count = await base_service.get_forget_memory_count(end_user_id, forgetting_threshold) + + # 按规则计算9种记忆类型的数量（使用英文枚举作为key） memory_counts = { "PERCEPTUAL_MEMORY": statement_count + entity_count, # 感知记忆 "WORKING_MEMORY": chunk_count + entity_count, # 工作记忆 "SHORT_TERM_MEMORY": chunk_count, # 短期记忆 "LONG_TERM_MEMORY": entity_count, # 长期记忆 - "EXPLICIT_MEMORY": entity_count // 2, # 显性记忆 (1/2 entity) + "EXPLICIT_MEMORY": explicit_count, # 显性记忆（情景记忆 + 语义记忆） "IMPLICIT_MEMORY": entity_count // 3, # 隐性记忆 (1/3 entity) - "EMOTIONAL_MEMORY": statement_count, # 情绪记忆 - "EPISODIC_MEMORY": memory_summary_count # 情景记忆 + "EMOTIONAL_MEMORY": emotion_count, # 情绪记忆（使用情绪标签统计） + "EPISODIC_MEMORY": episodic_count, # 情景记忆 + "FORGET_MEMORY": forget_count # 遗忘记忆（激活值低于阈值） } # 计算总数 diff --git a/api/app/version_info.json b/api/app/version_info.json new file mode 100644 index 00000000..87e313e4 --- /dev/null +++ b/api/app/version_info.json @@ -0,0 +1,33 @@ +{ + "v0.2.0": { + "codeName": "启知", + "releaseDate": "2026-1-16", + "upgradePosition": "本次为架构升级，核心目标是把“被动存储”升级为“主动认知”，让系统具备情绪感知、情景理解与类人记忆机制，为后续多智能体协作与专业场景落地奠定底座。", + "coreUpgrades": [ + "记忆详情：拟人记忆——情绪引擎、情景记忆、短期记忆、工作记忆、感知记忆、显性记忆、隐性记忆，并配套类脑遗忘机制，实现从感知→情绪→情景→长期沉淀的完整人类记忆闭环", + "可视化工作流：拖拽式节点编排（LLM、知识库、逻辑、工具），业务落地周期由天缩至小时。", + "多模态知识处理：PDF、PPT、MP3、MP4 一键解析，时间感知检索准确率 94.3%，问答对数据即插即用。", + "Agent集群内置“记忆-知识-工具-审核”四类角色模板，用户一键生成；主控Agent把复杂任务拆为子任务并行分发，再靠情景记忆统一消解冲突、校验一致性，输出完整报告。" + ] + }, + "v0.1.0": { + "codeName": "初心", + "releaseDate": "2025-12-01", + "upgradePosition": "这是一款专注于管理和利用AI记忆的工具，支持RAG和知识图谱两种主流存储方式，旨在为AI应用提供持久化、结构化的“记忆”能力。", + "coreUpgrades": [ + "记忆空间：用户可以创建独立的空间来隔离不同记忆，并灵活选择存储方式。", + "记忆配置：简化了配置流程，内置自动提取关键信息的“记忆萃取”和管理生命周期的\"遗忘\"引擎。", + "知识检索：提供语义、分词和混合三种检索模式，并支持多种参数微调和结果重排序，以提升召回效果。", + "全局管理：支持统一设置默认检索参数，并可一键应用到所有知识库。", + "测试与调试：内置\"召回测试\"功能，方便用户实时验证检索效果并调整参数，支持通过分享码与他人协作。", + "记忆洞察：可查看详细的对话记录、用户画像和分析报告，帮助理解AI的\"记忆\"内容。", + "集成与管理：提供API Key用于系统集成，并包含基本的用户管理功能。", + "界面与体验：采用现代化的卡片式布局和渐变色设计，注重交互的流畅性和视觉美感。", + "起步与使用：文档中提供了清晰的基础使用流程，引导用户从创建空间、配置记忆到测试检索快速上手。", + "版本说明与限制: 记忆熊 v0.1.0 版本\"初心\"囊括智能记忆管理的核心思路和基础能力，为后续开发奠定了基础。", + "文档资源：用户手册、API文档、FAQ", + "问题反馈：GitHub Issues、邮件支持", + "致谢：感谢所有参与测试和提供反馈的用户！" + ] + } +} \ No newline at end of file diff --git a/api/migrations/versions/9ab9b6393f32_20261511.py b/api/migrations/versions/9ab9b6393f32_20261511.py new file mode 100644 index 00000000..f8bc7418 --- /dev/null +++ b/api/migrations/versions/9ab9b6393f32_20261511.py @@ -0,0 +1,30 @@ +"""20261511 + +Revision ID: 9ab9b6393f32 +Revises: 793c31683aa5 +Create Date: 2026-01-13 15:14:54.708405 + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa + + +# revision identifiers, used by Alembic. +revision: str = '9ab9b6393f32' +down_revision: Union[str, None] = '793c31683aa5' +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.drop_constraint(op.f('tool_executions_user_id_fkey'), 'tool_executions', type_='foreignkey') + # ### end Alembic commands ### + + +def downgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.create_foreign_key(op.f('tool_executions_user_id_fkey'), 'tool_executions', 'users', ['user_id'], ['id']) + # ### end Alembic commands ### \ No newline at end of file diff --git a/web/src/api/common.ts b/web/src/api/common.ts index 025dcb4d..01568640 100644 --- a/web/src/api/common.ts +++ b/web/src/api/common.ts @@ -25,7 +25,12 @@ export interface DataResponse { } export interface versionResponse{ version: string; - introduction: string; + introduction: { + releaseDate: string; + upgradePosition: string; + coreUpgrades: string[]; + codeName: string; + }; } // 首页数据统计 export const getDashboardData = `/home-page/workspaces` diff --git a/web/src/api/memory.ts b/web/src/api/memory.ts index 47177136..0ac14451 100644 --- a/web/src/api/memory.ts +++ b/web/src/api/memory.ts @@ -117,26 +117,26 @@ export const getRagContent = (end_user_id: string) => { } // 情感分布分析 export const getWordCloud = (group_id: string) => { - return request.post(`/memory/emotion/wordcloud`, { group_id, limit: 20 }) + return request.post(`/memory/emotion-memory/wordcloud`, { group_id, limit: 20 }) } // 高频情绪关键词 export const getEmotionTags = (group_id: string) => { - return request.post(`/memory/emotion/tags`, { group_id, limit: 20 }) + return request.post(`/memory/emotion-memory/tags`, { group_id, limit: 20 }) } // 情绪健康指数 export const getEmotionHealth = (group_id: string) => { - return request.post(`/memory/emotion/health`, { group_id, limit: 20 }) + return request.post(`/memory/emotion-memory/health`, { group_id, limit: 20 }) } // 个性化建议 export const getEmotionSuggestions = (group_id: string) => { - return request.post(`/memory/emotion/suggestions`, { group_id, limit: 20 }) + return request.post(`/memory/emotion-memory/suggestions`, { group_id, limit: 20 }) } export const analyticsRefresh = (end_user_id: string) => { return request.post('/memory-storage/analytics/generate_cache', { end_user_id }) } // 遗忘 export const getForgetStats = (group_id: string) => { - return request.get(`/memory/forget/stats`, { group_id }) + return request.get(`/memory/forget-memory/stats`, { group_id }) } // 隐性记忆-偏好 export const getImplicitPreferences = (end_user_id: string) => { @@ -176,10 +176,10 @@ export const getPerceptualTimeline = (end_user: string) => { } // 情景记忆-总览 export const getEpisodicOverview = (data: { end_user_id: string; time_range: string; episodic_type: string; } ) => { - return request.post(`/memory-storage/classifications/episodic-memory`, data) + return request.post(`/memory/episodic-memory/overview`, data) } export const getEpisodicDetail = (data: { end_user_id: string; summary_id: string; } ) => { - return request.post(`/memory-storage/classifications/episodic-memory-details`, data) + return request.post(`/memory/episodic-memory/details`, data) } // 关系演化 export const getRelationshipEvolution = (data: { id: string; label: string; } ) => { @@ -190,10 +190,10 @@ export const getTimelineMemories = (data: { id: string; label: string; }) => { return request.get(`/memory-storage/memory_space/timeline_memories`, data) } export const getExplicitMemory = (end_user_id: string) => { - return request.post(`/memory-storage/classifications/explicit-memory`, { end_user_id }) + return request.post(`/memory/explicit-memory/overview`, { end_user_id }) } export const getExplicitMemoryDetails = (data: { end_user_id: string, memory_id: string; }) => { - return request.post(`/memory-storage/classifications/explicit-memory-details`, data) + return request.post(`/memory/explicit-memory/details`, data) } export const getConversations = (end_user: string) => { return request.get(`/memory/work/${end_user}/conversations`) @@ -204,8 +204,9 @@ export const getConversationMessages = (end_user: string, conversation_id: strin export const getConversationDetail = (end_user: string, conversation_id: string) => { return request.get(`/memory/work/${end_user}/detail`, { conversation_id }) } - - +export const forgetTrigger = (data: { max_merge_batch_size: number; min_days_since_access: number; end_user_id: string;}) => { + return request.post(`/memory/forget-memory/trigger`, data) +} /*************** end 用户记忆 相关接口 ******************************/ /****************** 记忆管理 相关接口 *******************************/ @@ -228,11 +229,11 @@ export const deleteMemoryConfig = (config_id: number) => { } // 遗忘引擎-获取配置 export const getMemoryForgetConfig = (config_id: number | string) => { - return request.get('/memory/forget/read_config', { config_id }) + return request.get('/memory/forget-memory/read_config', { config_id }) } // 遗忘引擎-更新配置 export const updateMemoryForgetConfig = (values: ForgetConfigForm) => { - return request.post('/memory/forget/update_config', values) + return request.post('/memory/forget-memory/update_config', values) } // 记忆萃取引擎-获取配置 export const getMemoryExtractionConfig = (config_id: number | string) => { diff --git a/web/src/assets/images/logout_hover.svg b/web/src/assets/images/logout_hover.svg new file mode 100644 index 00000000..d77ab292 --- /dev/null +++ b/web/src/assets/images/logout_hover.svg @@ -0,0 +1,17 @@ + + + 退出 + + + + + + + + + + + + + + \ No newline at end of file diff --git a/web/src/assets/images/menu/spaceConfig.svg b/web/src/assets/images/menu/spaceConfig.svg new file mode 100644 index 00000000..bcfeae12 --- /dev/null +++ b/web/src/assets/images/menu/spaceConfig.svg @@ -0,0 +1,17 @@ + + + 模型 (1) + + + + + + + + + + + + + + \ No newline at end of file diff --git a/web/src/assets/images/menu/spaceConfig_active.svg b/web/src/assets/images/menu/spaceConfig_active.svg new file mode 100644 index 00000000..41b25689 --- /dev/null +++ b/web/src/assets/images/menu/spaceConfig_active.svg @@ -0,0 +1,17 @@ + + + 模型 (1) + + + + + + + + + + + + + + \ No newline at end of file diff --git a/web/src/assets/images/userMemory/goto.svg b/web/src/assets/images/userMemory/goto.svg new file mode 100644 index 00000000..a66e2011 --- /dev/null +++ b/web/src/assets/images/userMemory/goto.svg @@ -0,0 +1,19 @@ + + + 编组 13备份 + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/web/src/components/Chat/ChatContent.tsx b/web/src/components/Chat/ChatContent.tsx index 2067f57e..11ccb5c3 100644 --- a/web/src/components/Chat/ChatContent.tsx +++ b/web/src/components/Chat/ChatContent.tsx @@ -2,7 +2,7 @@ * @Author: ZhaoYing * @Date: 2025-12-10 16:46:17 * @Last Modified by: ZhaoYing - * @Last Modified time: 2025-12-11 13:40:18 + * @Last Modified time: 2026-01-12 20:41:27 */ import { type FC, useRef, useEffect } from 'react' import clsx from 'clsx' @@ -55,7 +55,7 @@ const ChatContent: FC = ({ } {/* 消息气泡框 */} -
