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

269 lines
9.0 KiB
Python
Raw Normal View History

from __future__ import annotations
from dataclasses import dataclass
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}$",
description="手术6位号只允许6位数字。",
)
camera_ids: list[str] = Field(
min_length=1,
description="本次手术需要接入的摄像头 ID 列表。",
)
candidate_consumables: list[str] = Field(
default_factory=list,
description=(
"本次手术可能使用到的耗材清单。"
"服务端仅对该清单内的耗材做自动记账与待确认追问;"
"若为空则不会写入任何消耗(仅拉流推理)。"
),
)
class SurgeryEndRequest(BaseModel):
model_config = ConfigDict(
json_schema_extra={"example": {"surgery_id": "123456"}}
)
surgery_id: str = Field(
min_length=6,
max_length=6,
pattern=r"^\d{6}$",
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_iditem_nameqtydoctor_idtimestamp
"""
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:优先为耗材目录中的产品编码;"
"目录键经名称归一化后与分类类名匹配,未命中目录时与模型输出类名一致。"
),
)
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。")
doctor_id: str = Field(description="医生 ID。")
timestamp: datetime = Field(description="记录时间ISO 8601date-time")
@dataclass
class SurgeryConsumptionStored:
"""内存 / 数据库持久化用的明细行(含 source仅服务端内部使用不随 HTTP 返回)。"""
item_id: str
item_name: str
qty: int
doctor_id: str
timestamp: datetime
source: str = "vision"
def as_response(self) -> SurgeryConsumptionDetail:
return SurgeryConsumptionDetail(
item_id=self.item_id,
item_name=self.item_name,
qty=self.qty,
doctor_id=self.doctor_id,
timestamp=self.timestamp,
)
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": 2,
"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": 3},
{"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。"
),
)