Merge #31 into develop from memory-summary

[feature]开发用户记忆详情的接口 * memory-summary: (69 commits squashed) - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - Merge branch 'memory-summary' of codeup.aliyun.com:redbearai/python/redbear-mem-open into memory-summary - [feature]Develop the relationship graph interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - Merge branch 'memory-summary' of codeup.aliyun.com:redbearai/python/redbear-mem-open into memory-summary - [feature]Develop the end_user/profile interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - [feature]Develop the end_user/profile interface - Merge branch 'memory-summary' of codeup.aliyun.com:redbearai/python/redbear-mem-open into memory-summary - [updated]Base change operation - [refactor]1.Convert timestamp;2.Remove unnecessary code - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - [feature]Develop the end_user/profile interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [feature]Develop the relationship graph interface - [feature]Develop the end_user/profile interface - [updated]Base change operation - [refactor]1.Convert timestamp;2.Remove unnecessary code - Merge branch 'memory-summary' of codeup.aliyun.com:redbearai/python/redbear-mem-open into memory-summary - [check]check_code.py checks the quality of the code - [fix]Fix insecure database connections - [refactor]refactor memory_storage_controller and memory_storage_service - [add]The /total_memory_count interface returns the "name" field. - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - [feature]Develop the end_user/profile interface - [feature]Memory Insights and User Summary Cache Storage Ingestion - [feature]Develop the relationship graph interface - [feature]Develop the end_user/profile interface - [updated]Base change operation - [refactor]1.Convert timestamp;2.Remove unnecessary code - [feature]Memory Insights and User Summary Cache Storage Ingestion - [featrue]Develop a memory classification interface - [feature]Develop the relationship graph interface - [feature]Develop the end_user/profile interface - [updated]Base change operation - [refactor]1.Convert timestamp;2.Remove unnecessary code - [check]check_code.py checks the quality of the code - [fix]Fix insecure database connections - [refactor]refactor memory_storage_controller and memory_storage_service - [add]The /total_memory_count interface returns the "name" field. - Merge branch 'memory-summary' of codeup.aliyun.com:redbearai/python/redbear-mem-open into memory-summary - [refactor]Reconstruct the user's memory location - add uv.lock Signed-off-by: 乐力齐 <accounts_690c7b0af9007d7e338af636@mail.teambition.com> Reviewed-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com> Merged-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com> CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/31
2025-12-23 08:05:06 +00:00
parent b8c13b8085
commit 42e569b8e5
15 changed files with 1948 additions and 318 deletions
--- a/api/app/controllers/user_memory_controllers.py
+++ b/api/app/controllers/user_memory_controllers.py
@@ -0,0 +1,382 @@
+"""
+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
+import datetime
+from sqlalchemy.orm import Session
+from fastapi import APIRouter, Depends
+
+from app.db import get_db
+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.user_memory_service import (
+    UserMemoryService,
+    analytics_node_statistics,
+    analytics_graph_data,
+)
+from app.schemas.response_schema import ApiResponse
+from app.schemas.memory_storage_schema import GenerateCacheRequest
+from app.schemas.end_user_schema import (
+    EndUserProfileResponse,
+    EndUserProfileUpdate,
+)
+from app.models.end_user_model import EndUser
+from app.dependencies import get_current_user
+from app.models.user_model import User
+
+# Get API logger
+api_logger = get_api_logger()
+
+# Initialize service
+user_memory_service = UserMemoryService()
+
+router = APIRouter(
+    prefix="/memory-storage",
+    tags=["User Memory"],
+)
+
+
+@router.get("/analytics/memory_insight/report", response_model=ApiResponse)
+async def get_memory_insight_report_api(
+    end_user_id: str,  # 使用 end_user_id
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+    ) -> dict:
+    """获取缓存的记忆洞察报告"""
+    api_logger.info(f"记忆洞察报告请求: 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)
+        
+        if result["is_cached"]:
+            # 缓存存在，返回缓存数据
+            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=result, msg="查询成功")
+        else:
+            # 缓存不存在，返回提示消息
+            api_logger.info(f"记忆洞察报告缓存不存在: end_user_id={end_user_id}")
+            return success(data=result, msg="查询成功")