{ disabled?: boolean; style?: React.CSSProperties; className?: string; - filterOption?: (inputValue: string, option: DefaultOptionType) => boolean; + filterOption?: (inputValue: string, option?: DefaultOptionType) => boolean; } interface OptionType { [key: string]: Key | string | number; @@ -48,44 +48,27 @@ const CustomSelect: FC = ({ }) => { const { t } = useTranslation(); const [options, setOptions] = useState([]); - // 创建防抖定时器引用 - const debounceRef = useRef(); - - // 防抖搜索函数 - const handleSearch = useCallback((value?: string) => { - // 清除之前的定时器 - if (debounceRef.current) { - clearTimeout(debounceRef.current); - } - - // 设置新的定时器 - debounceRef.current = window.setTimeout(() => { - request.get>(url, {...params, [optionFilterProp]: value}).then((res) => { - const data = res; - setOptions(Array.isArray(data) ? data || [] : Array.isArray(data?.items) ? data.items || [] : []); - }); - }, 300); // 300毫秒防抖延迟 - }, [url, params, optionFilterProp]); + // 默认模糊搜索函数 + const defaultFilterOption = (inputValue: string, option?: DefaultOptionType) => { + if (!option || !inputValue) return true; + const label = String(option.children || option.label || ''); + return label.toLowerCase().includes(inputValue.toLowerCase()); + }; // 组件挂载时获取初始数据 useEffect(() => { - handleSearch(); - - // 组件卸载时清除定时器 - return () => { - if (debounceRef.current) { - clearTimeout(debounceRef.current); - } - }; - }, [url, handleSearch]); + request.get>(url, params).then((res) => { + const data = res; + setOptions(Array.isArray(data) ? data || [] : Array.isArray(data?.items) ? data.items || [] : []); + }); + }, []); return ( + - - + ((_props, ref) => { const { t } = useTranslation(); @@ -88,8 +89,8 @@ const TimeToolModal = forwardRef((_props, ref) => { } }) .then(res => { - const response = res as { data: CurrentTimeObj } - setTimestampFormat(response.data.datetime) + const response = res as { data: string } + setTimestampFormat(response.data) }) } const handleChangeFormatType = () => { @@ -149,7 +150,7 @@ const TimeToolModal = forwardRef((_props, ref) => { - + diff --git a/web/src/views/ToolManagement/constant.ts b/web/src/views/ToolManagement/constant.ts index 1e30bafa..6763a140 100644 --- a/web/src/views/ToolManagement/constant.ts +++ b/web/src/views/ToolManagement/constant.ts @@ -10,10 +10,10 @@ export const InnerConfigData: Record = { }, JsonTool: { features: [ - 'jsonFormat', - 'jsonGzip', - 'jsonCheck', - 'jsonConversion' + 'jsonParse', + 'jsonInsert', + 'jsonReplace', + 'jsonDelete' ], eg: '{"name":"工具","tool_class":"内置"}' }, diff --git a/web/src/views/ToolManagement/types.ts b/web/src/views/ToolManagement/types.ts index 6fd4e439..aa97db66 100644 --- a/web/src/views/ToolManagement/types.ts +++ b/web/src/views/ToolManagement/types.ts @@ -130,6 +130,7 @@ export interface ExecuteData { ensure_ascii?: boolean; sort_keys?: boolean; input_data?: string; + json_path?: string; } } export interface CustomToolModalRef { diff --git a/web/src/views/UserMemory/components/ConfigModal.tsx b/web/src/views/UserMemory/components/ConfigModal.tsx deleted file mode 100644 index 86ea8f19..00000000 --- a/web/src/views/UserMemory/components/ConfigModal.tsx +++ /dev/null @@ -1,127 +0,0 @@ -import { forwardRef, useImperativeHandle, useState } from 'react'; -import { Form, App } from 'antd'; -import { useTranslation } from 'react-i18next'; - -import type { ConfigModalData, ConfigModalRef } from '../types' -import { getWorkspaceModels, updateWorkspaceModels } from '@/api/workspaces' -import { getModelListUrl } from '@/api/models' -import CustomSelect from '@/components/CustomSelect' -import RbModal from '@/components/RbModal' - -const ConfigModal = forwardRef((_props, ref) => { - const { t } = useTranslation(); - const { message } = App.useApp(); - const [visible, setVisible] = useState(false); - const [form] = Form.useForm(); - const [loading, setLoading] = useState(false) - - const values = Form.useWatch([], form); - - // 封装取消方法，添加关闭弹窗逻辑 - const handleClose = () => { - setVisible(false); - form.resetFields(); - setLoading(false) - }; - - const handleOpen = () => { - getWorkspaceModels().then((res) => { - const { llm, embedding, rerank } = res as ConfigModalData - form.setFieldsValue({ - llm, - embedding, - rerank - }) - }) - setVisible(true); - }; - // 封装保存方法，添加提交逻辑 - const handleSave = () => { - form - .validateFields() - .then(() => { - setLoading(true) - updateWorkspaceModels(values) - .then(() => { - setLoading(false) - handleClose() - message.success(t('common.updateSuccess')) - }) - .catch(() => { - setLoading(false) - }); - - handleClose() - }) - .catch((err) => { - console.log('err', err) - }); - } - - // 暴露给父组件的方法 - useImperativeHandle(ref, () => ({ - handleOpen, - handleClose - })); - - return ( - -
- - - - - - - - - -
- - ); -}); - -export default ConfigModal; \ No newline at end of file diff --git a/web/src/views/UserMemory/index.tsx b/web/src/views/UserMemory/index.tsx index 7065f036..064b55be 100644 --- a/web/src/views/UserMemory/index.tsx +++ b/web/src/views/UserMemory/index.tsx @@ -1,56 +1,28 @@ -import { useEffect, useState, useRef } from 'react'; +import { useEffect, useState, useMemo } from 'react'; import { useTranslation } from 'react-i18next'; import { useNavigate } from 'react-router-dom' -import { Row, Col, Radio, Button, List, Skeleton, Space } from 'antd'; -import type { ColumnsType } from 'antd/es/table'; -import type { RadioChangeEvent } from 'antd'; -import { AppstoreOutlined, MenuOutlined } from '@ant-design/icons'; +import { Row, Col, List, Skeleton } from 'antd'; import Empty from '@/components/Empty' -import type { Data, ConfigModalRef } from './types' -import totalNum from '@/assets/images/memory/totalNum.svg' -import onlineNum from '@/assets/images/memory/onlineNum.svg' -import Table from '@/components/Table' -import { getTotalEndUsers, userMemoryListUrl, getUserMemoryList } from '@/api/memory'; -import ConfigModal from './components/ConfigModal'; +import type { Data } from './types' +import { getUserMemoryList } from '@/api/memory'; import { useUser } from '@/store/user' +import RbCard from '@/components/RbCard/Card' +import SearchInput from '@/components/SearchInput'; -const bgList = [ - 'linear-gradient( 180deg, #F1F6FE 0%, #FBFDFF 100%)', - 'linear-gradient( 180deg, #F1F9FE 0%, #FBFDFF 100%)', - 'linear-gradient( 180deg, #FEFBF7 0%, #FBFDFF 100%)', - 'linear-gradient( 180deg, #F1F9FE 0%, #FBFDFF 100%)', -] - -const countList = [ - 'total_num', 'online_num', -] -const IconList: Record = { - total_num: totalNum, - online_num: onlineNum, -} export default function UserMemory() { const { t } = useTranslation(); const navigate = useNavigate() const { storageType } = useUser() - const configModalRef = useRef(null) const [loading, setLoading] = useState(false); const [data, setData] = useState([]); - const [countData, setCountData] = useState>({}); - const [layout, setLayout] = useState<'card' | 'list'>('card'); + const [search, setSearch] = useState(undefined); // 获取数据 useEffect(() => { - getCountData() getData() }, []); - // 用户记忆统计 - const getCountData = () => { - getTotalEndUsers().then((res) => { - setCountData(res as Record || {}) - }) - } const getData = () => { setLoading(true) getUserMemoryList().then((res) => { @@ -60,7 +32,6 @@ export default function UserMemory() { setLoading(false) }) } - console.log('storageType', storageType) const handleViewDetail = (id: string | number) => { switch (storageType) { case 'neo4j': @@ -70,112 +41,77 @@ export default function UserMemory() { navigate(`/user-memory/${id}`) } } - const handleChangeLayout = (e: RadioChangeEvent) => { - const type = e.target.value - setLayout(type) + const handleViewMemoryConfig = () => { + navigate(`/memory`) } - // 表格列配置 - const columns: ColumnsType = [ - { - title: t('userMemory.user'), - dataIndex: 'end_user', - key: 'end_user', - render: (value) => value?.other_name && value?.other_name !== '' ? value?.other_name : value?.id || '-' - }, - { - title: t('userMemory.knowledgeEntryCount'), - dataIndex: 'memory_num', - key: 'memory_num', - render: (value) => value?.total || 0 - }, - { - title: t('common.operation'), - key: 'action', - render: (_, record) => ( - - ), - }, - ]; + + const filterData = useMemo(() => { + if (search && search.trim() !== '') { + return data.filter((item) => { + const { end_user } = item as Data; + const name = end_user?.other_name && end_user?.other_name !== '' ? end_user?.other_name : end_user?.id + return name?.includes(search) + }) + } + + return data + }, [search, data]) return (
- {countList.map(key => ( - -
-
- {countData[key] || 0}{key === 'avgInteractionTime' ? 's' : ''} - -
-
{t(`userMemory.${key}`)}
-
- - ))} - - - - - - - - + + setSearch(value)} + style={{ width: '100%' }} + /> - {layout === 'card' && - <> - {loading ? - - : data.length > 0 ? ( - { - const { end_user, memory_num } = item as Data; - const name = end_user?.other_name && end_user?.other_name !== '' ? end_user?.other_name : end_user?.id - return ( - -
+ : filterData.length > 0 ? ( + { + const { end_user, memory_num, memory_config } = item as Data; + const name = end_user?.other_name && end_user?.other_name !== '' ? end_user?.other_name : end_user?.id + return ( + + {name[0]}
} + title={name || '-'} + extra={
handleViewDetail(end_user.id)} - > -
-
{name[0]}
-
- {name || '-'}
-
-
-
-
-
{memory_num.total || 0}
-
{t(`userMemory.knowledgeEntryCount`)}
-
-
+ >
} + > +
+
{t('userMemory.capacity')}
+
{memory_num?.total || 0} {t('userMemory.memoryNum')}
+
+
+
{t('userMemory.type')}
+
{t(`userMemory.${item.type || 'person'}`)}
- - ) - }} - /> - ) : } - - } - {layout === 'list' && - +
+
