refactor(memory): replace raw dict responses with Pydantic schema models in user memory controllers

- Add user_memory_schema.py with typed Pydantic models for all user memory
  API responses: MemoryInsightReportData, UserSummaryData, GraphData,
  MemoryTypeStatItem, cache result models, and RelationshipEvolutionData
- Refactor user_memory_controllers.py to construct schema instances and
  return model_dump() instead of raw dicts
- Remove unused imports (datetime, timestamp_to_datetime, EndUserInfoResponse,
  EndUserInfoCreate, EndUser)

api/app/schemas/user_memory_schema.py

@@ -0,0 +1,118 @@
+"""
+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: Optional[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")