feat: 新增员工行为画像算法与费用风险标签体系

后端新增员工行为画像算法模块，支持标签规则引擎和评分计算，
完善员工模型、银行信息、序列化和导入逻辑，优化报销审批流
和工作流常量，增强 Hermes 同步和知识同步能力，前端新增费
用画像详情弹窗、雷达图和风险卡片组件，完善登录页和工作台
样式，优化文档中心和归档中心交互，补充单元测试。

server/src/app/schemas/employee.py

@@ -78,6 +78,9 @@ class EmployeeRead(BaseModel):
     joinDate: str | None = None
     location: str | None = None
     costCenter: str | None = None
+    bankName: str | None = None
+    bankAccountNo: str | None = None
+    bankAccountName: str | None = None
     updatedAt: str | None = None
     lastSync: str | None = None
     syncState: str
@@ -100,6 +103,9 @@ class EmployeeCreate(BaseModel):
     grade: str = Field(default="P3", max_length=20)
     cost_center: str | None = Field(default=None, max_length=50)
     finance_owner_name: str | None = Field(default=None, max_length=100)
+    bank_name: str | None = Field(default=None, max_length=120)
+    bank_account_no: str | None = Field(default=None, max_length=80)
+    bank_account_name: str | None = Field(default=None, max_length=100)
     employment_status: str = Field(default="在职", max_length=30)
     sync_state: str = Field(default="已同步", max_length=30)
     spotlight: bool = False
@@ -148,6 +154,9 @@ class EmployeeUpdate(BaseModel):
     grade: str | None = Field(default=None, min_length=1, max_length=20)
     cost_center: str | None = Field(default=None, max_length=50)
     finance_owner_name: str | None = Field(default=None, max_length=100)
+    bank_name: str | None = Field(default=None, max_length=120)
+    bank_account_no: str | None = Field(default=None, max_length=80)
+    bank_account_name: str | None = Field(default=None, max_length=100)
     organization_unit_code: str | None = Field(default=None, max_length=50)
     manager_employee_no: str | None = Field(default=None, max_length=50)
     role_codes: list[str] | None = None

server/src/app/schemas/employee_profile.py

@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+from datetime import datetime
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+
+class EmployeeProfilePeerGroupRead(BaseModel):
+    key: str = ""
+    fallback_level: int = 0
+    sample_size: int = 0
+
+
+class EmployeeProfileRead(BaseModel):
+    profile_type: str
+    profile_label: str
+    score: int
+    level: str
+    level_label: str
+    metrics: dict[str, Any] = Field(default_factory=dict)
+    top_contributors: list[dict[str, Any]] = Field(default_factory=list)
+
+
+class EmployeeProfileTagRead(BaseModel):
+    code: str
+    label: str
+    display_label: str
+    category: str
+    polarity: str = "behavior"
+    score: int
+    confidence: float
+    reason: str = ""
+    evidence: list[dict[str, Any]] = Field(default_factory=list)
+    radar_dimensions: list[str] = Field(default_factory=list)
+    algorithm_version: str = ""
+
+
+class EmployeeProfileRadarDimensionRead(BaseModel):
+    code: str
+    label: str
+    score: int
+    level: str
+    level_label: str
+    top_tags: list[str] = Field(default_factory=list)
+
+
+class EmployeeProfileRadarRead(BaseModel):
+    algorithm_version: str = ""
+    dimensions: list[EmployeeProfileRadarDimensionRead] = Field(default_factory=list)
+
+
+class EmployeeProfileLatestRead(BaseModel):
+    employee_id: str
+    employee_name: str = ""
+    scene: str = "approval"
+    window_days: int = 90
+    expense_type_scope: str = "overall"
+    calculated_at: datetime | None = None
+    peer_group: EmployeeProfilePeerGroupRead = Field(default_factory=EmployeeProfilePeerGroupRead)
+    review_priority_score: int = 0
+    review_priority_level: str = "normal"
+    review_priority_label: str = "正常"
+    profiles: list[EmployeeProfileRead] = Field(default_factory=list)
+    profile_tags: list[EmployeeProfileTagRead] = Field(default_factory=list)
+    radar: EmployeeProfileRadarRead = Field(default_factory=EmployeeProfileRadarRead)
+    review_suggestions: list[dict[str, Any]] = Field(default_factory=list)
+    empty_reason: str = ""