+ {t('userMemory.memory_config_name')} +
+
+
{memory_config?.memory_config_name || '-'}
+
+ + + ) + }} + /> + ) : } - ); } \ No newline at end of file diff --git a/web/src/views/UserMemory/types.ts b/web/src/views/UserMemory/types.ts index 696b1694..927cf778 100644 --- a/web/src/views/UserMemory/types.ts +++ b/web/src/views/UserMemory/types.ts @@ -17,13 +17,10 @@ export interface Data { entity: number; } }, + memory_config: { + memory_config_id: string; + memory_config_name: string; + }, + type: string; name?: string; -} -export interface ConfigModalData { - llm: string; - embedding: string; - rerank: string; -} -export interface ConfigModalRef { - handleOpen: () => void; } \ No newline at end of file diff --git a/web/src/views/UserMemoryDetail/components/EmotionLine.tsx b/web/src/views/UserMemoryDetail/components/EmotionLine.tsx index 3652e7c5..68664d39 100644 --- a/web/src/views/UserMemoryDetail/components/EmotionLine.tsx +++ b/web/src/views/UserMemoryDetail/components/EmotionLine.tsx @@ -3,7 +3,7 @@ import { useTranslation } from 'react-i18next' import ReactEcharts from 'echarts-for-react'; import Empty from '@/components/Empty' import Loading from '@/components/Empty/Loading' -import type { Emotion } from './GraphDetail' +import type { Emotion } from '../pages/GraphDetail' interface EmotionLineProps { chartData: Emotion[]; @@ -26,7 +26,7 @@ const EmotionLine: FC = ({ chartData, loading }) => { const seriesData = timePoints.map(time => dataMap.get(time) || 0) return { - name: emotionType, + name: t(`userMemory.${emotionType}`), type: 'line', smooth: true, lineStyle: { @@ -71,7 +71,7 @@ const EmotionLine: FC = ({ chartData, loading }) => { formatter: function(params: any) { let result = `${params[0].axisValue}
` params.forEach((param: any) => { - result += `${param.marker}${param.seriesName}: ${param.value}
` + result += `${param.marker}${param.seriesName}: ${param.value}%
` }) return result } @@ -92,7 +92,7 @@ const EmotionLine: FC = ({ chartData, loading }) => { }, grid: { top: 16, - left: 30, + left: 40, right: 36, bottom: 48, // containLabel: false @@ -103,7 +103,7 @@ const EmotionLine: FC = ({ chartData, loading }) => { boundaryGap: false, axisLabel: { color: '#A8A9AA', - fontFamily: 'PingFangSC, PingFang SC' + fontFamily: 'PingFangSC, PingFang SC', }, axisLine: { show: true, @@ -130,7 +130,8 @@ const EmotionLine: FC = ({ chartData, loading }) => { type: 'value', axisLabel: { color: '#A8A9AA', - fontFamily: 'PingFangSC, PingFang SC' + fontFamily: 'PingFangSC, PingFang SC', + formatter: '{value}%' }, axisLine: { show: true, @@ -152,7 +153,7 @@ const EmotionLine: FC = ({ chartData, loading }) => { type: 'solid' } }, - max: 1, + max: 100, min: 0 }, series: getSeries() diff --git a/web/src/views/UserMemoryDetail/components/ForgetRefreshModal.tsx b/web/src/views/UserMemoryDetail/components/ForgetRefreshModal.tsx new file mode 100644 index 00000000..1d0974e3 --- /dev/null +++ b/web/src/views/UserMemoryDetail/components/ForgetRefreshModal.tsx @@ -0,0 +1,113 @@ +import { forwardRef, useImperativeHandle, useState } from 'react'; +import { useParams } from 'react-router-dom' +import { Form, Slider } from 'antd'; +import { useTranslation } from 'react-i18next'; + +import RbModal from '@/components/RbModal' +import { forgetTrigger } from '@/api/memory' +import type { ForgetRefreshModalRef } from '../pages/ForgetDetail' + +interface ForgetRefreshModalProps { + refresh: (flag: boolean) => void; +} + +const ForgetRefreshModal = forwardRef(({ + refresh +}, ref) => { + const { t } = useTranslation(); + const { id } = useParams() + const [visible, setVisible] = useState(false); + const [form] = Form.useForm<{ max_merge_batch_size: number; min_days_since_access: number; }>(); + const [loading, setLoading] = useState(false) + const values = Form.useWatch([], form); + + // 封装取消方法，添加关闭弹窗逻辑 + const handleClose = () => { + setVisible(false); + form.resetFields(); + setLoading(false) + }; + + const handleOpen = () => { + form.resetFields(); + setVisible(true); + }; + // 封装保存方法，添加提交逻辑 + const handleSave = () => { + if(!id) return + form + .validateFields() + .then((values) => { + setLoading(true) + forgetTrigger({ + ...values, + end_user_id: id + }) + .then(() => { + refresh(true) + handleClose() + }) + .finally(() => { + setLoading(false) + }) + }) + .catch((err) => { + console.log('err', err) + }); + } + + // 暴露给父组件的方法 + useImperativeHandle(ref, () => ({ + handleOpen, + handleClose + })); + + return ( + +
+
+
+ {t(`forgettingEngine.max_merge_batch_size`)} +
+ + + + +
+ {t(`forgettingEngine.range`)}: {[1, 1000]?.join('-')} + {t('forgettingEngine.CurrentValue')}: {values?.min_days_since_access || 0} +
+
+
+
+ {t(`forgettingEngine.min_days_since_access`)} +
+ + + + +
+ {t(`forgettingEngine.range`)}: {[1, 365]?.join('-')} + {t('forgettingEngine.CurrentValue')}: {values?.min_days_since_access || 0} +
+
+ + + ); +}); + +export default ForgetRefreshModal; \ No newline at end of file diff --git a/web/src/views/UserMemoryDetail/components/InteractionBar.tsx b/web/src/views/UserMemoryDetail/components/InteractionBar.tsx index 51224676..60c977fd 100644 --- a/web/src/views/UserMemoryDetail/components/InteractionBar.tsx +++ b/web/src/views/UserMemoryDetail/components/InteractionBar.tsx @@ -1,9 +1,9 @@ -import { type FC } from 'react' +import { type FC, useMemo } from 'react' import { useTranslation } from 'react-i18next' import ReactEcharts from 'echarts-for-react' import Empty from '@/components/Empty' import Loading from '@/components/Empty/Loading' -import type { Interaction } from './GraphDetail' +import type { Interaction } from '../pages/GraphDetail' interface InteractionBarProps { chartData: Interaction[]; @@ -14,11 +14,13 @@ const Colors = ['#155EEF', '#369F21', '#FF5D34'] const InteractionBar: FC = ({ chartData, loading }) => { const { t } = useTranslation() - const series = [{ - name: 'Interaction Count', - type: 'bar', - data: chartData.map(item => item.count) - }] + const series = useMemo(() => { + return [{ + name: t('userMemory.interactionCountData'), + type: 'bar', + data: chartData.map(item => item.count) + }] + }, [chartData, t]) return ( <> @@ -80,6 +82,7 @@ const InteractionBar: FC = ({ chartData, loading }) => { }, yAxis: { type: 'value', + minInterval: 1, axisLabel: { color: '#A8A9AA', fontFamily: 'PingFangSC, PingFang SC' @@ -104,8 +107,6 @@ const InteractionBar: FC = ({ chartData, loading }) => { type: 'solid' } }, - max: 1, - min: 0 }, series }} diff --git a/web/src/views/UserMemoryDetail/components/PageHeader.tsx b/web/src/views/UserMemoryDetail/components/PageHeader.tsx index 56da70e0..68cdada8 100644 --- a/web/src/views/UserMemoryDetail/components/PageHeader.tsx +++ b/web/src/views/UserMemoryDetail/components/PageHeader.tsx @@ -1,20 +1,22 @@ import { type FC, type ReactNode } from 'react'; import { useNavigate } from 'react-router-dom'; -import { Layout } from 'antd'; +import { Layout, Space, Button } from 'antd'; import { useTranslation } from 'react-i18next'; -import logoutIcon from '@/assets/images/logout.svg' +import logoutIcon from '@/assets/images/logout_hover.svg' const { Header } = Layout; interface ConfigHeaderProps { name?: string; operation?: ReactNode; - source?: 'detail' | 'node' + source?: 'detail' | 'node'; + extra?: ReactNode; } const PageHeader: FC = ({ name, operation, - source = 'detail' + source = 'detail', + extra }) => { const { t } = useTranslation(); const navigate = useNavigate(); @@ -33,10 +35,13 @@ const PageHeader: FC = ({ {operation} -
- - {t('common.return')} -
+ + + {extra} + ); }; diff --git a/web/src/views/UserMemoryDetail/components/RelationshipNetwork.tsx b/web/src/views/UserMemoryDetail/components/RelationshipNetwork.tsx index 07095fe4..d12c3e57 100644 --- a/web/src/views/UserMemoryDetail/components/RelationshipNetwork.tsx +++ b/web/src/views/UserMemoryDetail/components/RelationshipNetwork.tsx @@ -1,19 +1,18 @@ import React, { type FC, useEffect, useState, useRef, useCallback } from 'react' import { useTranslation } from 'react-i18next' -import { useParams } from 'react-router-dom' +import { useParams, useNavigate } from 'react-router-dom' import { Col, Row, Space, Button } from 'antd' import dayjs from 'dayjs' import RbCard from '@/components/RbCard/Card' import ReactEcharts from 'echarts-for-react' import detailEmpty from '@/assets/images/userMemory/detail_empty.png' -import type { Node, Edge, GraphData, StatementNodeProperties, ExtractedEntityNodeProperties, GraphDetailRef } from '../types' +import type { Node, Edge, GraphData, StatementNodeProperties, ExtractedEntityNodeProperties } from '../types' import { getMemorySearchEdges, } from '@/api/memory' import Empty from '@/components/Empty' import Tag from '@/components/Tag' -import GraphDetail from '../components/GraphDetail' const colors = ['#155EEF', '#369F21', '#4DA8FF', '#FF5D34', '#9C6FFF', '#FF8A4C', '#8BAEF7', '#FFB048'] const RelationshipNetwork:FC = () => { @@ -26,7 +25,7 @@ const RelationshipNetwork:FC = () => { const [categories, setCategories] = useState<{ name: string }[]>([]) const [selectedNode, setSelectedNode] = useState(null) // const [fullScreen, setFullScreen] = useState(false) - const graphDetailRef = useRef(null) + const navigate = useNavigate() console.log('categories', categories) // 关系网络 @@ -133,15 +132,14 @@ const RelationshipNetwork:FC = () => { } }, [nodes]) - // const handleFullScreen = () => { - // setFullScreen(prev => !prev) - // } - - console.log('selectedNode', selectedNode) - const handleViewAll = () => { if (!selectedNode) return - graphDetailRef.current?.handleOpen(selectedNode) + const params = new URLSearchParams({ + nodeId: selectedNode.id, + nodeLabel: selectedNode.label, + nodeName: selectedNode.name || '' + }) + navigate(`/user-memory/detail/${id}/GRAPH?${params.toString()}`) } return ( @@ -336,8 +334,6 @@ const RelationshipNetwork:FC = () => { - - ) } diff --git a/web/src/views/UserMemoryDetail/components/Timeline.tsx b/web/src/views/UserMemoryDetail/components/Timeline.tsx index d7b9b273..e2d9446f 100644 --- a/web/src/views/UserMemoryDetail/components/Timeline.tsx +++ b/web/src/views/UserMemoryDetail/components/Timeline.tsx @@ -9,6 +9,7 @@ import { } from '@/api/memory' import { formatDateTime } from '@/utils/format'; import Empty from '@/components/Empty' +import Tag from '@/components/Tag' interface TimelineItem { id: string; @@ -18,6 +19,9 @@ interface TimelineItem { summary: string; storage_type: number; created_time: string | number; + domain: string; + topic: string; + keywords: string[] } const KEYS = { @@ -68,9 +72,14 @@ const Timeline: FC = () => { {formatDateTime(vo.created_time)} {index !== data.length - 1 && } -
