You've already forked DataMate
Jerry Yan
371df12a96
- 在前端组件中新增 segmentationEnabled 字段控制切片开关 - 为文本数据集添加段落切片配置选项，默认启用切片功能 - 在后端接口中新增 segmentation_enabled 参数传递给标注项目 - 实现切片逻辑控制，支持文本数据的自动段落分割 - 添加数据集类型判断，仅文本数据集支持切片配置 - 更新标注任务创建和编辑表单中的切片相关字段处理
76 lines
3.7 KiB
Python
76 lines
3.7 KiB
Python
from pydantic import Field, BaseModel
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from typing import Optional, TYPE_CHECKING
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from datetime import datetime
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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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if TYPE_CHECKING:
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from .template import AnnotationTemplateResponse
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class DatasetMappingCreateRequest(BaseModel):
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"""数据集映射 创建 请求模型
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Accept both snake_case and camelCase field names from frontend JSON by
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declaring explicit aliases. Frontend sends `datasetId`, `name`,
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`description`, `templateId` (camelCase), so provide aliases so pydantic will map them
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to the internal attributes used in the service code (dataset_id, name,
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description, template_id).
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"""
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dataset_id: str = Field(..., alias="datasetId", description="源数据集ID")
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name: Optional[str] = Field(None, alias="name", description="标注项目名称")
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description: Optional[str] = Field(None, alias="description", description="标注项目描述")
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template_id: Optional[str] = Field(None, alias="templateId", description="标注模板ID")
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label_config: Optional[str] = Field(None, alias="labelConfig", description="Label Studio XML配置")
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segmentation_enabled: Optional[bool] = Field(
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None,
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alias="segmentationEnabled",
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description="是否启用文本分段",
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)
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class Config:
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# allow population by field name when constructing model programmatically
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validate_by_name = True
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class DatasetMappingCreateResponse(BaseResponseModel):
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"""数据集映射 创建 响应模型"""
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id: str = Field(..., description="映射UUID")
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labeling_project_id: str = Field(..., description="Label Studio项目ID")
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labeling_project_name: str = Field(..., description="Label Studio项目名称")
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class DatasetMappingUpdateRequest(BaseResponseModel):
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"""数据集映射 更新 请求模型"""
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dataset_id: Optional[str] = Field(None, description="源数据集ID")
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class DatasetMappingResponse(BaseModel):
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"""数据集映射 查询 响应模型"""
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id: str = Field(..., description="映射UUID")
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dataset_id: str = Field(..., alias="datasetId", description="源数据集ID")
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dataset_name: Optional[str] = Field(None, alias="datasetName", description="数据集名称")
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labeling_project_id: str = Field(..., alias="labelingProjectId", description="标注项目ID")
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name: Optional[str] = Field(None, description="标注项目名称")
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description: Optional[str] = Field(None, description="标注项目描述")
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template_id: Optional[str] = Field(None, alias="templateId", description="关联的模板ID")
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template: Optional['AnnotationTemplateResponse'] = Field(None, description="关联的标注模板详情")
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label_config: Optional[str] = Field(None, alias="labelConfig", description="实际使用的 Label Studio XML 配置")
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segmentation_enabled: Optional[bool] = Field(
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None,
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alias="segmentationEnabled",
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description="是否启用文本分段",
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)
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total_count: int = Field(0, alias="totalCount", description="数据集总数据量")
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annotated_count: int = Field(0, alias="annotatedCount", description="已标注数据量")
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created_at: datetime = Field(..., alias="createdAt", description="创建时间")
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updated_at: Optional[datetime] = Field(None, alias="updatedAt", description="更新时间")
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deleted_at: Optional[datetime] = Field(None, alias="deletedAt", description="删除时间")
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class Config:
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from_attributes = True
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populate_by_name = True
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class DeleteDatasetResponse(BaseResponseModel):
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"""删除数据集响应模型"""
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id: str = Field(..., description="映射UUID")
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status: str = Field(..., description="删除状态")
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