diff --git a/api/app/controllers/user_memory_controllers.py b/api/app/controllers/user_memory_controllers.py index c8d24d92..10b396a7 100644 --- a/api/app/controllers/user_memory_controllers.py +++ b/api/app/controllers/user_memory_controllers.py @@ -2,8 +2,8 @@ 用户记忆相关的控制器 包含用户摘要、记忆洞察、节点统计、图数据和用户档案等接口 """ -from typing import Optional, List - +from typing import Optional +import datetime from sqlalchemy.orm import Session from fastapi import APIRouter, Depends, Header @@ -12,6 +12,7 @@ from app.core.language_utils import get_language_from_header 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.core.api_key_utils import timestamp_to_datetime from app.services.user_memory_service import ( UserMemoryService, analytics_memory_types, @@ -21,25 +22,14 @@ 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 ( - MemoryInsightReportData, - UserSummaryData, - SingleUserCacheResultData, - GenerateCacheErrorItem, - WorkspaceCacheResultData, - WorkspaceCacheErrorItem, - MemoryTypeStatItem, - GraphData, - GraphNodeData, - GraphEdgeData, - GraphStatistics, - RelationshipEvolutionData, -) from app.repositories.workspace_repository import WorkspaceRepository from app.repositories.end_user_repository import EndUserRepository from app.schemas.end_user_info_schema import ( + EndUserInfoResponse, + EndUserInfoCreate, EndUserInfoUpdate, ) +from app.models.end_user_model import EndUser from app.dependencies import get_current_user from app.models.user_model import User @@ -71,22 +61,13 @@ async def get_memory_insight_report_api( try: # 调用服务层获取缓存数据 result = await user_memory_service.get_cached_memory_insight(db, end_user_id) - data = MemoryInsightReportData( - memory_insight=result.get("memory_insight"), - behavior_pattern=result.get("behavior_pattern"), - key_findings=result.get("key_findings"), - growth_trajectory=result.get("growth_trajectory"), - updated_at=result.get("updated_at"), - is_cached=result["is_cached"], - message=result.get("message"), - ) - if data.is_cached: + if result["is_cached"]: api_logger.info(f"成功返回缓存的记忆洞察报告: end_user_id={end_user_id}") - return success(data=data.model_dump(), msg="查询成功") + return success(data=result, msg="查询成功") else: api_logger.info(f"记忆洞察报告缓存不存在: end_user_id={end_user_id}") - return success(data=data.model_dump(), msg="数据尚未生成") + return success(data=result, msg="数据尚未生成") except Exception as e: api_logger.error(f"记忆洞察报告查询失败: end_user_id={end_user_id}, error={str(e)}") return fail(BizCode.INTERNAL_ERROR, "记忆洞察报告查询失败", str(e)) @@ -124,22 +105,13 @@ async def get_user_summary_api( try: # 调用服务层获取缓存数据 result = await user_memory_service.get_cached_user_summary(db, end_user_id, model_id, language) - data = UserSummaryData( - user_summary=result.get("user_summary"), - personality=result.get("personality"), - core_values=result.get("core_values"), - one_sentence=result.get("one_sentence"), - updated_at=result.get("updated_at"), - is_cached=result["is_cached"], - message=result.get("message"), - ) - if data.is_cached: + if result["is_cached"]: api_logger.info(f"成功返回缓存的用户摘要: end_user_id={end_user_id}") - return success(data=data.model_dump(), msg="查询成功") + return success(data=result, msg="查询成功") else: api_logger.info(f"用户摘要缓存不存在: end_user_id={end_user_id}") - return success(data=data.model_dump(), msg="数据尚未生成") + return success(data=result, msg="数据尚未生成") except Exception as e: api_logger.error(f"用户摘要查询失败: end_user_id={end_user_id}, error={str(e)}") return fail(BizCode.INTERNAL_ERROR, "用户摘要查询失败", str(e)) @@ -193,32 +165,32 @@ async def generate_cache_api( language=language) # 