+    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))
+
+
+@router.get("/analytics/user_summary", response_model=ApiResponse)
+async def get_user_summary_api(
+    end_user_id: str,  # 使用 end_user_id
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+    ) -> dict:
+    """获取缓存的用户摘要"""
+    api_logger.info(f"用户摘要请求: 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)
+        
+        if result["is_cached"]:
+            # 缓存存在，返回缓存数据
+            api_logger.info(f"成功返回缓存的用户摘要: end_user_id={end_user_id}")
+            return success(data=result, msg="查询成功")
+        else:
+            # 缓存不存在，返回提示消息
+            api_logger.info(f"用户摘要缓存不存在: end_user_id={end_user_id}")
+            return success(data=result, msg="查询成功")
+    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))
+
+
+@router.post("/analytics/generate_cache", response_model=ApiResponse)
+async def generate_cache_api(
+    request: GenerateCacheRequest,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+) -> dict:
+    """
+    手动触发缓存生成
+    
+    - 如果提供 end_user_id，只为该用户生成
+    - 如果不提供，为当前工作空间的所有用户生成
+    """
+    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} 尝试生成缓存但未选择工作空间")
+        return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None")
+    
+    group_id = request.end_user_id
+    
+    api_logger.info(
+        f"缓存生成请求: user={current_user.username}, workspace={workspace_id}, "
+        f"end_user_id={group_id if group_id else '全部用户'}"
+    )
+    
+    try:
+        if group_id:
+            # 为单个用户生成
+            api_logger.info(f"开始为单个用户生成缓存: end_user_id={group_id}")
+            
+            # 生成记忆洞察
+            insight_result = await user_memory_service.generate_and_cache_insight(db, group_id, workspace_id)
+            
+            # 生成用户摘要
+            summary_result = await user_memory_service.generate_and_cache_summary(db, group_id, workspace_id)
+            
+            # 构建响应
+            result = {
+                "end_user_id": group_id,
+                "insight_success": insight_result["success"],
+                "summary_success": summary_result["success"],
+                "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 result["insight_success"] and result["summary_success"]:
+                api_logger.info(f"成功为用户 {group_id} 生成缓存")
+            else:
+                api_logger.warning(f"用户 {group_id} 的缓存生成部分失败: {result['errors']}")
+            
+            return success(data=result, msg="生成完成")
+            
+        else:
+            # 为整个工作空间生成
+            api_logger.info(f"开始为工作空间 {workspace_id} 批量生成缓存")
+            
+            result = await user_memory_service.generate_cache_for_workspace(db, workspace_id)
+            
+            # 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={result['total_users']}, 成功={result['successful']}, 失败={result['failed']}"
+            )
+            
+            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)}")
+        return fail(BizCode.INTERNAL_ERROR, "缓存生成失败", str(e))
+
+
+@router.get("/analytics/node_statistics", response_model=ApiResponse)
+async def get_node_statistics_api(
+    end_user_id: str,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+) -> dict:
+    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} 尝试查询节点统计但未选择工作空间")
+        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"节点统计请求: end_user_id={end_user_id}, user={current_user.username}, workspace={workspace_id}")
+    
+    try:
+        result = await analytics_node_statistics(db, end_user_id)
+        
+        # 检查是否有错误消息
+        if "message" in result and result["total"] == 0:
+            api_logger.warning(f"节点统计查询返回空结果: {result.get('message')}")
+            return success(data=result, msg=result.get("message", "查询成功"))
+        
+        api_logger.info(f"成功获取节点统计: end_user_id={end_user_id}, total={result['total']}")
+        return success(data=result, msg="查询成功")
+    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))
+
+@router.get("/analytics/graph_data", response_model=ApiResponse)
+async def get_graph_data_api(
+    end_user_id: str,
+    node_types: Optional[str] = None,
+    limit: int = 100,
+    depth: int = 1,
+    center_node_id: Optional[str] = None,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+) -> dict:
+    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} 尝试查询图数据但未选择工作空间")
+        return fail(BizCode.INVALID_PARAMETER, "请先切换到一个工作空间", "current_workspace_id is None")
+    
+    # 参数验证
+    if limit > 1000:
+        limit = 1000
+        api_logger.warning("limit 参数超过最大值，已调整为 1000")
+    
+    if depth > 3:
+        depth = 3
+        api_logger.warning("depth 参数超过最大值，已调整为 3")
+    
+    # 解析 node_types 参数
