# -*- coding: utf-8 -*-
"""
响应数据模型
定义 API 响应的数据结构
"""

from typing import Any, Dict, List, Optional

from pydantic import BaseModel, Field


class ErrorDetail(BaseModel):
    """错误详情"""

    code: str = Field(..., description="错误代码")
    message: str = Field(..., description="错误信息")
    details: Optional[Dict[str, Any]] = Field(
        default=None,
        description="额外的错误详情",
    )


class TextBlockData(BaseModel):
    """文本块数据"""

    text: str = Field(..., description="识别出的文本内容")
    confidence: float = Field(..., description="置信度 (0.0 ~ 1.0)")
    bbox: List[List[float]] = Field(
        ...,
        description="边界框 4 个顶点坐标 [[x1,y1], [x2,y2], [x3,y3], [x4,y4]]",
    )
    bbox_with_offset: List[List[float]] = Field(
        ...,
        description="带偏移的边界框坐标 (已还原到原图坐标系)",
    )
    center: List[float] = Field(..., description="文本块中心点坐标 [x, y]")
    width: float = Field(..., description="文本块宽度 (像素)")
    height: float = Field(..., description="文本块高度 (像素)")


class OCRResultData(BaseModel):
    """OCR 识别结果数据"""

    processing_time_ms: float = Field(..., description="处理耗时 (毫秒)")
    text_count: int = Field(..., description="识别出的文本块数量")
    average_confidence: float = Field(
        ...,
        description="所有文本块的平均置信度",
    )
    roi_applied: bool = Field(..., description="是否应用了 ROI 裁剪")
    roi_rect: Optional[List[int]] = Field(
        default=None,
        description="ROI 矩形区域 [x, y, width, height]",
    )
    text_blocks: List[TextBlockData] = Field(
        default_factory=list,
        description="识别出的文本块列表",
    )
    annotated_image_base64: Optional[str] = Field(
        default=None,
        description="标注后的图片 (Base64 编码)",
    )


class OCRResponse(BaseModel):
    """OCR 识别响应"""

    success: bool = Field(..., description="请求是否成功")
    data: Optional[OCRResultData] = Field(
        default=None,
        description="识别结果数据",
    )
    error: Optional[ErrorDetail] = Field(
        default=None,
        description="错误信息 (仅在失败时存在)",
    )


class ExpressPersonData(BaseModel):
    """快递单人员信息"""

    name: Optional[str] = Field(default=None, description="姓名")
    phone: Optional[str] = Field(default=None, description="电话")
    address: Optional[str] = Field(default=None, description="地址")


class ExpressInfoData(BaseModel):
    """快递单结构化信息"""

    tracking_number: Optional[str] = Field(default=None, description="运单号")
    sender: ExpressPersonData = Field(
        default_factory=ExpressPersonData,
        description="寄件人信息",
    )
    receiver: ExpressPersonData = Field(
        default_factory=ExpressPersonData,
        description="收件人信息",
    )
    courier_company: Optional[str] = Field(
        default=None,
        description="快递公司名称",
    )
    confidence: float = Field(default=0.0, description="平均置信度")
    extra_fields: Dict[str, str] = Field(
        default_factory=dict,
        description="其他识别到的额外字段",
    )
    raw_text: str = Field(default="", description="原始合并文本")


class ExpressResultData(BaseModel):
    """快递单解析结果数据"""

    processing_time_ms: float = Field(..., description="处理耗时 (毫秒)")
    express_info: ExpressInfoData = Field(..., description="快递单结构化信息")
    merged_text: str = Field(..., description="智能合并后的完整文本")
    annotated_image_base64: Optional[str] = Field(
        default=None,
        description="标注后的图片 (Base64 编码)",
    )


class ExpressResponse(BaseModel):
    """快递单解析响应"""

    success: bool = Field(..., description="请求是否成功")
    data: Optional[ExpressResultData] = Field(
        default=None,
        description="解析结果数据",
    )
    error: Optional[ErrorDetail] = Field(
        default=None,
        description="错误信息 (仅在失败时存在)",
    )


class HealthResponse(BaseModel):
    """健康检查响应"""

    status: str = Field(..., description="服务状态: 'healthy' 或 'unhealthy'")
    model_loaded: bool = Field(..., description="OCR 模型是否已加载")
    version: str = Field(..., description="API 版本")