schemas/user_input.py

"""
用户输入数据模型定义
使用Pydantic进行数据验证
"""

from pydantic import BaseModel, Field
from typing import Optional, List
from enum import Enum

class RiskLevel(str, Enum):
    """风险等级枚举"""
    LOW = "low"
    MEDIUM = "medium" 
    HIGH = "high"

class ModelType(str, Enum):
    """模型类型枚举"""
    SARCO_I = "sarcoI"
    SARCO_II = "sarcoII"

class UserInput(BaseModel):
    """用户输入数据模型"""
    
    # 基本信息 (注意：本系统适用于18-55岁成年人群)
    age_years: float = Field(..., ge=16, le=120, description="年龄(岁) - 推荐18-55岁")
    race_ethnicity: int = Field(..., ge=0, le=4, description="种族/民族编码(0-4)")
    
    # 身体指标  
    body_mass_index: float = Field(..., ge=10, le=80, description="体质量指数BMI")
    WWI: float = Field(..., ge=3, le=50, description="腰围重量指数")
    
    # NHANES PAQ 原始问卷数据
    # 工作相关活动
    PAQ605: int = Field(..., ge=1, le=2, description="工作高强度活动(1=是,2=否)")
    PAQ610: Optional[int] = Field(0, ge=0, le=7, description="工作高强度活动天数/周")
    PAD615: Optional[float] = Field(0, ge=0, le=1440, description="工作高强度活动分钟数/天")
    PAQ620: int = Field(..., ge=1, le=2, description="工作中等强度活动(1=是,2=否)")
    PAQ625: Optional[int] = Field(0, ge=0, le=7, description="工作中等强度活动天数/周")
    PAD630: Optional[float] = Field(0, ge=0, le=1440, description="工作中等强度活动分钟数/天")
    
    # 交通相关活动
    PAQ635: int = Field(..., ge=1, le=2, description="步行/骑车通勤(1=是,2=否)")
    PAQ640: Optional[int] = Field(0, ge=0, le=7, description="步行/骑车通勤天数/周")
    PAD645: Optional[float] = Field(0, ge=0, le=1440, description="步行/骑车通勤分钟数/天")
    
    # 休闲运动活动
    PAQ650: int = Field(..., ge=1, le=2, description="休闲高强度活动(1=是,2=否)")
    PAQ655: Optional[int] = Field(0, ge=0, le=7, description="休闲高强度活动天数/周")
    PAD660: Optional[float] = Field(0, ge=0, le=1440, description="休闲高强度活动分钟数/天")
    PAQ665: int = Field(..., ge=1, le=2, description="休闲中等强度活动(1=是,2=否)")
    PAQ670: Optional[int] = Field(0, ge=0, le=7, description="休闲中等强度活动天数/周")
    PAD675: Optional[float] = Field(0, ge=0, le=1440, description="休闲中等强度活动分钟数/天")
    
    # 久坐行为
    PAD680: float = Field(..., ge=0, le=1440, description="每日久坐时间(分钟)")
    
    # 医疗史 (筛查模型必需)
    arthritis: Optional[int] = Field(0, ge=0, le=1, description="关节炎史(0=无,1=有)")
    diabetes: Optional[int] = Field(0, ge=0, le=1, description="糖尿病史(0=无,1=有)")
    
    # 计算得出的衍生特征 (前端计算后传入)
    Activity_Sedentary_Ratio: Optional[float] = Field(None, ge=0, le=100, description="久坐活动比例")
    Total_Moderate_Minutes_week: Optional[float] = Field(None, ge=0, le=10080, description="每周中等强度运动时间(分钟)")
    Total_Moderate_Equivalent_Minutes: Optional[float] = Field(None, ge=0, le=10080, description="每周中等强度等效运动时间(分钟)")
    Avg_Vigorous_Duration_Per_Bout: Optional[float] = Field(None, ge=0, le=1440, description="平均高强度运动时长每次(分钟)")
    Vigorous_MET_Ratio: Optional[float] = Field(None, ge=0, le=10, description="高强度运动比例")
    Activity_Diversity_Index: Optional[float] = Field(None, ge=0, le=5, description="活动多样性指数(0-5)")
    sedentary_minutes: Optional[float] = Field(None, ge=0, le=1440, description="每日久坐时间(分钟,同PAD680)")

    class Config:
        json_schema_extra = {
            "example": {
                "age_years": 45,
                "race_ethnicity": 2,
                "body_mass_index": 28.5,
                "WWI": 11.2,
                "PAQ605": 2,
                "PAQ620": 1,
                "PAQ625": 3,
                "PAD630": 60,
                "PAQ635": 1,
                "PAQ640": 5,
                "PAD645": 30,
                "PAQ650": 1,
                "PAQ655": 2,
                "PAD660": 45,
                "PAQ665": 1,
                "PAQ670": 3,
                "PAD675": 60,
                "PAD680": 480,
                "arthritis": 0,
                "diabetes": 0,
                "Activity_Sedentary_Ratio": 0.6,
                "Total_Moderate_Minutes_week": 150,
                "Total_Moderate_Equivalent_Minutes": 150,
                "Avg_Vigorous_Duration_Per_Bout": 30,
                "Vigorous_MET_Ratio": 0.3,
                "Activity_Diversity_Index": 3,
                "sedentary_minutes": 480
            }
        }

class ScreeningRequest(BaseModel):
    """筛查请求模型"""
    user_data: UserInput
    models: List[ModelType] = [ModelType.SARCO_I, ModelType.SARCO_II]

class AdvisoryRequest(BaseModel):
    """建议请求模型"""
    user_data: UserInput
    risk_types: List[ModelType] = []
    num_recommendations: int = Field(default=3, ge=1, le=5, description="建议数量")
    language: str = Field(default="zh", description="语言设置 (zh/en)")

class ScreeningResponse(BaseModel):
    """筛查响应模型"""
    # 筛查模型结果 (高召回率)
    sarcoI_risk: RiskLevel
    sarcoI_probability: float
    sarcoI_threshold: float
    sarcoII_risk: RiskLevel
    sarcoII_probability: float
    sarcoII_threshold: float

    # 建议模型结果 (高精确率)
    sarcoI_advisory_risk: Optional[RiskLevel] = None
    sarcoI_advisory_probability: Optional[float] = None
    sarcoI_advisory_threshold: Optional[float] = None
    sarcoII_advisory_risk: Optional[RiskLevel] = None
    sarcoII_advisory_probability: Optional[float] = None
    sarcoII_advisory_threshold: Optional[float] = None

    # 综合结果
    overall_risk: RiskLevel
    confidence: float
    processing_time: float

class RecommendationItem(BaseModel):
    """单个建议项"""
    title: str
    description: str
    priority: str
    target_change: Optional[str] = None
    expected_impact: Optional[str] = None

class AdvisoryResponse(BaseModel):
    """建议响应模型"""
    sarcoI_recommendations: List[RecommendationItem]
    sarcoII_recommendations: List[RecommendationItem]
    recommendations: Optional[List[RecommendationItem]] = None  # 合并的建议列表，用于前端显示
    priority_actions: List[str]
    target_metrics: dict
    processing_time: float
    success: bool
    fallback_used: bool = False

class ErrorResponse(BaseModel):
    """错误响应模型"""
    error: str
    detail: str
    timestamp: str