deepdata: core product code (backend, frontend, runtime, deepflow module)

2026-08-30 19:23:38 +08:00
commit bd3db30be9
1405 changed files with 271727 additions and 0 deletions
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+from typing import Literal, List, Dict, Any, Optional
+from datetime import datetime
+
+from pydantic import Field, ConfigDict
+
+from app.module.shared.schema import BaseResponseModel
+from app.module.shared.schema import StandardResponse
+
+
+class SyncDatasetRequest(BaseResponseModel):
+    """同步数据集请求模型"""
+    model_config = ConfigDict(populate_by_name=True)
+    
+    id: str = Field(..., description="映射ID（mapping UUID）")
+    batch_size: int = Field(50, ge=1, le=100, description="批处理大小", alias="batchSize")
+    file_priority: Literal[0, 1] = Field(0, description="0 数据集为主，1 标注平台为主", alias="filePriority")
+    label_priority: Literal[0, 1] = Field(0, description="0 数据集为主，1 标注平台为主", alias="labelPriority")
+    sync_annotations: bool = Field(True, description="是否同步标注数据", alias="syncAnnotations")
+    annotation_direction: Literal["ls_to_dm", "dm_to_ls", "bidirectional"] = Field(
+        "bidirectional", 
+        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)",
+        alias="annotationDirection"
+    )
+    overwrite: bool = Field(
+        True, 
+        description="是否覆盖DeepData中的标注（基于时间戳比较）"
+    )
+    overwrite_labeling_project: bool = Field(
+        True, 
+        description="是否覆盖Label Studio中的标注（基于时间戳比较）",
+        alias="overwriteLabelingProject"
+    )
+
+class SyncDatasetResponse(BaseResponseModel):
+    """同步数据集响应模型"""
+    id: str = Field(..., description="映射UUID")
+    status: str = Field(..., description="同步状态")
+    synced_files: int = Field(..., description="已同步文件数量")
+    total_files: int = Field(0, description="总文件数量")
+    message: str = Field(..., description="响应消息")
+
+class SyncDatasetResponseStd(StandardResponse[SyncDatasetResponse]):
+    pass
+
+
+class SyncAnnotationsRequest(BaseResponseModel):
+    """同步标注请求模型
+    
+    使用camelCase作为API接口字段名（通过alias），但Python代码内部使用snake_case。
+    Pydantic会自动处理两种格式的转换。
+    """
+    model_config = ConfigDict(populate_by_name=True)
+    
+    id: str = Field(..., description="映射ID（mapping UUID）")
+    batch_size: int = Field(50, ge=1, le=100, description="批处理大小", alias="batchSize")
+    direction: Literal["ls_to_dm", "dm_to_ls", "bidirectional"] = Field(
+        "bidirectional", 
+        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)"
+    )
+    overwrite: bool = Field(
+        True, 
+        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"
+    )
+    overwrite_labeling_project: bool = Field(
+        True, 
+        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",
+        alias="overwriteLabelingProject"
+    )
+
+
+class TagInfo(BaseResponseModel):
+    """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）"""
+    from_name: str = Field(..., description="标注工具名称")
+    to_name: str = Field(..., description="目标对象名称")
+    type: str = Field(..., description="标注类型")
+    values: Dict[str, Any] = Field(..., description="标注值")
+
+
+class SyncAnnotationsResponse(BaseResponseModel):
+    """同步标注响应模型"""
+    id: str = Field(..., description="映射UUID")
+    status: str = Field(..., description="同步状态: success/partial/error")
+    synced_to_dm: int = Field(0, description="同步到数据集的标注数量")
+    synced_to_ls: int = Field(0, description="同步到Label Studio的标注数量")
+    skipped: int = Field(0, description="跳过的标注数量")
+    failed: int = Field(0, description="失败的标注数量")
+    conflicts_resolved: int = Field(0, description="解决的冲突数量")
+    message: str = Field(..., description="响应消息")
+
+
+class SyncAnnotationsResponseStd(StandardResponse[SyncAnnotationsResponse]):
+    pass