-
{vo.summary}
-
{t(`perceptualDetail.${perceptual_type[vo.perceptual_type]}`)}
+
+
+
{vo.summary}
+
{t(`perceptualDetail.${perceptual_type[vo.perceptual_type]}`)}
+
+
{[vo.domain, vo.topic].join(' | ')}
+ + {vo.keywords.map(tag => {tag})}
))} diff --git a/web/src/views/UserMemoryDetail/pages/ForgetDetail.tsx b/web/src/views/UserMemoryDetail/pages/ForgetDetail.tsx index 602dbf25..9a19f055 100644 --- a/web/src/views/UserMemoryDetail/pages/ForgetDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/ForgetDetail.tsx @@ -1,7 +1,7 @@ -import { type FC, useEffect, useState, useMemo } from 'react' +import { useEffect, useState, useMemo, forwardRef, useImperativeHandle, useRef } from 'react' import { useTranslation } from 'react-i18next' import { useParams } from 'react-router-dom' -import { Row, Col, Progress } from 'antd' +import { Row, Col, Progress, App } from 'antd' import RbCard from '@/components/RbCard/Card' import { getForgetStats, @@ -12,6 +12,7 @@ import RecentTrendsLineCard from '../components/RecentTrendsLineCard' import Table from '@/components/Table' import { formatDateTime } from '@/utils/format' import StatusTag from '@/components/StatusTag' +import ForgetRefreshModal from '../components/ForgetRefreshModal' const statusTagColors: Record = { statement: 'success', @@ -20,24 +21,33 @@ const statusTagColors: Record { +export interface ForgetRefreshModalRef { + handleOpen: () => void; +} + +const ForgetDetail = forwardRef((_props, ref) => { const { t } = useTranslation() const { id } = useParams() + const { message } = App.useApp() const [loading, setLoading] = useState(false) const [data, setData] = useState({} as ForgetData) + const forgetRefreshModalRef = useRef(null) useEffect(() => { if (!id) return getData() }, [id]) - const getData = () => { + const getData = (flag: boolean = false) => { if (!id) return setLoading(true) getForgetStats(id).then((res) => { const response = res as ForgetData setData(response) setLoading(false) + if (flag) { + message.success(t('forgetDetail.refreshSuccess')) + } }) .finally(() => { setLoading(false) @@ -67,6 +77,14 @@ const ForgetDetail: FC = () => { } }, [data.recent_trends]) + const handleRefresh = () => { + forgetRefreshModalRef.current?.handleOpen() + } + + useImperativeHandle(ref, () => ({ + handleRefresh + })); + return (
{t('forgetDetail.title')}
@@ -152,7 +170,12 @@ const ForgetDetail: FC = () => { ]} pagination={false} /> + +
) -} +}) export default ForgetDetail \ No newline at end of file diff --git a/web/src/views/UserMemoryDetail/components/GraphDetail.tsx b/web/src/views/UserMemoryDetail/pages/GraphDetail.tsx similarity index 50% rename from web/src/views/UserMemoryDetail/components/GraphDetail.tsx rename to web/src/views/UserMemoryDetail/pages/GraphDetail.tsx index aed795f5..47efce76 100644 --- a/web/src/views/UserMemoryDetail/components/GraphDetail.tsx +++ b/web/src/views/UserMemoryDetail/pages/GraphDetail.tsx @@ -1,16 +1,17 @@ -import { useState, forwardRef, useImperativeHandle, useMemo } from 'react' +import { useState, forwardRef, useImperativeHandle, useMemo, useEffect } from 'react' import { useTranslation } from 'react-i18next' +import { useSearchParams } from 'react-router-dom' import { Row, Col, Tabs, Space, Skeleton } from 'antd' import { getRelationshipEvolution, getTimelineMemories } from '@/api/memory' import type { Node, GraphDetailRef } from '../types' -import RbDrawer from '@/components/RbDrawer' import RbCard from '@/components/RbCard/Card' -import EmotionLine from './EmotionLine' +import EmotionLine from '../components/EmotionLine' import { formatDateTime } from '@/utils/format' import Tag from '@/components/Tag' -import InteractionBar from './InteractionBar' +import InteractionBar from '../components/InteractionBar' import Empty from '@/components/Empty' +import PageHeader from '../components/PageHeader' export interface Emotion { emotion_intensity: number; @@ -35,7 +36,7 @@ interface Timeline { const GraphDetail = forwardRef((_props, ref) => { const { t } = useTranslation() - const [open, setOpen] = useState(false); + const [searchParams] = useSearchParams() const [vo, setVo] = useState(null) const [loading, setLoading] = useState(false) const [emotionData, setEmotionData] = useState([]) @@ -43,14 +44,23 @@ const GraphDetail = forwardRef((_props, ref) => { const [activeTab, setActiveTab] = useState('timelines_memory') const [timelineLoading, setTimelineLoading] = useState(false) const [timelineMemories, setTimelineMemories] = useState({ timelines_memory: [], MemorySummary: [], Statement: [], ExtractedEntity: []}) + useEffect(() => { + const nodeId = searchParams.get('nodeId') + const nodeLabel = searchParams.get('nodeLabel') + const nodeName = searchParams.get('nodeName') + + if (nodeId && nodeLabel) { + const nodeFromUrl = { + id: nodeId, + label: nodeLabel, + name: nodeName || nodeLabel + } + handleOpen(nodeFromUrl as Node) + } + }, [searchParams]) - const handleCancel = () => { - setVo(null) - setOpen(false) - } const handleOpen = (vo: Node) => { setActiveTab('timelines_memory') - setOpen(true) setVo(vo) getRelationshipEvolutionData(vo) getTimelineMemoriesData(vo) @@ -85,56 +95,57 @@ const GraphDetail = forwardRef((_props, ref) => { }, [activeTab, timelineMemories]) return ( - -
{t('userMemory.relationshipEvolution')}
- - - - - - - - - - + <> + +
+
{t('userMemory.relationshipEvolution')}
+ + +
+ + + + + + + -
{t('userMemory.timelineMemories')}
- - ({ - label: t(`userMemory.${key}`), - key - }))} - onChange={(key: string) => setActiveTab(key)} - /> - {timelineLoading - ? - : !activeContent || activeContent.length === 0 - ? - : - {activeContent.map((vo, index) => ( - -
{formatDateTime(vo.created_at)}
- {vo.type} - - ))} - - } +
{t('userMemory.timelineMemories')}
+ + ({ + label: t(`userMemory.${key}`), + key + }))} + onChange={(key: string) => setActiveTab(key)} + /> + {timelineLoading + ? + : !activeContent || activeContent.length === 0 + ? + : + {activeContent.map((vo, index) => ( + +
{formatDateTime(vo.created_at)}
+ {vo.type} + + ))} + + } - - - + + + + ) }) export default GraphDetail \ No newline at end of file diff --git a/web/src/views/UserMemoryDetail/pages/index.tsx b/web/src/views/UserMemoryDetail/pages/index.tsx index d29a8fad..f5b1a937 100644 --- a/web/src/views/UserMemoryDetail/pages/index.tsx +++ b/web/src/views/UserMemoryDetail/pages/index.tsx @@ -1,7 +1,7 @@ -import { type FC, useEffect, useState, useMemo } from 'react' +import { type FC, useEffect, useState, useMemo, useRef } from 'react' import { useParams, useNavigate } from 'react-router-dom' import { useTranslation } from 'react-i18next' -import { Dropdown } from 'antd' +import { Dropdown, Button } from 'antd' import PageHeader from '../components/PageHeader' import StatementDetail from './StatementDetail' @@ -15,12 +15,16 @@ import WorkingDetail from './WorkingDetail' import { getEndUserProfile, } from '@/api/memory' +import refreshIcon from '@/assets/images/refresh_hover.svg' +import GraphDetail from './GraphDetail' const Detail: FC = () => { const { t } = useTranslation() const { id, type } = useParams() const navigate = useNavigate() const [name, setName] = useState('') + const forgetDetailRef = useRef<{ handleRefresh: () => void }>(null) + useEffect(() => { if (!id) return getData() @@ -40,6 +44,13 @@ const Detail: FC = () => { const onClick = ({ key }: { key: string }) => { navigate(`/user-memory/detail/${id}/${key}`, { replace: true }) } + const handleRefresh = () => { + forgetDetailRef.current?.handleRefresh() + } + + if (type === 'GRAPH') { + return + } return (
@@ -49,17 +60,22 @@ const Detail: FC = () => { operation={
- - {type ? t(`userMemory.${type}`) : ''} + - {type ? t(`userMemory.${type}`) : ''}
-
+
} + extra={type === 'FORGETTING_MANAGEMENT' && + } />