构建响应 - errors: List[GenerateCacheErrorItem] = [] - if not insight_result["success"]: - errors.append(GenerateCacheErrorItem( - type="insight", - error=insight_result.get("error"), - )) - if not summary_result["success"]: - errors.append(GenerateCacheErrorItem( - type="summary", - error=summary_result.get("error"), - )) + result = { + "end_user_id": end_user_id, + "insight_success": insight_result["success"], + "summary_success": summary_result["success"], + "errors": [] + } - data = SingleUserCacheResultData( - end_user_id=end_user_id, - insight_success=insight_result["success"], - summary_success=summary_result["success"], - errors=errors, - ) + # 收集错误信息 + if not insight_result["success"]: + result["errors"].append({ + "type": "insight", + "error": insight_result.get("error") + }) + if not summary_result["success"]: + result["errors"].append({ + "type": "summary", + "error": summary_result.get("error") + }) # 记录结果 - if data.insight_success and data.summary_success: + if result["insight_success"] and result["summary_success"]: api_logger.info(f"成功为用户 {end_user_id} 生成缓存") else: - api_logger.warning(f"用户 {end_user_id} 的缓存生成部分失败: {[e.model_dump() for e in errors]}") + api_logger.warning(f"用户 {end_user_id} 的缓存生成部分失败: {result['errors']}") - return success(data=data.model_dump(), msg="生成完成") + return success(data=result, msg="生成完成") else: # 为整个工作空间生成 @@ -226,29 +198,13 @@ async def generate_cache_api( result = await user_memory_service.generate_cache_for_workspace(db, workspace_id, language=language) - ws_errors = [ - WorkspaceCacheErrorItem( - end_user_id=e.get("end_user_id"), - insight_error=e.get("insight_error"), - summary_error=e.get("summary_error"), - error=e.get("error"), - ) - for e in result.get("errors", []) - ] - data = WorkspaceCacheResultData( - total_users=result["total_users"], - successful=result["successful"], - failed=result["failed"], - errors=ws_errors, - ) - # 记录统计信息 api_logger.info( f"工作空间 {workspace_id} 批量生成完成: " - f"总数={data.total_users}, 成功={data.successful}, 失败={data.failed}" + f"总数={result['total_users']}, 成功={result['successful']}, 失败={result['failed']}" ) - return success(data=data.model_dump(), msg="批量生成完成") + return success(data=result, msg="批量生成完成") except Exception as e: api_logger.error(f"缓存生成失败: user={current_user.username}, error={str(e)}") @@ -275,21 +231,11 @@ async def get_node_statistics_api( # 调用新的记忆类型统计函数 result = await analytics_memory_types(db, end_user_id) - # 使用 schema 模型构建响应 - stat_items = [ - MemoryTypeStatItem( - type=item["type"], - count=item["count"], - percentage=item["percentage"], - ) - for item in result - ] - # 计算总数用于日志 - total_count = sum(item.count for item in stat_items) + total_count = sum(item["count"] for item in result) api_logger.info( - f"成功获取记忆类型统计: end_user_id={end_user_id}, 总记忆数={total_count}, 类型数={len(stat_items)}") - return success(data=[item.model_dump() for item in stat_items], msg="查询成功") + f"成功获取记忆类型统计: end_user_id={end_user_id}, 总记忆数={total_count}, 类型数={len(result)}") + return success(data=result, msg="查询成功") except Exception as e: api_logger.error(f"记忆类型查询失败: end_user_id={end_user_id}, error={str(e)}") return fail(BizCode.INTERNAL_ERROR, "记忆类型查询失败", str(e)) @@ -340,26 +286,17 @@ async def get_graph_data_api( depth=depth, center_node_id=center_node_id ) - - # 使用 schema 模型构建响应 - data = GraphData( - nodes=[GraphNodeData(**n) for n in result.get("nodes", [])], - edges=[GraphEdgeData(**e) for e in result.get("edges", [])], - statistics=GraphStatistics(**result.get("statistics", {})), - message=result.get("message"), - ) - # 