92 lines
4.3 KiB
Python
92 lines
4.3 KiB
Python
from typing import Literal, List, Dict, Any, Optional
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from datetime import datetime
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from pydantic import Field, ConfigDict
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from app.module.shared.schema import BaseResponseModel
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from app.module.shared.schema import StandardResponse
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class SyncDatasetRequest(BaseResponseModel):
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"""同步数据集请求模型"""
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model_config = ConfigDict(populate_by_name=True)
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id: str = Field(..., description="映射ID（mapping UUID）")
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batch_size: int = Field(50, ge=1, le=100, description="批处理大小", alias="batchSize")
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file_priority: Literal[0, 1] = Field(0, description="0 数据集为主，1 标注平台为主", alias="filePriority")
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label_priority: Literal[0, 1] = Field(0, description="0 数据集为主，1 标注平台为主", alias="labelPriority")
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sync_annotations: bool = Field(True, description="是否同步标注数据", alias="syncAnnotations")
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annotation_direction: Literal["ls_to_dm", "dm_to_ls", "bidirectional"] = Field(
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"bidirectional",
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description="标注同步方向: ls_to_dm(Label Studio到数据集), dm_to_ls(数据集到Label Studio), bidirectional(双向)",
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alias="annotationDirection"
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)
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overwrite: bool = Field(
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True,
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description="是否覆盖DeepData中的标注（基于时间戳比较）"
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)
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overwrite_labeling_project: bool = Field(
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True,
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description="是否覆盖Label Studio中的标注（基于时间戳比较）",
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alias="overwriteLabelingProject"
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)
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class SyncDatasetResponse(BaseResponseModel):
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"""同步数据集响应模型"""
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id: str = Field(..., description="映射UUID")
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status: str = Field(..., description="同步状态")
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synced_files: int = Field(..., description="已同步文件数量")
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total_files: int = Field(0, description="总文件数量")
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message: str = Field(..., description="响应消息")
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class SyncDatasetResponseStd(StandardResponse[SyncDatasetResponse]):
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pass
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class SyncAnnotationsRequest(BaseResponseModel):
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"""同步标注请求模型
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使用camelCase作为API接口字段名（通过alias），但Python代码内部使用snake_case。
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Pydantic会自动处理两种格式的转换。
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"""
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model_config = ConfigDict(populate_by_name=True)
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id: str = Field(..., description="映射ID（mapping UUID）")
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batch_size: int = Field(50, ge=1, le=100, description="批处理大小", alias="batchSize")
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direction: Literal["ls_to_dm", "dm_to_ls", "bidirectional"] = Field(
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"bidirectional",
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description="同步方向: ls_to_dm(Label Studio到数据集), dm_to_ls(数据集到Label Studio), bidirectional(双向)"
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)
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overwrite: bool = Field(
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True,
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description="是否覆盖DeepData中的标注（基于时间戳比较）。True时，如果Label Studio的标注更新时间更新，则覆盖DeepData的标注"
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)
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overwrite_labeling_project: bool = Field(
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True,
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description="是否覆盖Label Studio中的标注（基于时间戳比较）。True时，如果DeepData的标注更新时间更新，则覆盖Label Studio的标注",
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alias="overwriteLabelingProject"
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)
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class TagInfo(BaseResponseModel):
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"""标注信息结构（不包含时间戳，时间戳存储在文件级别的tags_updated_at字段）"""
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from_name: str = Field(..., description="标注工具名称")
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to_name: str = Field(..., description="目标对象名称")
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type: str = Field(..., description="标注类型")
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values: Dict[str, Any] = Field(..., description="标注值")
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class SyncAnnotationsResponse(BaseResponseModel):
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"""同步标注响应模型"""
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id: str = Field(..., description="映射UUID")
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status: str = Field(..., description="同步状态: success/partial/error")
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synced_to_dm: int = Field(0, description="同步到数据集的标注数量")
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synced_to_ls: int = Field(0, description="同步到Label Studio的标注数量")
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skipped: int = Field(0, description="跳过的标注数量")
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failed: int = Field(0, description="失败的标注数量")
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conflicts_resolved: int = Field(0, description="解决的冲突数量")
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message: str = Field(..., description="响应消息")
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class SyncAnnotationsResponseStd(StandardResponse[SyncAnnotationsResponse]):
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pass |