{type === 'EMOTIONAL_MEMORY' && } - {type === 'FORGETTING_MANAGEMENT' && } + {type === 'FORGETTING_MANAGEMENT' && } {type === 'IMPLICIT_MEMORY' && } {type === 'SHORT_TERM_MEMORY' && } {type === 'PERCEPTUAL_MEMORY' && } diff --git a/web/src/views/Workflow/components/Chat/Chat.tsx b/web/src/views/Workflow/components/Chat/Chat.tsx index 4824cc9c..0673389e 100644 --- a/web/src/views/Workflow/components/Chat/Chat.tsx +++ b/web/src/views/Workflow/components/Chat/Chat.tsx @@ -26,6 +26,7 @@ const Chat = forwardRef(({ appId const [chatList, setChatList] = useState([]) const [variables, setVariables] = useState([]) const [streamLoading, setStreamLoading] = useState(false) + const [conversationId, setConversationId] = useState(null) const handleOpen = () => { setOpen(true) @@ -100,7 +101,7 @@ const Chat = forwardRef(({ appId setStreamLoading(false) data.forEach(item => { - const { chunk } = item.data as { chunk: string; }; + const { chunk, conversation_id } = item.data as { chunk: string; conversation_id: string | null; }; switch(item.event) { case 'message': @@ -131,6 +132,10 @@ const Chat = forwardRef(({ appId setStreamLoading(false) break } + + if (conversation_id && conversationId !== conversation_id) { + setConversationId(conversation_id) + } }) } @@ -138,7 +143,8 @@ const Chat = forwardRef(({ appId draftRun(appId, { message: message, variables: params, - stream: true + stream: true, + conversation_id: conversationId }, handleStreamMessage) .finally(() => { setLoading(false) diff --git a/web/src/views/Workflow/components/Nodes/AddNode.tsx b/web/src/views/Workflow/components/Nodes/AddNode.tsx index 52b8da4f..c40600d6 100644 --- a/web/src/views/Workflow/components/Nodes/AddNode.tsx +++ b/web/src/views/Workflow/components/Nodes/AddNode.tsx @@ -107,7 +107,7 @@ const AddNode: ReactShapeConfig['component'] = ({ node, graph }) => {
{nodeLibrary.map((category, categoryIndex) => { const filteredNodes = category.nodes.filter(nodeType => - nodeType.type !== 'start' && nodeType.type !== 'end' && nodeType.type !== 'loop' && nodeType.type !== 'cycle-start' + nodeType.type !== 'start' && nodeType.type !== 'end' && nodeType.type !== 'iteration' && nodeType.type !== 'loop' && nodeType.type !== 'cycle-start' ); if (filteredNodes.length === 0) return null; diff --git a/web/src/views/Workflow/components/Nodes/LoopNode.tsx b/web/src/views/Workflow/components/Nodes/LoopNode.tsx index dac91b68..40b4b8ec 100644 --- a/web/src/views/Workflow/components/Nodes/LoopNode.tsx +++ b/web/src/views/Workflow/components/Nodes/LoopNode.tsx @@ -33,7 +33,7 @@ const LoopNode: ReactShapeConfig['component'] = ({ node, graph }) => { y: cycleStartBBox.y, data: { type: 'add-node', - label: '添加节点', + label: t('workflow.addNode'), icon: '+', parentId: node.id, cycle: data.id, @@ -61,7 +61,7 @@ const LoopNode: ReactShapeConfig['component'] = ({ node, graph }) => { }, }, }, - zIndex: 3 + zIndex: 10 }); } } @@ -97,7 +97,7 @@ const LoopNode: ReactShapeConfig['component'] = ({ node, graph }) => { y: centerY, data: { type: 'add-node', - label: '添加节点', + label: t('workflow.addNode'), icon: '+', parentId: node.id, cycle: data.id, @@ -128,7 +128,7 @@ const LoopNode: ReactShapeConfig['component'] = ({ node, graph }) => { }, }, }, - zIndex: 3 + zIndex: 10 } graph.addEdge(edgeConfig) diff --git a/web/src/views/Workflow/components/PortClickHandler.tsx b/web/src/views/Workflow/components/PortClickHandler.tsx index 9a644438..9d9225e8 100644 --- a/web/src/views/Workflow/components/PortClickHandler.tsx +++ b/web/src/views/Workflow/components/PortClickHandler.tsx @@ -151,11 +151,11 @@ const PortClickHandler: React.FC = ({ graph }) => { let filteredNodes; if (isChildOfLoop) { - // Use same filtering as AddNode for child nodes of loop + // Use same filtering as AddNode for child nodes of loop, but allow break filteredNodes = category.nodes.filter(nodeType => !['start', 'end', 'loop', 'cycle-start', 'iteration'].includes(nodeType.type)); } else if (isChildOfIteration) { - // Filter out loop and iteration nodes for children of iteration nodes - filteredNodes = category.nodes.filter(nodeType => !['start', 'end', 'loop', 'break', 'cycle-start', 'iteration'].includes(nodeType.type)); + // Filter out loop and iteration nodes for children of iteration nodes, but allow break + filteredNodes = category.nodes.filter(nodeType => !['start', 'end', 'loop', 'cycle-start', 'iteration'].includes(nodeType.type)); } else { // Original filtering for non-loop child nodes filteredNodes = category.nodes.filter(nodeType => !['start', 'end', 'break', 'cycle-start'].includes(nodeType.type)); diff --git a/web/src/views/Workflow/components/Properties/AssignmentList/index.tsx b/web/src/views/Workflow/components/Properties/AssignmentList/index.tsx index 97f28668..494e4342 100644 --- a/web/src/views/Workflow/components/Properties/AssignmentList/index.tsx +++ b/web/src/views/Workflow/components/Properties/AssignmentList/index.tsx @@ -60,7 +60,7 @@ const AssignmentList: FC = ({ > vo.nodeData.type === 'loop' || vo.value.includes('conv.'))} popupMatchSelectWidth={false} onChange={() => { form.setFieldValue([parentName, name, 'operation'], undefined); diff --git a/web/src/views/Workflow/components/Properties/CategoryList/index.tsx b/web/src/views/Workflow/components/Properties/CategoryList/index.tsx index 69ed2030..6fa47421 100644 --- a/web/src/views/Workflow/components/Properties/CategoryList/index.tsx +++ b/web/src/views/Workflow/components/Properties/CategoryList/index.tsx @@ -1,17 +1,19 @@ import { type FC } from 'react'; import { useTranslation } from 'react-i18next'; -import { Input, Button, Form, Space } from 'antd'; -import { PlusOutlined, CopyOutlined, DeleteOutlined, ExpandOutlined } from '@ant-design/icons'; +import { Button, Form, Space } from 'antd'; +import { DeleteOutlined } from '@ant-design/icons'; import { Graph, Node } from '@antv/x6'; -import type { PortMetadata } from '@antv/x6/lib/model/port'; +import Editor from '../../Editor'; +import type { Suggestion } from '../../Editor/plugin/AutocompletePlugin' interface CategoryListProps { parentName: string; + options: Suggestion[]; selectedNode?: Node | null; graphRef?: React.MutableRefObject; } -const CategoryList: FC = ({ parentName, selectedNode, graphRef }) => { +const CategoryList: FC = ({ parentName, selectedNode, graphRef, options }) => { const { t } = useTranslation(); const form = Form.useFormInstance(); const formValues = Form.useWatch([parentName], form); @@ -167,9 +169,9 @@ const CategoryList: FC = ({ parentName, selectedNode, graphRe name={[name, 'class_name']} noStyle > -
diff --git a/web/src/views/Workflow/components/Properties/ConditionList/index.tsx b/web/src/views/Workflow/components/Properties/ConditionList/index.tsx index 8fbebeda..d809fec5 100644 --- a/web/src/views/Workflow/components/Properties/ConditionList/index.tsx +++ b/web/src/views/Workflow/components/Properties/ConditionList/index.tsx @@ -1,6 +1,6 @@ import { type FC } from 'react' import { useTranslation } from 'react-i18next'; -import { Form, Button, Select, Row, Col, InputNumber, Radio, type SelectProps } from 'antd' +import { Form, Button, Select, Row, Col, InputNumber, Radio, Input, type SelectProps } from 'antd' import { DeleteOutlined } from '@ant-design/icons'; import type { Suggestion } from '../../Editor/plugin/AutocompletePlugin' @@ -114,7 +114,7 @@ const ConditionList: FC = ({
vo.value.includes('sys.') || vo.value.includes('conv.') || vo.nodeData.type === 'loop')} size="small" allowClear={false} popupMatchSelectWidth={false} @@ -186,7 +186,7 @@ const ConditionList: FC = ({ True False - : + : } diff --git a/web/src/views/Workflow/components/Properties/CycleVarsList/index.tsx b/web/src/views/Workflow/components/Properties/CycleVarsList/index.tsx index c05cce25..4d436af0 100644 --- a/web/src/views/Workflow/components/Properties/CycleVarsList/index.tsx +++ b/web/src/views/Workflow/components/Properties/CycleVarsList/index.tsx @@ -1,6 +1,6 @@ import { type FC } from 'react' import { useTranslation } from 'react-i18next'; -import { Form, Button, Select, Row, Col, Input } from 'antd' +import { Form, Select, Row, Col, Input } from 'antd' import { DeleteOutlined, PlusOutlined } from '@ant-design/icons'; import VariableSelect from '../VariableSelect' @@ -36,7 +36,6 @@ const CycleVarsList: FC = ({ value = [], options, parentName, - onChange, selectedNode, graphRef }) => { @@ -139,12 +138,17 @@ const CycleVarsList: FC = ({ {currentInputType === 'variable' ? ( { + const currentType = value?.[index]?.type; + if (!currentType) return true; + + return option.dataType === currentType + })} /> ) : ( diff --git a/web/src/views/Workflow/components/Properties/GroupVariableList/index.tsx b/web/src/views/Workflow/components/Properties/GroupVariableList/index.tsx index 2b2db0f7..61cdd7b0 100644 --- a/web/src/views/Workflow/components/Properties/GroupVariableList/index.tsx +++ b/web/src/views/Workflow/components/Properties/GroupVariableList/index.tsx @@ -18,8 +18,22 @@ const GroupVariableList: FC = ({ isCanAdd = false }) => { const { t } = useTranslation(); + const form = Form.useFormInstance(); + const value = form.getFieldValue(name) || []; + + console.log('GroupVariableList', value) if (!isCanAdd) { + // Filter options based on first variable's dataType if value exists + let filteredOptions = options; + if (value.length > 0) { + const firstVariableValue = value[0]; + const firstVariable = options.find(opt => `{{${opt.value}}}` === firstVariableValue); + if (firstVariable) { + filteredOptions = options.filter(opt => opt.dataType === firstVariable.dataType); + } + } + return (
@@ -38,7 +52,7 @@ const GroupVariableList: FC = ({ > @@ -77,7 +91,18 @@ const GroupVariableList: FC = ({ > { + const currentGroupValue = value[name]?.value || []; + if (currentGroupValue.length > 0) { + const firstVariableValue = currentGroupValue[0]; + const firstVariable = options.find(opt => `{{${opt.value}}}` === firstVariableValue); + if (firstVariable) { + return options.filter(opt => opt.dataType === firstVariable.dataType); + } + } + return options; + })() + } mode="multiple" /> diff --git a/web/src/views/Workflow/components/Properties/HttpRequest/index.tsx b/web/src/views/Workflow/components/Properties/HttpRequest/index.tsx index bbb3238d..5823c1d8 100644 --- a/web/src/views/Workflow/components/Properties/HttpRequest/index.tsx +++ b/web/src/views/Workflow/components/Properties/HttpRequest/index.tsx @@ -90,7 +90,7 @@ const HttpRequest: FC<{ options: Suggestion[]; selectedNode?: any; graphRef?: an
