operating-room-monitor-server/app/schemas.py

from __future__ import annotations

from datetime import datetime

from pydantic import BaseModel, ConfigDict, Field


class HealthResponse(BaseModel):
    status: str
    database: str


class SurgeryStartRequest(BaseModel):
    model_config = ConfigDict(
        json_schema_extra={
            "example": {
                "surgery_id": "123456",
                "camera_ids": ["or-cam-01", "or-cam-02"],
                "candidate_consumables": ["纱布", "缝线", "止血钳"],
            }
        }
    )

    surgery_id: str = Field(
        min_length=6,
        max_length=6,
        pattern=r"^\d{6}$",
        description="手术6位号，只允许6位数字。",
    )
    camera_ids: list[str] = Field(
        min_length=1,
        description="本次手术需要接入的摄像头 ID 列表。",
    )
    candidate_consumables: list[str] = Field(
        default_factory=list,
        description=(
            "本次手术可能使用到的耗材子集（可选）。"
            "非空时仅对该清单内名称做自动记账与待确认追问。"
            "缺省或空数组时，使用 consumable_classifier_labels.yaml 中全部类名；"
            "无有效 yaml 则使用分类模型全部类名。"
        ),
    )


class SurgeryEndRequest(BaseModel):
    model_config = ConfigDict(
        json_schema_extra={"example": {"surgery_id": "123456"}}
    )

    surgery_id: str = Field(
        min_length=6,
        max_length=6,
        pattern=r"^\d{6}$",
        description="手术6位号，只允许6位数字。",
    )


class SurgeryApiResponse(BaseModel):
    surgery_id: str = Field(description="手术6位号。")
    status: str = Field(description="接口处理状态。")
    message: str = Field(description="返回说明。")


class SurgeryClientErrorDetail(BaseModel):
    """与 `HTTPException(detail={...})` 对应；最终 JSON 为 `{"detail": {...}}`。"""

    code: str = Field(description="业务错误码，如 RECORDING_CANNOT_START、RECORDING_NOT_STOPPED、RESULT_NOT_READY。")
    message: str = Field(description="人类可读说明。")
    surgery_id: str = Field(description="手术 6 位号。")


class SurgeryClientErrorResponse(BaseModel):
    """FastAPI/Starlette 对 HTTPException 序列化后的常见外形（`detail` 为对象时）。"""

    detail: SurgeryClientErrorDetail


class SurgeryConsumptionDetail(BaseModel):
    """单条消耗明细（HTTP 与 OpenAPI；按事件发生，可能多行）。

    JSON 字段顺序：item_id → item_name → qty → doctor_id → timestamp。
    （可选落盘耗材 TSV 明细列与此一致：item_id、item_name、qty、doctor_id、timestamp。）
    """

    model_config = ConfigDict(
        json_schema_extra={
            "example": {
                "item_id": "HC001",
                "item_name": "纱布",
                "qty": 1,
                "doctor_id": "D1001",
                "timestamp": "2026-04-21T10:30:00+08:00",
            }
        }
    )

    item_id: str = Field(
        description=(
            "业务物品标识：来自 consumable_classifier_labels.yaml 的 label_id；"
            "类名经归一化后匹配，未在 yaml 中配置 label_id 时与模型类名相同。"
        ),
    )
    item_name: str = Field(description="物品名称（分类或确认后的展示名）。")
    qty: int = Field(
        ge=0,
        description="本条记录对应的消耗数量；当前一次识别或一次人工确认仅追加一条明细，因此固定为 1。",
    )
    doctor_id: str = Field(description="医生 ID。")
    timestamp: datetime = Field(description="记录时间（ISO 8601，date-time）。")


class SurgeryConsumptionSummary(BaseModel):
    """按物品汇总：该手术下该物品消耗数量合计（item_id、item_name、total_quantity）。"""

    model_config = ConfigDict(
        json_schema_extra={
            "example": {
                "item_id": "HC001",
                "item_name": "纱布",
                "total_quantity": 3,
            }
        }
    )

