prepare fastapi root layout for server deployment

app/schemas/session.py

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+from pydantic import BaseModel, Field, field_validator
+
+
+class CreateSessionRequest(BaseModel):
+    """创建会话入参：选择病例、训练类别、模式和分数类型。"""
+
+    case_id: int
+    training_type: str = Field(pattern="^(case_analysis|diagnosis_treatment|consultation)$")
+    mode: str = Field(pattern="^(novice|practice|teaching)$")
+    score_type: str = Field(default="percentage", pattern="^(percentage|five_point)$")
+
+    @field_validator("mode")
+    @classmethod
+    def normalize_mode(cls, value: str) -> str:
+        """训练模式：兼容旧 novice 请求，实际按 practice 练习模式处理。"""
+        return "practice" if value == "novice" else value
+
+
+class CreateSessionResponse(BaseModel):
+    """创建会话响应：返回会话标识和 AI 病人开场白。"""
+
+    session_id: int
+    session_code: str
+    status: str
+    patient_opening: str
+
+
+class ChatRequest(BaseModel):
+    """问诊消息入参：医生向 AI 病人发送的自然语言问题。"""
+
+    message: str = Field(min_length=1, max_length=2000)
+
+
+class ChatResponse(BaseModel):
+    """问诊消息响应：返回 AI 病人的非流式回复。"""
+
+    reply: str
+    latency_ms: int
+    model: str
+    fallback_used: bool = False
+
+
+class OrderItemResponse(BaseModel):
+    """可申请检查项：只返回名称和类型，不返回结果。"""
+
+    item_code: str
+    item_name: str
+    item_type: str
+
+
+class OrderItemsResponse(BaseModel):
+    """可申请检查项列表响应。"""
+
+    items: list[OrderItemResponse]
+
+
+class CreateOrderRequest(BaseModel):
+    """检查申请入参：指定当前病例下的检查项目编码。"""
+
+    item_code: str = Field(min_length=1, max_length=64)
+
+
+class CreateOrderResponse(BaseModel):
+    """检查申请响应：返回数据库预设的结构化检查结果。"""
+
+    item_code: str
+    item_name: str
+    item_type: str
+    result_text: str
+    result_structured: dict | None = None
+    is_key: bool
+    is_abnormal: bool
+    context_written: bool = True
+    already_ordered: bool = False
+
+
+class SessionStatusResponse(BaseModel):
+    """会话状态响应：用于阶段流转接口。"""
+
+    session_id: int
+    status: str
+
+
+class SubmitDiagnosisRequest(BaseModel):
+    """诊断提交入参：保存主要诊断、鉴别诊断和诊断依据。"""
+
+    primary_diagnosis: str = Field(min_length=1, max_length=2000)
+    differential_diagnoses: list[str] = Field(default_factory=list)
+    diagnosis_basis: str = Field(min_length=1, max_length=5000)
+
+
+class SubmitDiagnosisResponse(BaseModel):
+    """诊断提交响应：进入治疗阶段。"""
+
+    status: str
+
+
+class SubmitTreatmentRequest(BaseModel):
+    """治疗方案入参：保存治疗原则、措施、风险预案、沟通和随访。"""
+
+    treatment_principle: str = Field(min_length=1, max_length=3000)
+    treatment_measures: str = Field(min_length=1, max_length=5000)
+    risk_plan: str | None = Field(default=None, max_length=3000)
+    communication: str | None = Field(default=None, max_length=3000)
+    follow_up: str | None = Field(default=None, max_length=3000)
+
+
+class SubmitTreatmentResponse(BaseModel):
+    """治疗提交响应：进入评价阶段。"""
+
+    status: str
+
+
+class HintRequest(BaseModel):
+    """会话提示入参：基于当前会话上下文生成新手模式提醒。"""
+
+    last_user_message: str | None = Field(default=None, max_length=2000)
+    scope: str = Field(default="current_conversation", pattern="^current_conversation$")
+
+
+class HintResponse(BaseModel):
+    """会话提示响应：返回缺失维度、下一步问题和轻量训练提示。"""
+
+    hints: list[str]
+    missing_dimensions: list[str]
+    next_questions: list[str]
+    recommended_orders: list[dict] = Field(default_factory=list)