+    node_types_list = None
+    if node_types:
+        node_types_list = [t.strip() for t in node_types.split(",") if t.strip()]
+    
+    api_logger.info(
+        f"图数据查询请求: end_user_id={end_user_id}, user={current_user.username}, "
+        f"workspace={workspace_id}, node_types={node_types_list}, limit={limit}, depth={depth}"
+    )
+    
+    try:
+        result = await analytics_graph_data(
+            db=db,
+            end_user_id=end_user_id,
+            node_types=node_types_list,
+            limit=limit,
+            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')}")
+            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={result['statistics']['total_nodes']}, "
+            f"edges={result['statistics']['total_edges']}"
+        )
+        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)}")
+        return fail(BizCode.INTERNAL_ERROR, "图数据查询失败", str(e))
+
+
+@router.get("/read_end_user/profile", response_model=ApiResponse)
+async def get_end_user_profile(
+    end_user_id: str,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+) -> dict:
+    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} 尝试查询用户信息但未选择工作空间")
+        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"用户信息查询请求: end_user_id={end_user_id}, user={current_user.username}, "
+        f"workspace={workspace_id}"
+    )
+    
+    try:
+        # 查询终端用户
+        end_user = db.query(EndUser).filter(EndUser.id == end_user_id).first()
+        
+        if not end_user:
+            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}")
+        
+        # 构建响应数据
+        profile_data = EndUserProfileResponse(
+            id=end_user.id,
+            name=end_user.name,
+            position=end_user.position,
+            department=end_user.department,
+            contact=end_user.contact,
+            phone=end_user.phone,
+            hire_date=end_user.hire_date,
+            updatetime_profile=end_user.updatetime_profile
+        )
+        
+        api_logger.info(f"成功获取用户信息: end_user_id={end_user_id}")
+        return success(data=profile_data.model_dump(), msg="查询成功")
+        
+    except Exception as e:
+        api_logger.error(f"用户信息查询失败: end_user_id={end_user_id}, error={str(e)}")
+        return fail(BizCode.INTERNAL_ERROR, "用户信息查询失败", str(e))
+
+
+@router.post("/updated_end_user/profile", response_model=ApiResponse)
+async def update_end_user_profile(
+    profile_update: EndUserProfileUpdate,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+) -> dict:
+    """
+    更新终端用户的基本信息
+    
+    该接口可以更新用户的姓名、职位、部门、联系方式、电话和入职日期等信息。
+    所有字段都是可选的，只更新提供的字段。
+    
+    """
+    workspace_id = current_user.current_workspace_id
+    end_user_id = profile_update.end_user_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} 尝试更新用户信息但未选择工作空间")
+        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"用户信息更新请求: end_user_id={end_user_id}, user={current_user.username}, "
+        f"workspace={workspace_id}"
+    )
+    
+    try:
+        # 查询终端用户
+        end_user = db.query(EndUser).filter(EndUser.id == end_user_id).first()
+        
+        if not end_user:
+            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}")
+        
+        # 更新字段（只更新提供的非 None 字段，排除 end_user_id）
+        update_data = profile_update.model_dump(exclude_unset=True, exclude={'end_user_id'})
+        for field, value in update_data.items():
+            if value is not None:
+                setattr(end_user, field, value)
+        
+        # 更新 updated_at 时间戳
+        end_user.updated_at = datetime.datetime.now()
+        
+        # 更新 updatetime_profile 为当前时间戳（毫秒）
+        current_timestamp = int(datetime.datetime.now().timestamp() * 1000)
+        end_user.updatetime_profile = current_timestamp
+        
+        # 提交更改
+        db.commit()
+        db.refresh(end_user)
+        
+        # 构建响应数据
+        profile_data = EndUserProfileResponse(
+            id=end_user.id,
+            name=end_user.name,
+            position=end_user.position,
+            department=end_user.department,
+            contact=end_user.contact,
+            phone=end_user.phone,
+            hire_date=end_user.hire_date,
+            updatetime_profile=end_user.updatetime_profile
+        )
+        
+        api_logger.info(f"成功更新用户信息: end_user_id={end_user_id}, updated_fields={list(update_data.keys())}, updatetime_profile={current_timestamp}")
+        return success(data=profile_data.model_dump(), msg="更新成功")
+        
+    except Exception as e:
+        db.rollback()
+        api_logger.error(f"用户信息更新失败: end_user_id={end_user_id}, error={str(e)}")
+        return fail(BizCode.INTERNAL_ERROR, "用户信息更新失败", str(e))