- + vo.dataType === 'string' || vo.dataType === 'number')} variant="outlined" /> @@ -144,7 +144,7 @@ const HttpRequest: FC<{ options: Suggestion[]; selectedNode?: any; graphRef?: an vo.dataType === 'string' || vo.dataType === 'number')} filterBooleanType={true} /> @@ -154,7 +154,7 @@ const HttpRequest: FC<{ options: Suggestion[]; selectedNode?: any; graphRef?: an vo.dataType === 'string' || vo.dataType === 'number')} isArray={false} title="JSON" /> diff --git a/web/src/views/Workflow/components/Properties/VariableSelect.tsx b/web/src/views/Workflow/components/Properties/VariableSelect.tsx index b92475d7..5f0f1f0b 100644 --- a/web/src/views/Workflow/components/Properties/VariableSelect.tsx +++ b/web/src/views/Workflow/components/Properties/VariableSelect.tsx @@ -91,6 +91,7 @@ const VariableSelect: FC = ({ showSearch allowClear={allowClear} filterOption={(input, option) => { + if (input === '/') return true; if (option?.options) { return option.label?.toLowerCase().includes(input.toLowerCase()) || option.options.some((opt: any) => diff --git a/web/src/views/Workflow/components/Properties/index.tsx b/web/src/views/Workflow/components/Properties/index.tsx index 765fd207..2903b2c9 100644 --- a/web/src/views/Workflow/components/Properties/index.tsx +++ b/web/src/views/Workflow/components/Properties/index.tsx @@ -22,6 +22,7 @@ import ConditionList from './ConditionList' import CycleVarsList from './CycleVarsList' import AssignmentList from './AssignmentList' import ToolConfig from './ToolConfig' +// import { calculateVariableList } from './utils/variableListCalculator' interface PropertiesProps { selectedNode?: Node | null; @@ -338,112 +339,35 @@ const Properties: FC = ({ const parentLoopNode = getParentLoopNode(selectedNode.id); console.log('childNodeIds', selectedNode, childNodeIds) - const allRelevantNodeIds = [...allPreviousNodeIds, ...childNodeIds]; + let allRelevantNodeIds = [...allPreviousNodeIds, ...childNodeIds]; - // Add parent loop/iteration node variables if current node is a child + // Add variables from nodes preceding the parent loop/iteration node if current node is a child if (parentLoopNode) { - const parentData = parentLoopNode.getData(); - const parentNodeId = parentLoopNode.getData().id; - - if (parentData.type === 'loop') { - const cycleVars = parentData.cycle_vars || []; - cycleVars.forEach((cycleVar: any) => { - const key = `${parentNodeId}_cycle_${cycleVar.name}`; - if (!addedKeys.has(key)) { - addedKeys.add(key); - variableList.push({ - key, - label: cycleVar.name, - type: 'variable', - dataType: cycleVar.type || 'String', - value: `${parentNodeId}.${cycleVar.name}`, - nodeData: parentData, - }); - } - }); - } else if (parentData.type === 'iteration') { - // Add item and index variables for iteration parent - const itemKey = `${parentNodeId}_item`; - const indexKey = `${parentNodeId}_index`; - - if (!addedKeys.has(itemKey)) { - addedKeys.add(itemKey); - variableList.push({ - key: itemKey, - label: 'item', - type: 'variable', - dataType: 'Object', - value: `${parentNodeId}.item`, - nodeData: parentData, - }); - } - - if (!addedKeys.has(indexKey)) { - addedKeys.add(indexKey); - variableList.push({ - key: indexKey, - label: 'index', - type: 'variable', - dataType: 'Number', - value: `${parentNodeId}.index`, - nodeData: parentData, - }); - } - } - - // Check if parent loop/iteration is connected to http-request via ERROR connection - if (parentData.type === 'loop' || parentData.type === 'iteration') { - const parentPreviousNodeIds = getAllPreviousNodes(parentLoopNode.id); - parentPreviousNodeIds.forEach(prevNodeId => { - const prevNode = nodes.find(n => n.id === prevNodeId); - if (!prevNode) return; - - const prevNodeData = prevNode.getData(); - if (prevNodeData.type === 'http-request') { - // Check if connected via ERROR connection point - const errorEdges = edges.filter(edge => { - return edge.getTargetCellId() === parentLoopNode.id && - edge.getSourceCellId() === prevNodeId && - edge.getSourcePortId() === 'ERROR' - }); - - if (errorEdges.length > 0) { - const errorMessageKey = `${prevNodeData.id}_error_message`; - const errorTypeKey = `${prevNodeData.id}_error_type`; - - if (!addedKeys.has(errorMessageKey)) { - addedKeys.add(errorMessageKey); - variableList.push({ - key: errorMessageKey, - label: 'error_message', - type: 'variable', - dataType: 'string', - value: `${prevNodeData.id}.error_message`, - nodeData: prevNodeData, - }); - } - - if (!addedKeys.has(errorTypeKey)) { - addedKeys.add(errorTypeKey); - variableList.push({ - key: errorTypeKey, - label: 'error_type', - type: 'variable', - dataType: 'string', - value: `${prevNodeData.id}.error_type`, - nodeData: prevNodeData, - }); - } - } - } - }); - } - - // Add variables from nodes preceding the parent loop/iteration node const parentPreviousNodeIds = getAllPreviousNodes(parentLoopNode.id); allRelevantNodeIds.push(...parentPreviousNodeIds); } + + + // Add conversation variables from global config + const conversationVariables = workflowConfig?.variables || []; + + conversationVariables.forEach((variable: any) => { + const key = `CONVERSATION_${variable.name}`; + if (!addedKeys.has(key)) { + addedKeys.add(key); + variableList.push({ + key, + label: variable.name, + type: 'variable', + dataType: variable.type, + value: `conv.${variable.name}`, + nodeData: { type: 'CONVERSATION', name: 'CONVERSATION', icon: '' }, + group: 'CONVERSATION' + }); + } + }); + allRelevantNodeIds.forEach(nodeId => { const node = nodes.find(n => n.id === nodeId); if (!node) return; @@ -496,7 +420,7 @@ const Properties: FC = ({ key: llmKey, label: 'output', type: 'variable', - dataType: 'String', + dataType: 'string', value: `${dataNodeId}.output`, nodeData: nodeData, }); @@ -565,6 +489,17 @@ const Properties: FC = ({ const groupVariables = nodeData.config.group_variables.defaultValue || []; groupVariables?.forEach((groupVar: any) => { if (!groupVar || !groupVar.key) return; + + // Determine dataType from first variable in the group + let groupDataType = 'string'; + if (groupVar.value && Array.isArray(groupVar.value) && groupVar.value.length > 0) { + const firstVariableValue = groupVar.value[0]; + const firstVariable = variableList.find(v => `{{${v.value}}}` === firstVariableValue); + if (firstVariable) { + groupDataType = firstVariable.dataType; + } + } + const groupVarKey = `${dataNodeId}_${groupVar.key}`; if (!addedKeys.has(groupVarKey)) { addedKeys.add(groupVarKey); @@ -572,14 +507,26 @@ const Properties: FC = ({ key: groupVarKey, label: groupVar.key, type: 'variable', - dataType: 'string', + dataType: groupDataType, value: `${dataNodeId}.${groupVar.key}`, nodeData: nodeData, }); } }); } else { - // If group=false, add output variable + // If group=false, add output variable with type from first group_variable + const groupVariables = nodeData.config.group_variables.defaultValue || []; + const firstVariable = groupVariables[0]; + let outputDataType: string = 'any'; + if (firstVariable) { + const filterVo = [...variableList].find(v => { + return `{{${v.value}}}` === firstVariable + }) + if (filterVo) { + outputDataType = filterVo?.dataType + } + } + const varAggregatorKey = `${dataNodeId}_output`; if (!addedKeys.has(varAggregatorKey)) { addedKeys.add(varAggregatorKey); @@ -587,7 +534,7 @@ const Properties: FC = ({ key: varAggregatorKey, label: 'output', type: 'variable', - dataType: 'string', + dataType: outputDataType, value: `${dataNodeId}.output`, nodeData: nodeData, }); @@ -684,21 +631,20 @@ const Properties: FC = ({ nodeData: nodeData, }); } - if (!addedKeys.has(outputKey)) { - addedKeys.add(outputKey); - variableList.push({ - key: outputKey, - label: 'output', - type: 'variable', - dataType: 'string', - value: `${dataNodeId}.output`, - nodeData: nodeData, - }); - } + // if (!addedKeys.has(outputKey)) { + // addedKeys.add(outputKey); + // variableList.push({ + // key: outputKey, + // label: 'output', + // type: 'variable', + // dataType: 'string', + // value: `${dataNodeId}.output`, + // nodeData: nodeData, + // }); + // } break case 'iteration': const iterationOutputKey = `${dataNodeId}_output`; - const iterationItemKey = `${dataNodeId}_item`; if (!addedKeys.has(iterationOutputKey)) { addedKeys.add(iterationOutputKey); // Get the data type from the output configuration, default to string @@ -715,22 +661,11 @@ const Properties: FC = ({ key: iterationOutputKey, label: 'output', type: 'variable', - dataType: outputDataType, + dataType: `array[${outputDataType}]`, value: `${dataNodeId}.output`, nodeData: nodeData, }); } - if (!addedKeys.has(iterationItemKey)) { - addedKeys.add(iterationItemKey); - variableList.push({ - key: iterationItemKey, - label: 'item', - type: 'variable', - dataType: 'string', - value: `${dataNodeId}.item`, - nodeData: nodeData, - }); - } break case 'loop': const cycleVars = nodeData.config.cycle_vars.defaultValue || []; @@ -760,47 +695,337 @@ const Properties: FC = ({ key: toolDataKey, label: 'data', type: 'variable', - dataType: 'object', + dataType: 'string', value: `${dataNodeId}.data`, nodeData: nodeData, }); } break + case 'memory-read': + const memoryReadAnswerKey = `${dataNodeId}_answer`; + const memoryReadIntermediateOutputs = `${dataNodeId}_intermediate_outputs`; + if (!addedKeys.has(memoryReadAnswerKey)) { + addedKeys.add(memoryReadAnswerKey); + variableList.push({ + key: memoryReadAnswerKey, + label: 'answer', + type: 'variable', + dataType: 'string', + value: `${dataNodeId}.answer`, + nodeData: nodeData, + }); + } + if (!addedKeys.has(memoryReadIntermediateOutputs)) { + addedKeys.add(memoryReadIntermediateOutputs); + variableList.push({ + key: memoryReadIntermediateOutputs, + label: 'intermediate_outputs', + type: 'variable', + dataType: 'array[object]', + value: `${dataNodeId}.intermediate_outputs`, + nodeData: nodeData, + }); + } + break } }); - // Add conversation variables from global config - const conversationVariables = workflowConfig?.variables || []; - - conversationVariables.forEach((variable: any) => { - const key = `CONVERSATION_${variable.name}`; - if (!addedKeys.has(key)) { - addedKeys.add(key); - variableList.push({ - key, - label: variable.name, - type: 'variable', - dataType: variable.type, - value: `conv.