检查是否有错误消息 - if data.message is not None and data.statistics.total_nodes == 0: - api_logger.warning(f"图数据查询返回空结果: {data.message}") - return success(data=data.model_dump(), msg=data.message) + if "message" in result and result["statistics"]["total_nodes"] == 0: + api_logger.warning(f"图数据查询返回空结果: {result.get('message')}") + return success(data=result, msg=result.get("message", "查询成功")) api_logger.info( f"成功获取图数据: end_user_id={end_user_id}, " - f"nodes={data.statistics.total_nodes}, " - f"edges={data.statistics.total_edges}" + f"nodes={result['statistics']['total_nodes']}, " + f"edges={result['statistics']['total_edges']}" ) - return success(data=data.model_dump(), msg="查询成功") + return success(data=result, msg="查询成功") except Exception as e: api_logger.error(f"图数据查询失败: end_user_id={end_user_id}, error={str(e)}") @@ -386,24 +323,16 @@ async def get_community_graph_data_api( try: result = await analytics_community_graph_data(db=db, end_user_id=end_user_id) - # 使用 schema 模型构建响应 - data = GraphData( - nodes=[GraphNodeData(**n) for n in result.get("nodes", [])], - edges=[GraphEdgeData(**e) for e in result.get("edges", [])], - statistics=GraphStatistics(**result.get("statistics", {})), - message=result.get("message"), - ) - - if data.message is not None and data.statistics.total_nodes == 0: - api_logger.warning(f"社区图谱查询返回空结果: {data.message}") - return success(data=data.model_dump(), msg=data.message) + if "message" in result and result["statistics"]["total_nodes"] == 0: + api_logger.warning(f"社区图谱查询返回空结果: {result.get('message')}") + return success(data=result, msg=result.get("message", "查询成功")) api_logger.info( f"成功获取社区图谱: end_user_id={end_user_id}, " - f"nodes={data.statistics.total_nodes}, " - f"edges={data.statistics.total_edges}" + f"nodes={result['statistics']['total_nodes']}, " + f"edges={result['statistics']['total_edges']}" ) - return success(data=data.model_dump(), msg="查询成功") + return success(data=result, msg="查询成功") except Exception as e: api_logger.error(f"社区图谱查询失败: end_user_id={end_user_id}, error={str(e)}") @@ -566,13 +495,13 @@ async def memory_space_relationship_evolution(id: str, label: str, await emotion.close() await interaction.close() - data = RelationshipEvolutionData( - emotion=emotion_result, - interaction=interaction_result, - ) + result = { + "emotion": emotion_result, + "interaction": interaction_result + } api_logger.info(f"关系演变查询成功: id={id}, table={label}") - return success(data=data.model_dump(), msg="关系演变") + return success(data=result, msg="关系演变") 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) diff --git a/api/app/schemas/user_memory_schema.py b/api/app/schemas/user_memory_schema.py deleted file mode 100644 index e0149ceb..00000000 --- a/api/app/schemas/user_memory_schema.py +++ /dev/null @@ -1,118 +0,0 @@ -""" -用户记忆相关的请求和响应模型 -包含用户摘要、记忆洞察、节点统计、图数据和用户档案等接口的 Schema -""" -from typing import Optional, List, Dict, Any - -from pydantic import BaseModel, Field - - -# ==================== 记忆洞察报告 ==================== - -class MemoryInsightReportData(BaseModel): - """记忆洞察报告数据""" - memory_insight: Optional[str] = Field(None, description="总体概述") - behavior_pattern: Optional[str] = Field(None, description="行为模式") - key_findings: Optional[List[str]] = Field(None, description="关键发现") - growth_trajectory: Optional[str] = Field(None, description="成长轨迹") - updated_at: Optional[int] = Field(None, description="更新时间戳（毫秒）") - is_cached: bool = Field(..., description="是否有缓存数据") - message: Optional[str] = Field(None, description="附加消息") - - -# ==================== 