add training configuration APIs

app/schemas/session.py

@@ -1,5 +1,7 @@
 from pydantic import BaseModel, Field, field_validator
 
+from app.schemas.training_config import PatientConfig
+
 
 class CreateSessionRequest(BaseModel):
     """创建会话入参：选择病例、训练类别、模式和分数类型。"""
@@ -8,6 +10,7 @@ class CreateSessionRequest(BaseModel):
     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)$")
+    patient_config: PatientConfig | None = None
 
     @field_validator("mode")
     @classmethod
@@ -23,6 +26,7 @@ class CreateSessionResponse(BaseModel):
     session_code: str
     status: str
     patient_opening: str
+    patient_config: dict | None = None
 
 
 class ChatRequest(BaseModel):

app/schemas/training_config.py

@@ -0,0 +1,36 @@
+from pydantic import BaseModel
+
+
+class ConfigOption(BaseModel):
+    """训练配置选项：用于前端渲染单个可选项。"""
+
+    value: str
+    label: str
+    description: str | None = None
+
+
+class PatientConfig(BaseModel):
+    """病人初始化配置：控制 AI 病人的就诊场景、年龄段、文化程度和性格。"""
+
+    visit_environment: str = "outpatient"
+    age_group: str = "youth"
+    education_level: str = "higher"
+    personality: str = "calm"
+
+
+class TrainingConfigOptionsResponse(BaseModel):
+    """训练配置响应：返回默认配置和全部可选项。"""
+
+    case_id: int
+    recommended: PatientConfig
+    recommended_labels: dict[str, str]
+    options: dict[str, list[ConfigOption]]
+
+
+class TrainingConfigRecommendedResponse(BaseModel):
+    """推荐训练配置响应：用于训练页进入时初始化默认病人信息。"""
+
+    case_id: int
+    recommended: PatientConfig
+    recommended_labels: dict[str, str]
+    options: dict[str, list[ConfigOption]]