${variable.name}`, - nodeData: { type: 'CONVERSATION', name: 'CONVERSATION', icon: '' }, - group: 'CONVERSATION' + + // Add parent loop/iteration node variables if current node is a child + if (parentLoopNode) { + const parentData = parentLoopNode.getData(); + const parentNodeId = parentLoopNode.getData().id; + + if (parentData.type === 'loop') { + const cycleVars = parentData.cycle_vars || []; + cycleVars.forEach((cycleVar: any) => { + const key = `${parentNodeId}_cycle_${cycleVar.name}`; + if (!addedKeys.has(key)) { + addedKeys.add(key); + variableList.push({ + key, + label: cycleVar.name, + type: 'variable', + dataType: cycleVar.type || 'String', + value: `${parentNodeId}.${cycleVar.name}`, + nodeData: parentData, + }); + } + }); + } else if (parentData.type === 'iteration') { + // Add item and index variables for iteration parent only if input has value + if (parentData.config.input.defaultValue) { + const itemKey = `${parentNodeId}_item`; + const indexKey = `${parentNodeId}_index`; + + // Determine item dataType from input variable + let itemDataType = 'object'; + const inputVariable = variableList.find(v => `{{${v.value}}}` === parentData.config.input.defaultValue); + console.log('itemDataType defaultValue', parentData.config.input.defaultValue, variableList, inputVariable) + if (inputVariable && inputVariable.dataType.startsWith('array[')) { + itemDataType = inputVariable.dataType.replace(/^array\[(.+)\]$/, '$1'); + console.log('itemDataType', itemDataType) + } + + + if (!addedKeys.has(itemKey)) { + addedKeys.add(itemKey); + variableList.push({ + key: itemKey, + label: 'item', + type: 'variable', + dataType: itemDataType, + value: `${parentNodeId}.item`, + nodeData: parentData, + }); + } + + if (!addedKeys.has(indexKey)) { + addedKeys.add(indexKey); + variableList.push({ + key: indexKey, + label: 'index', + type: 'variable', + dataType: 'number', + value: `${parentNodeId}.index`, + nodeData: parentData, + }); + } + } + } + + // Check if parent loop/iteration is connected to http-request via ERROR connection + if (parentData.type === 'loop' || parentData.type === 'iteration') { + const parentPreviousNodeIds = getAllPreviousNodes(parentLoopNode.id); + parentPreviousNodeIds.forEach(prevNodeId => { + const prevNode = nodes.find(n => n.id === prevNodeId); + if (!prevNode) return; + + const prevNodeData = prevNode.getData(); + if (prevNodeData.type === 'http-request') { + // Check if connected via ERROR connection point + const errorEdges = edges.filter(edge => { + return edge.getTargetCellId() === parentLoopNode.id && + edge.getSourceCellId() === prevNodeId && + edge.getSourcePortId() === 'ERROR' + }); + + if (errorEdges.length > 0) { + const errorMessageKey = `${prevNodeData.id}_error_message`; + const errorTypeKey = `${prevNodeData.id}_error_type`; + + if (!addedKeys.has(errorMessageKey)) { + addedKeys.add(errorMessageKey); + variableList.push({ + key: errorMessageKey, + label: 'error_message', + type: 'variable', + dataType: 'string', + value: `${prevNodeData.id}.error_message`, + nodeData: prevNodeData, + }); + } + + if (!addedKeys.has(errorTypeKey)) { + addedKeys.add(errorTypeKey); + variableList.push({ + key: errorTypeKey, + label: 'error_type', + type: 'variable', + dataType: 'string', + value: `${prevNodeData.id}.error_type`, + nodeData: prevNodeData, + }); + } + } + } }); } - }); + } return variableList; }, [selectedNode, graphRef, workflowConfig?.variables]); // Filter out boolean type variables for loop and llm nodes - const getFilteredVariableList = (nodeType?: string) => { - if (nodeType === 'loop' || nodeType === 'llm') { - return variableList.filter(variable => variable.dataType !== 'boolean'); + const getFilteredVariableList = (nodeType?: string, key?: string) => { + // Check if current node is a child of iteration node + const parentIterationNode = selectedNode ? (() => { + const nodes = graphRef.current?.getNodes() || []; + const nodeData = selectedNode.getData(); + const cycle = nodeData?.cycle; + + if (cycle) { + const parentNode = nodes.find(n => n.getData().id === cycle); + if (parentNode) { + const parentData = parentNode.getData(); + if (parentData?.type === 'iteration') { + return parentNode; + } + } + } + return null; + })() : null; + + // Helper function to add parent iteration variables + const addParentIterationVars = (filteredList: any[]) => { + if (parentIterationNode) { + const parentData = parentIterationNode.getData(); + const parentNodeId = parentData.id; + + if (parentData.config?.input?.defaultValue) { + const itemKey = `${parentNodeId}_item`; + const indexKey = `${parentNodeId}_index`; + + const existingItemVar = filteredList.find(v => v.key === itemKey); + const existingIndexVar = filteredList.find(v => v.key === indexKey); + + if (!existingItemVar) { + // Determine item dataType from input variable + let itemDataType = 'object'; + const inputVariable = variableList.find(v => `{{${v.value}}}` === parentData.config.input.defaultValue); + if (inputVariable && inputVariable.dataType.startsWith('array[')) { + itemDataType = inputVariable.dataType.replace(/^array\[(.+)\]$/, '$1'); + } + + filteredList.push({ + key: itemKey, + label: 'item', + type: 'variable', + dataType: itemDataType, + value: `${parentNodeId}.item`, + nodeData: parentData, + }); + } + + if (!existingIndexVar) { + filteredList.push({ + key: indexKey, + label: 'index', + type: 'variable', + dataType: 'number', + value: `${parentNodeId}.index`, + nodeData: parentData, + }); + } + } + } + return filteredList; + }; + + if (nodeType === 'llm') { + // For LLM nodes that are children of iteration or loop nodes, include parent variables + const parentLoopNode = selectedNode ? (() => { + const nodes = graphRef.current?.getNodes() || []; + const nodeData = selectedNode.getData(); + const cycle = nodeData?.cycle; + + if (cycle) { + const parentNode = nodes.find(n => n.getData().id === cycle); + if (parentNode) { + const parentData = parentNode.getData(); + if (parentData?.type === 'loop' || parentData?.type === 'iteration') { + return parentNode; + } + } + } + return null; + })() : null; + + let filteredList = variableList.filter(variable => variable.dataType !== 'boolean'); + + // If this LLM node is a child of iteration/loop, ensure parent variables are included + if (parentLoopNode) { + const parentData = parentLoopNode.getData(); + const parentNodeId = parentData.id; + + // Ensure parent loop/iteration variables are included + if (parentData.type === 'loop') { + const cycleVars = parentData.cycle_vars || []; + cycleVars.forEach((cycleVar: any) => { + const key = `${parentNodeId}_cycle_${cycleVar.name}`; + const existingVar = filteredList.find(v => v.key === key); + if (!existingVar && cycleVar.name && cycleVar.type !== 'boolean') { + filteredList.push({ + key, + label: cycleVar.name, + type: 'variable', + dataType: cycleVar.type || 'String', + value: `${parentNodeId}.${cycleVar.name}`, + nodeData: parentData, + }); + } + }); + } else if (parentData.type === 'iteration') { + // Add item and index variables for iteration parent + if (parentData.config?.input?.defaultValue) { + const itemKey = `${parentNodeId}_item`; + const indexKey = `${parentNodeId}_index`; + + const existingItemVar = filteredList.find(v => v.key === itemKey); + const existingIndexVar = filteredList.find(v => v.key === indexKey); + + if (!existingItemVar) { + // Determine item dataType from input variable + let itemDataType = 'object'; + const inputVariable = variableList.find(v => `{{${v.value}}}` === parentData.config.input.defaultValue); + if (inputVariable && inputVariable.dataType.startsWith('array[')) { + itemDataType = inputVariable.dataType.replace(/^array\[(.+)\]$/, '$1'); + } + + filteredList.push({ + key: itemKey, + label: 'item', + type: 'variable', + dataType: itemDataType, + value: `${parentNodeId}.item`, + nodeData: parentData, + }); + } + + if (!existingIndexVar) { + filteredList.push({ + key: indexKey, + label: 'index', + type: 'variable', + dataType: 'Number', + value: `${parentNodeId}.index`, + nodeData: parentData, + }); + } + } + } + } + + return filteredList; } - return variableList; + if (nodeType === 'knowledge-retrieval' || nodeType === 'parameter-extractor' && key !== 'prompt' || nodeType === 'memory-read' || nodeType === 'memory-write' || nodeType === 'question-classifier') { + let filteredList = variableList.filter(variable => variable.dataType === 'string'); + return addParentIterationVars(filteredList); + } + if (nodeType === 'parameter-extractor' && key === 'prompt') { + let filteredList = variableList.filter(variable => variable.dataType === 'string' || variable.dataType === 'number'); + return addParentIterationVars(filteredList); + } + if (nodeType === 'iteration' && key === 'output') { + return variableList.filter(variable => variable.value.includes('sys.')); + } + if (nodeType === 'iteration') { + return variableList.filter(variable => variable.dataType.includes('array')); + } + if (nodeType === 'loop' && key === 'condition') { + let filteredList = variableList.filter(variable => variable.nodeData.type !== 'loop'); + return addParentIterationVars(filteredList); + } + + // For all other node types, add parent iteration variables if applicable + let baseList = variableList; + return addParentIterationVars(baseList); }; + // const defaultVariableList = calculateVariableList(selectedNode as Node, graphRef, workflowConfig ) + console.log('values', values) - console.log('variableList', variableList, selectedNode?.data) + // console.log('variableList', variableList, defaultVariableList) return (
