557fcee803
- Refine effective candidate consumables and classifier labels - Adjust vision algorithm, TSV logging, and video session wiring - Refresh client surgery HTTP contract doc and staging/video docs - Update settings, docker-compose prod, tests, and uv.lock Made-with: Cursor
251 lines
8.6 KiB
Python
251 lines
8.6 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from pydantic import BaseModel, ConfigDict, Field
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class HealthResponse(BaseModel):
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status: str
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database: str
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class SurgeryStartRequest(BaseModel):
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model_config = ConfigDict(
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json_schema_extra={
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"example": {
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"surgery_id": "123456",
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"camera_ids": ["or-cam-01", "or-cam-02"],
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"candidate_consumables": ["纱布", "缝线", "止血钳"],
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}
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}
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)
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surgery_id: str = Field(
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min_length=6,
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max_length=6,
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pattern=r"^\d{6}$",
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description="手术6位号，只允许6位数字。",
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)
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camera_ids: list[str] = Field(
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min_length=1,
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description="本次手术需要接入的摄像头 ID 列表。",
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)
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candidate_consumables: list[str] = Field(
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default_factory=list,
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description=(
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"本次手术可能使用到的耗材子集（可选）。"
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"非空时仅对该清单内名称做自动记账与待确认追问。"
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"缺省或空数组时，使用 consumable_classifier_labels.yaml 中全部类名；"
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"无有效 yaml 则使用分类模型全部类名。"
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),
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)
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class SurgeryEndRequest(BaseModel):
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model_config = ConfigDict(
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json_schema_extra={"example": {"surgery_id": "123456"}}
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)
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surgery_id: str = Field(
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min_length=6,
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max_length=6,
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pattern=r"^\d{6}$",
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description="手术6位号，只允许6位数字。",
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)
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class SurgeryApiResponse(BaseModel):
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surgery_id: str = Field(description="手术6位号。")
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status: str = Field(description="接口处理状态。")
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message: str = Field(description="返回说明。")
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class SurgeryClientErrorDetail(BaseModel):
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"""与 `HTTPException(detail={...})` 对应；最终 JSON 为 `{"detail": {...}}`。"""
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code: str = Field(description="业务错误码，如 RECORDING_CANNOT_START、RECORDING_NOT_STOPPED、RESULT_NOT_READY。")
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message: str = Field(description="人类可读说明。")
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surgery_id: str = Field(description="手术 6 位号。")
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class SurgeryClientErrorResponse(BaseModel):
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"""FastAPI/Starlette 对 HTTPException 序列化后的常见外形（`detail` 为对象时）。"""
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detail: SurgeryClientErrorDetail
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class SurgeryConsumptionDetail(BaseModel):
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"""单条消耗明细（HTTP 与 OpenAPI；按事件发生，可能多行）。
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JSON 字段顺序：item_id → item_name → qty → doctor_id → timestamp。
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（可选落盘耗材 TSV 明细列与此一致：item_id、item_name、qty、doctor_id、timestamp。）
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"""
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model_config = ConfigDict(
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json_schema_extra={
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"example": {
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"item_id": "HC001",
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"item_name": "纱布",
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"qty": 1,
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"doctor_id": "D1001",
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"timestamp": "2026-04-21T10:30:00+08:00",
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}
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}
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)
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item_id: str = Field(
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description=(
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"业务物品标识：来自 consumable_classifier_labels.yaml 的 label_id；"
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"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。"
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),
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)
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item_name: str = Field(description="物品名称（分类或确认后的展示名）。")
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qty: int = Field(
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ge=0,
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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。",
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)
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doctor_id: str = Field(description="医生 ID。")
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timestamp: datetime = Field(description="记录时间（ISO 8601，date-time）。")
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class SurgeryConsumptionSummary(BaseModel):
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"""按物品汇总：该手术下该物品消耗数量合计（item_id、item_name、total_quantity）。"""
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model_config = ConfigDict(
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json_schema_extra={
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"example": {
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"item_id": "HC001",
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"item_name": "纱布",
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"total_quantity": 3,
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}
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}
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)
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item_id: str = Field(description="物品 ID，与明细中 item_id 一致。")
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item_name: str = Field(description="物品名称，取该物品首条明细中的名称。")
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total_quantity: int = Field(ge=0, description="该物品在本台手术中的消耗数量合计。")
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def build_consumption_summary(
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details: list[SurgeryConsumptionDetail],
