新增中翻英功能（记忆时间线）(用户摘要)(兴趣分布接口)(查询核心档案)(记忆洞察)

api/app/controllers/user_memory_controllers.py

@@ -12,6 +12,7 @@ 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.memory_base_service import Translation_English
 from app.services.user_memory_service import (
     UserMemoryService,
     analytics_memory_types,
@@ -20,7 +21,7 @@ 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.repositories.workspace_repository import WorkspaceRepository
 from app.schemas.end_user_schema import (
     EndUserProfileResponse,
     EndUserProfileUpdate,
@@ -44,6 +45,7 @@ router = APIRouter(
 @router.get("/analytics/memory_insight/report", response_model=ApiResponse)
 async def get_memory_insight_report_api(
     end_user_id: str,
+    language_type: str = "zh",
     current_user: User = Depends(get_current_user),
     db: Session = Depends(get_db),
 ) -> dict:
@@ -53,10 +55,18 @@ async def get_memory_insight_report_api(
     此接口仅查询数据库中已缓存的记忆洞察数据，不执行生成操作。
     如需生成新的洞察报告，请使用专门的生成接口。
     """
+    workspace_id = current_user.current_workspace_id
+    workspace_repo = WorkspaceRepository(db)
+    workspace_models = workspace_repo.get_workspace_models_configs(workspace_id)
+
+    if workspace_models:
+        model_id = workspace_models.get("llm", None)
+    else:
+        model_id = None
     api_logger.info(f"记忆洞察报告查询请求: end_user_id={end_user_id}, user={current_user.username}")
     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)
+        result = await user_memory_service.get_cached_memory_insight(db, end_user_id,model_id,language_type)
 
         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}")
@@ -72,6 +82,7 @@ async def get_memory_insight_report_api(
 @router.get("/analytics/user_summary", response_model=ApiResponse)
 async def get_user_summary_api(
     end_user_id: str,
+    language_type: str="zh",
     current_user: User = Depends(get_current_user),
     db: Session = Depends(get_db),
 ) -> dict:
@@ -81,10 +92,18 @@ async def get_user_summary_api(
     此接口仅查询数据库中已缓存的用户摘要数据，不执行生成操作。
     如需生成新的用户摘要，请使用专门的生成接口。
     """
+    workspace_id = current_user.current_workspace_id
+    workspace_repo = WorkspaceRepository(db)
+    workspace_models = workspace_repo.get_workspace_models_configs(workspace_id)
+
+    if workspace_models:
+        model_id = workspace_models.get("llm", None)
+    else:
+        model_id = None
     api_logger.info(f"用户摘要查询请求: end_user_id={end_user_id}, user={current_user.username}")
     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)
+        result = await user_memory_service.get_cached_user_summary(db, end_user_id,model_id,language_type)
 
         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}")
@@ -253,7 +272,6 @@ async def get_graph_data_api(
             depth=depth,
             center_node_id=center_node_id
         )
-
         # 检查是否有错误消息
         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')}")
@@ -274,11 +292,18 @@ async def get_graph_data_api(
 @router.get("/read_end_user/profile", response_model=ApiResponse)
 async def get_end_user_profile(
     end_user_id: str,
+    language_type: str = "zh",
     current_user: User = Depends(get_current_user),
     db: Session = Depends(get_db),
 ) -> dict:
     workspace_id = current_user.current_workspace_id
+    workspace_repo = WorkspaceRepository(db)
+    workspace_models = workspace_repo.get_workspace_models_configs(workspace_id)
 
+    if workspace_models:
+        model_id = workspace_models.get("llm", None)
+    else:
+        model_id = None
     # 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} 尝试查询用户信息但未选择工作空间")
@@ -297,12 +322,19 @@ async def get_end_user_profile(
             api_logger.warning(f"终端用户不存在: end_user_id={end_user_id}")
             return fail(BizCode.INVALID_PARAMETER, "终端用户不存在", f"end_user_id={end_user_id}")
 
+        other_name=end_user.other_name
+        position=end_user.position
+        department=end_user.department
+        if language_type!="zh":
+            other_name=await Translation_English(model_id,other_name)
+            position = await Translation_English(model_id, position)
+            department = await Translation_English(model_id, department)
         # 构建响应数据
         profile_data = EndUserProfileResponse(
             id=end_user.id,
-            other_name=end_user.other_name,
-            position=end_user.position,
-            department=end_user.department,
+            other_name=other_name,
+            position=position,
+            department=department,
             contact=end_user.contact,
             phone=end_user.phone,
             hire_date=end_user.hire_date,
@@ -396,12 +428,21 @@ async def update_end_user_profile(
         return fail(BizCode.INTERNAL_ERROR, "用户信息更新失败", str(e))
 
 @router.get("/memory_space/timeline_memories", response_model=ApiResponse)
-async def memory_space_timeline_of_shared_memories(id: str, label: str,
+async def memory_space_timeline_of_shared_memories(id: str, label: str,language_type: str,
                                       current_user: User = Depends(get_current_user),
                                       db: Session = Depends(get_db),
                                       ):
+    workspace_id=current_user.current_workspace_id
+    workspace_repo = WorkspaceRepository(db)
+    workspace_models = workspace_repo.get_workspace_models_configs(workspace_id)
+
+    if workspace_models:
+        model_id = workspace_models.get("llm", None)
+    else:
+        model_id = None
     MemoryEntity = MemoryEntityService(id, label)
-    timeline_memories_result = await MemoryEntity.get_timeline_memories_server()
+    timeline_memories_result = await MemoryEntity.get_timeline_memories_server(model_id, language_type)
+
     return success(data=timeline_memories_result, msg="共同记忆时间线")
 @router.get("/memory_space/relationship_evolution", response_model=ApiResponse)
 async def memory_space_relationship_evolution(id: str, label: str,