@@ -901,11 +1126,10 @@ const Properties: FC = ({ }); } } - return ( variable.nodeData?.type !== 'knowledge-retrieval')} parentName={key} /> @@ -915,7 +1139,12 @@ const Properties: FC = ({ if (selectedNode?.data?.type === 'end' && key === 'output') { return ( - + variable.nodeData?.type !== 'knowledge-retrieval')} + /> ) } @@ -943,7 +1172,7 @@ const Properties: FC = ({ isArray={!!config.isArray} parentName={key} enableJinja2={config.enableJinja2 as boolean} - options={getFilteredVariableList(selectedNode?.data?.type)} + options={getFilteredVariableList(selectedNode?.data?.type, key)} /> ) @@ -964,7 +1193,7 @@ const Properties: FC = ({ @@ -976,7 +1205,7 @@ const Properties: FC = ({ @@ -989,7 +1218,7 @@ const Properties: FC = ({ - + ) @@ -999,7 +1228,7 @@ const Properties: FC = ({ ) @@ -1013,9 +1242,9 @@ const Properties: FC = ({ if (config.filterLoopIterationVars) { const loopIterationVars: Suggestion[] = []; - return [...getFilteredVariableList(selectedNode?.data?.type), ...loopIterationVars]; + return [...getFilteredVariableList(selectedNode?.data?.type, key), ...loopIterationVars]; } - return getFilteredVariableList(selectedNode?.data?.type); + return getFilteredVariableList(selectedNode?.data?.type, key); })() } /> @@ -1060,7 +1289,7 @@ const Properties: FC = ({ ? { - const baseVariableList = getFilteredVariableList(selectedNode?.data?.type); + const baseVariableList = getFilteredVariableList(selectedNode?.data?.type, key); // Apply filtering if specified in config if (config.filterNodeTypes || config.filterVariableNames) { return baseVariableList.filter(variable => { @@ -1068,7 +1297,7 @@ const Properties: FC = ({ (Array.isArray(config.filterNodeTypes) && config.filterNodeTypes.includes(variable.nodeData?.type)); const variableNameMatch = !config.filterVariableNames || (Array.isArray(config.filterVariableNames) && config.filterVariableNames.includes(variable.label)); - return nodeTypeMatch && variableNameMatch; + return nodeTypeMatch || variableNameMatch; }); } // Filter child nodes for iteration output @@ -1085,7 +1314,7 @@ const Properties: FC = ({ }); return baseVariableList.filter(variable => - childNodes.some(node => node.id === variable.nodeData?.id) + childNodes.some(node => node.id === variable.nodeData?.id) || selectedNode?.data?.type === 'iteration' && key === 'output' && variable.value.includes('sys.') ); } return baseVariableList; @@ -1095,7 +1324,12 @@ const Properties: FC = ({ : config.type === 'switch' ? { form.setFieldValue('group_variables', []) } : undefined} /> : config.type === 'categoryList' - ? + ? : config.type === 'conditionList' ? = ({ value: `${selectedNode.getData().id}.${cycleVar.name}`, nodeData: selectedNode.getData(), })); - return [...variableList.filter(variable => { - // Keep conversation variables - if (variable.group === 'CONVERSATION') return true; - // Keep sys variables from start nodes - if (variable.nodeData?.type === 'start' && variable.value?.startsWith('sys.')) return true; - // Keep variables from non-start nodes - if (variable.nodeData?.type !== 'start' && variable.nodeData?.type !== 'http-request' && variable.dataType !== 'boolean') return true; - // Filter out custom variables from start nodes - return false; - }), ...cycleVarSuggestions]; - })() - } + + return [...getFilteredVariableList(selectedNode?.data?.type, key), ...cycleVarSuggestions]; + })()} selectedNode={selectedNode} graphRef={graphRef} addBtnText={t('workflow.config.addCase')} diff --git a/web/src/views/Workflow/constant.ts b/web/src/views/Workflow/constant.ts index 692339da..593639ce 100644 --- a/web/src/views/Workflow/constant.ts +++ b/web/src/views/Workflow/constant.ts @@ -270,7 +270,7 @@ export const nodeLibrary: NodeLibrary[] = [ config: { input: { type: 'variableList', - filterNodeTypes: ['knowledge-retrieval'], + filterNodeTypes: ['knowledge-retrieval', 'iteration', 'loop'], filterVariableNames: ['message'] }, parallel: { @@ -334,8 +334,7 @@ export const nodeLibrary: NodeLibrary[] = [ } } }, - { - type: "assigner", icon: assignerIcon, + { type: "assigner", icon: assignerIcon, config: { assignments: { type: 'assignmentList', @@ -628,4 +627,114 @@ export const graphNodeLibrary: Record = { items: [{ group: 'left' }], }, } +} + + +export interface OutputVariable { + default?: Array<{ + name: string; + type: string; + }>; + define?: string[]; + sys?: Array<{ + name: string; + type: string; + }>; + error?: Array<{ + name: string; + type: string; + }>; +} +export const outputVariable: { [key: string]: OutputVariable } = { + start: { + sys: [ + { name: "message", type: "string" }, + { name: "conversation_id", type: "string" }, + { name: "execution_id", type: "string", }, + { name: "workspace_id", type: "string" }, + { name: "user_id", type: "string" }, + ], + define: ['variables'] + }, + end: { + }, + llm: { + default: [ + { name: "output", type: "string" }, + ] + }, + 'knowledge-retrieval': { + default: [ + { name: "output", type: "array[object]" }, + ] + }, + 'parameter-extractor': { + default: [ + { name: "__is_success", type: "number" }, + { name: "__reason", type: "string" }, + ], + define: ['params'] + }, + 'memory-read': { + default: [ + { name: "answer", type: "string" }, + { name: "intermediate_outputs", type: "array[object]" }, + ], + }, + 'memory-write': { + + }, + 'if-else': { + + }, + 'question-classifier': { + default: [ + { name: "class_name", type: "string" }, + // { name: "output", type: "string" }, + ], + }, + 'iteration': { + default: [ + // { name: "item", type: "string" }, // 仅内部使用 + { name: "output", type: "array[string]" }, + ], + }, + 'loop': { + define: ['cycle_vars'] + }, + 'cycle-start': { + + }, + 'break': { + + }, + 'var-aggregator': { + // default: [ + // { name: "output", type: "string" }, + // ], + define: ['group_variables'] + }, + 'assigner': { + + }, + 'http-request': { + default: [ + { name: "body", type: "string" }, + { name: "status_code", type: "number" }, + ], + error: [ + { name: "error_message", type: "string" }, + { name: "error_type", type: "string" }, + ] + }, + 'tool': { + default: [ + { name: "data", type: "string" }, + ], + }, + 'jinja-render': { + default: [ + { name: "output", type: "string" }, + ], + }, } \ No newline at end of file diff --git a/web/src/views/Workflow/hooks/useWorkflowGraph.ts b/web/src/views/Workflow/hooks/useWorkflowGraph.ts index dfbf2e92..dc7001e5 100644 --- a/web/src/views/Workflow/hooks/useWorkflowGraph.ts +++ b/web/src/views/Workflow/hooks/useWorkflowGraph.ts @@ -282,9 +282,21 @@ export const useWorkflowGraph = ({ }, 100) } if (edges.length) { - // 去重处理：相同节点之间的连线仅连一次 + // 去重处理：对于if-else和question-classifier节点，不同连接桩允许连接到相同节点 const uniqueEdges = edges.filter((edge, index, arr) => { - return arr.findIndex(e => e.source === edge.source && e.target === edge.target) === index; + return arr.findIndex(e => { + const sourceCell = graphRef.current?.getCellById(e.source); + const sourceType = sourceCell?.getData()?.type; + const isMultiPortNode = sourceType === 'question-classifier' || sourceType === 'if-else'; + + if (isMultiPortNode) { + // 多端口节点需要同时比较source、target和label + return e.source === edge.source && e.target === edge.target && e.label === edge.label; + } else { + // 其他节点只比较source和target + return e.source === edge.source && e.target === edge.target; + } + }) === index; }); const edgeList = uniqueEdges.map(edge => { @@ -954,7 +966,10 @@ export const useWorkflowGraph = ({ itemConfig = { ...itemConfig, ...data.config[key].defaultValue, - knowledge_bases: knowledge_bases?.map((vo: any) => ({ kb_id: vo.id, ...vo.config })) + knowledge_bases: knowledge_bases?.map((vo: any) => { + const kb_config = vo.config || { similarity_threshold: vo.similarity_threshold, strategy: vo.strategy, top_k: vo.top_k, weight: vo.weight } + return { kb_id: vo.kb_id || vo.id, ...kb_config, } + }) } } }) @@ -1025,8 +1040,21 @@ export const useWorkflowGraph = ({ }) .filter(edge => edge !== null) .filter((edge, index, arr) => { - // 去重：相同节点之间的连线仅保留一次 - return arr.findIndex(e => e && e.source === edge?.source && e.target === edge?.target) === index; + // 去重：对于if-else和question-classifier节点，不同连接桩允许连接到相同节点 + return arr.findIndex(e => { + if (!e || !edge) return false; + const sourceCell = graphRef.current?.getCellById(e.source); + const sourceType = sourceCell?.getData()?.type; + const isMultiPortNode = sourceType === 'question-classifier' || sourceType === 'if-else'; + + if (isMultiPortNode) { + // 多端口节点需要同时比较source、target和label + return e.source === edge.source && e.target === edge.target && e.label === edge.label; + } else { + // 其他节点只比较source和target + return e.source === edge.source && e.target === edge.target; + } + }) === index; }), } saveWorkflowConfig(config.app_id, params as WorkflowConfig)