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) -> list[SurgeryConsumptionSummary]:
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"""按 item_id 汇总 total_quantity；名称取该物品首条出现时的 item_name。"""
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totals: dict[str, tuple[str, int]] = {}
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for row in details:
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if row.item_id not in totals:
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totals[row.item_id] = (row.item_name, 0)
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name, acc = totals[row.item_id]
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totals[row.item_id] = (name, acc + row.qty)
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return [
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SurgeryConsumptionSummary(
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item_id=iid,
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item_name=name,
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total_quantity=qty,
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)
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for iid, (name, qty) in sorted(totals.items(), key=lambda x: x[0])
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]
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class PendingConfirmationOption(BaseModel):
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label: str
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confidence: float
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class SurgeryPendingConfirmationResponse(BaseModel):
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"""当前待医生确认的一条低置信度识别。"""
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surgery_id: str
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confirmation_id: str
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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）。")
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prompt_audio_mp3_base64: str = Field(
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description=(
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"与 prompt_text 对应的百度 TTS 音频（MP3）的标准 Base64 字符串（无换行）；"
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"客户端解码为二进制后以 audio/mpeg 播放。"
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),
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)
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options: list[PendingConfirmationOption]
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model_top1_label: str = Field(description="模型原始 Top1 标签（可能不在候选清单内）。")
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model_top1_confidence: float
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created_at: datetime
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class SurgeryPendingConfirmationResolveResponse(BaseModel):
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surgery_id: str
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confirmation_id: str
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status: str = Field(description="accepted")
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message: str
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resolved_label: str | None = Field(
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default=None,
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description="解析并确认后的耗材名称；否认全部候选时为 null。",
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)
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rejected: bool = Field(
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default=False,
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description="是否为否认全部候选（不记消耗）。",
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)
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asr_text: str | None = Field(
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default=None,
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description="服务端语音识别得到的文本。",
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)
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audio_object_key: str | None = Field(
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default=None,
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description="MinIO 中原始 WAV 的对象键，用于追溯。",
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)
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class SurgeryResultResponse(BaseModel):
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model_config = ConfigDict(
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json_schema_extra={
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"example": {
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"surgery_id": "123456",
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"status": "completed",
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"message": "结果查询成功。",
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"details": [
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{
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"item_id": "HC001",
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"item_name": "纱布",
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"qty": 1,
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"doctor_id": "D1001",
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"timestamp": "2026-04-21T10:30:00+08:00",
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},
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{
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"item_id": "HC001",
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"item_name": "纱布",
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"qty": 1,
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"doctor_id": "D1002",
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"timestamp": "2026-04-21T11:05:00+08:00",
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},
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{
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"item_id": "HC002",
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"item_name": "缝线",
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"qty": 1,
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"doctor_id": "D1001",
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"timestamp": "2026-04-21T10:45:00+08:00",
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},
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],
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"summary": [
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{"item_id": "HC001", "item_name": "纱布", "total_quantity": 2},
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{"item_id": "HC002", "item_name": "缝线", "total_quantity": 1},
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],
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}
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}
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)
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surgery_id: str = Field(description="手术6位号。")
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status: str = Field(description="结果状态，例如 pending / completed / failed。")
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message: str = Field(description="返回说明。")
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details: list[SurgeryConsumptionDetail] = Field(
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default_factory=list,
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description=(
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"消耗明细（多行）。每行字段顺序：item_id、item_name、qty、doctor_id、timestamp；"
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"同一 item_id 可多次出现。"
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),
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)
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summary: list[SurgeryConsumptionSummary] = Field(
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default_factory=list,
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description=(
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"按 item_id 汇总的合计表（仅 item_id、item_name、total_quantity），"
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"应与 details 按 item_id 汇总 qty 一致。"
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),
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)
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