    item_id: str = Field(description="物品 ID，与明细中 item_id 一致。")
    item_name: str = Field(description="物品名称，取该物品首条明细中的名称。")
    total_quantity: int = Field(ge=0, description="该物品在本台手术中的消耗数量合计。")


def build_consumption_summary(
    details: list[SurgeryConsumptionDetail],
) -> list[SurgeryConsumptionSummary]:
    """按 item_id 汇总 total_quantity；名称取该物品首条出现时的 item_name。"""
    totals: dict[str, tuple[str, int]] = {}
    for row in details:
        if row.item_id not in totals:
            totals[row.item_id] = (row.item_name, 0)
        name, acc = totals[row.item_id]
        totals[row.item_id] = (name, acc + row.qty)
    return [
        SurgeryConsumptionSummary(
            item_id=iid,
            item_name=name,
            total_quantity=qty,
        )
        for iid, (name, qty) in sorted(totals.items(), key=lambda x: x[0])
    ]


class PendingConfirmationOption(BaseModel):
    label: str
    confidence: float


class SurgeryPendingConfirmationResponse(BaseModel):
    """当前待医生确认的一条低置信度识别。"""

    surgery_id: str
    confirmation_id: str
    prompt_text: str = Field(description="可直接用于展示或无障碍朗读的话术（与 MP3 内容一致）。")
    prompt_audio_mp3_base64: str = Field(
        description=(
            "与 prompt_text 对应的百度 TTS 音频（MP3）的标准 Base64 字符串（无换行）；"
            "客户端解码为二进制后以 audio/mpeg 播放。"
        ),
    )
    options: list[PendingConfirmationOption]
    model_top1_label: str = Field(description="模型原始 Top1 标签（可能不在候选清单内）。")
    model_top1_confidence: float
    created_at: datetime


class SurgeryPendingConfirmationResolveResponse(BaseModel):
    surgery_id: str
    confirmation_id: str
    status: str = Field(description="accepted")
    message: str
    resolved_label: str | None = Field(
        default=None,
        description="解析并确认后的耗材名称；否认全部候选时为 null。",
    )
    rejected: bool = Field(
        default=False,
        description="是否为否认全部候选（不记消耗）。",
    )
    asr_text: str | None = Field(
        default=None,
        description="服务端语音识别得到的文本。",
    )
    audio_object_key: str | None = Field(
        default=None,
        description="MinIO 中原始 WAV 的对象键，用于追溯。",
    )


class SurgeryResultResponse(BaseModel):
    model_config = ConfigDict(
        json_schema_extra={
            "example": {
                "surgery_id": "123456",
                "status": "completed",
                "message": "结果查询成功。",
                "details": [
                    {
                        "item_id": "HC001",
                        "item_name": "纱布",
                        "qty": 1,
                        "doctor_id": "D1001",
                        "timestamp": "2026-04-21T10:30:00+08:00",
                    },
                    {
                        "item_id": "HC001",
                        "item_name": "纱布",
                        "qty": 1,
                        "doctor_id": "D1002",
                        "timestamp": "2026-04-21T11:05:00+08:00",
                    },
                    {
                        "item_id": "HC002",
                        "item_name": "缝线",
                        "qty": 1,
                        "doctor_id": "D1001",
                        "timestamp": "2026-04-21T10:45:00+08:00",
                    },
                ],
                "summary": [
                    {"item_id": "HC001", "item_name": "纱布", "total_quantity": 2},
                    {"item_id": "HC002", "item_name": "缝线", "total_quantity": 1},
                ],
            }
        }
    )

    surgery_id: str = Field(description="手术6位号。")
    status: str = Field(description="结果状态，例如 pending / completed / failed。")
    message: str = Field(description="返回说明。")
    details: list[SurgeryConsumptionDetail] = Field(
        default_factory=list,
        description=(
            "消耗明细（多行）。每行字段顺序：item_id、item_name、qty、doctor_id、timestamp；"
            "同一 item_id 可多次出现。"
        ),
    )
    summary: list[SurgeryConsumptionSummary] = Field(
        default_factory=list,
        description=(
            "按 item_id 汇总的合计表（仅 item_id、item_name、total_quantity），"
            "应与 details 按 item_id 汇总 qty 一致。"
        ),
    )