用户摘要 ==================== - -class UserSummaryData(BaseModel): - """用户摘要数据""" - user_summary: Optional[str] = Field(None, description="用户摘要") - personality: Optional[str] = Field(None, description="性格特征") - core_values: Optional[str] = Field(None, description="核心价值观") - one_sentence: Optional[str] = Field(None, description="一句话总结") - updated_at: Optional[int] = Field(None, description="更新时间戳（毫秒）") - is_cached: bool = Field(..., description="是否有缓存数据") - message: Optional[str] = Field(None, description="附加消息") - - -# ==================== 缓存生成 ==================== - -class GenerateCacheErrorItem(BaseModel): - """缓存生成错误项""" - type: Optional[str] = Field(None, description="错误类型 (insight/summary)") - error: Optional[str] = Field(None, description="错误信息") - - -class SingleUserCacheResultData(BaseModel): - """单用户缓存生成结果""" - end_user_id: str = Field(..., description="终端用户ID") - insight_success: bool = Field(..., description="洞察生成是否成功") - summary_success: bool = Field(..., description="摘要生成是否成功") - errors: List[GenerateCacheErrorItem] = Field(default_factory=list, description="错误列表") - - -class WorkspaceCacheErrorItem(BaseModel): - """工作空间缓存生成错误项""" - end_user_id: Optional[str] = Field(None, description="终端用户ID") - insight_error: Optional[str] = Field(None, description="洞察生成错误") - summary_error: Optional[str] = Field(None, description="摘要生成错误") - error: Optional[str] = Field(None, description="通用错误信息") - - -class WorkspaceCacheResultData(BaseModel): - """工作空间批量缓存生成结果""" - total_users: int = Field(..., description="总用户数") - successful: int = Field(..., description="成功数") - failed: int = Field(..., description="失败数") - errors: List[WorkspaceCacheErrorItem] = Field(default_factory=list, description="错误列表") - - -# ==================== 节点统计 ==================== - -class MemoryTypeStatItem(BaseModel): - """记忆类型统计项""" - type: str = Field(..., description="记忆类型枚举值") - count: int = Field(..., description="该类型的数量") - percentage: float = Field(..., description="该类型在所有记忆中的占比") - - -# ==================== 图数据 ==================== - -class GraphNodeData(BaseModel): - """图节点数据""" - id: str = Field(..., description="节点ID") - label: str = Field(..., description="节点类型标签") - properties: Dict[str, Any] = Field(default_factory=dict, description="节点属性") - caption: Optional[str] = Field(None, description="节点显示名称") - - -class GraphEdgeData(BaseModel): - """图边数据""" - id: str = Field(..., description="边ID") - source: str = Field(..., description="源节点ID") - target: str = Field(..., description="目标节点ID") - type: Optional[str] = Field(None, description="关系类型") - properties: Dict[str, Any] = Field(default_factory=dict, description="边属性") - caption: Optional[str] = Field(None, description="边显示名称") - - -class GraphStatistics(BaseModel): - """图统计信息""" - total_nodes: int = Field(0, description="节点总数") - total_edges: int = Field(0, description="边总数") - node_types: Dict[str, int] = Field(default_factory=dict, description="各节点类型数量") - edge_types: Dict[str, int] = Field(default_factory=dict, description="各边类型数量") - - -class GraphData(BaseModel): - """图数据响应""" - nodes: List[GraphNodeData] = Field(..., description="节点列表") - edges: List[GraphEdgeData] = Field(..., description="边列表") - statistics: GraphStatistics = Field(..., description="统计信息") - message: Optional[str] = Field(None, description="附加消息") - - -# ==================== 关系演变 ==================== - -class RelationshipEvolutionData(BaseModel): - """关系演变数据""" - emotion: Any = Field(None, description="情绪数据") - interaction: Any = Field(None, description="交互频率数据")