feat: 报销审批流重构与管家计划全链路贯通

- 重构报销状态注册表、审批流路由与平台风险标记
- 完善管家意图规划器与模型计划构建器全链路
- 新增 OCR Worker 脚本、数据库会话管理与通知状态
- 优化文档中心、日志视图、预算中心与员工管理交互
- 增强工作台摘要、图标资源与全局主题样式
- 补充审批路由、状态注册、OCR 服务与管家规划器测试覆盖

server/src/app/schemas/steward.py

@@ -8,6 +8,18 @@ from pydantic import BaseModel, Field
 StewardTaskType = Literal["expense_application", "reimbursement"]
 StewardAssignedAgent = Literal["application_assistant", "reimbursement_assistant"]
 StewardPlanningSource = Literal["llm_function_call", "rule_fallback"]
+StewardSlotDecisionSource = Literal["llm_function_call", "rule_fallback"]
+StewardSlotNextAction = Literal["ask_user", "render_preview"]
+StewardRuntimeDecisionSource = Literal["llm_function_call", "rule_fallback"]
+StewardRuntimeNextAction = Literal[
+    "plan_new_tasks",
+    "submit_current_application",
+    "continue_next_task",
+    "fill_current_slot",
+    "ask_user",
+    "cancel_current_action",
+    "no_op",
+]
 StewardTaskStatus = Literal[
     "planned",
     "needs_confirmation",
@@ -88,3 +100,50 @@ class StewardPlanResponse(BaseModel):
     attachment_groups: list[StewardAttachmentGroup] = Field(default_factory=list, description="附件归集建议。")
     confirmation_groups: list[StewardConfirmationAction] = Field(default_factory=list, description="等待用户确认的动作。")
     model_call_traces: list[dict[str, Any]] = Field(default_factory=list, description="模型工具调用轨迹。")
+
+
+class StewardSlotOption(BaseModel):
+    label: str = Field(description="用户可见选项文案。")
+    value: str = Field(description="写回本体字段的选项值。")
+    field_key: str = Field(description="对应 canonical ontology field。")
+    description: str = Field(default="", description="选项说明。")
+
+
+class StewardSlotDecisionRequest(BaseModel):
+    task_type: StewardTaskType = Field(description="当前小财管家正在推进的任务类型。")
+    user_message: str = Field(description="用户原始话术或小财管家携带的任务上下文。")
+    ontology_fields: dict[str, str] = Field(default_factory=dict, description="当前已抽取的 canonical ontology 字段。")
+    missing_fields: list[str] = Field(default_factory=list, description="上游意图识别给出的 canonical 缺失字段。")
+    task_context: dict[str, Any] = Field(default_factory=dict, description="当前任务、附件、申请预览等上下文。")
+
+
+class StewardSlotDecisionResponse(BaseModel):
+    decision_source: StewardSlotDecisionSource = Field(default="rule_fallback", description="字段决策来源。")
+    next_action: StewardSlotNextAction = Field(description="下一步应追问用户还是展示核对结果。")
+    required_fields: list[str] = Field(default_factory=list, description="模型认为当前业务需要的 canonical 字段。")
+    missing_fields: list[str] = Field(default_factory=list, description="当前仍缺失的 canonical 字段。")
+    question: str = Field(default="", description="需要追问时展示给用户的问题。")
+    options: list[StewardSlotOption] = Field(default_factory=list, description="可直接选择的补充选项。")
+    rationale: str = Field(default="", description="面向用户的简短判断依据，不暴露推理链。")
+    model_call_traces: list[dict[str, Any]] = Field(default_factory=list, description="模型工具调用轨迹。")
+
+
+class StewardRuntimeDecisionRequest(BaseModel):
+    user_message: str = Field(description="用户当前输入。")
+    session_type: str = Field(default="steward", description="当前前端会话类型。")
+    runtime_state: dict[str, Any] = Field(default_factory=dict, description="小财管家运行时上下文。")
+    context_json: dict[str, Any] = Field(default_factory=dict, description="调用方补充上下文。")
+
+
+class StewardRuntimeDecisionResponse(BaseModel):
+    decision_source: StewardRuntimeDecisionSource = Field(default="rule_fallback", description="运行时决策来源。")
+    next_action: StewardRuntimeNextAction = Field(description="小财管家下一步动作。")
+    target_task_id: str = Field(default="", description="关联的小财管家任务 ID。")
+    target_message_id: str = Field(default="", description="关联的前端消息 ID。")
+    field_key: str = Field(default="", description="补字段时对应 canonical ontology field。")
+    field_value: str = Field(default="", description="补字段时用户提供的字段值。")
+    confirmation_required: bool = Field(default=False, description="执行该动作前是否仍需要用户二次确认。")
+    question: str = Field(default="", description="需要追问用户时展示的问题。")
+    response_text: str = Field(default="", description="无需调用工具时给用户的简短回复。")
+    rationale: str = Field(default="", description="面向用户的简短判断依据，不暴露推理链。")
+    model_call_traces: list[dict[str, Any]] = Field(default_factory=list, description="模型工具调用轨迹。")