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refactor(annotation): 移除对 Label Studio Server 的依赖并切换到内嵌编辑器模式
- 移除 LabelStudioClient 和 SyncService 的导入及使用 - 删除与 Label Studio 项目的创建、删除和同步相关代码 - 修改创建数据集映射功能，改为创建 DataMate 标注项目 - 更新删除映射接口，仅进行软删除不再删除 Label Studio 项目 - 修改同步接口为兼容性保留，实际操作为空操作 - 移除 Label Studio 连接诊断功能 - 更新文档说明以反映内嵌编辑器模式的变化
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@@ -2,7 +2,7 @@ from typing import Optional
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import math
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import uuid
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from fastapi import APIRouter, Depends, HTTPException, Query, Path, Response
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from fastapi import APIRouter, Depends, HTTPException, Query, Path
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.db.session import get_db
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@@ -10,11 +10,8 @@ from app.db.models import LabelingProject
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from app.module.shared.schema import StandardResponse, PaginatedData
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from app.module.dataset import DatasetManagementService
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from app.core.logging import get_logger
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from app.core.config import settings
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from ..client import LabelStudioClient
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from ..service.mapping import DatasetMappingService
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from ..service.sync import SyncService
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from ..service.template import AnnotationTemplateService
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from ..schema import (
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DatasetMappingCreateRequest,
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@@ -30,37 +27,11 @@ router = APIRouter(
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logger = get_logger(__name__)
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@router.get("/{mapping_id}/login")
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async def list_mappings(
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async def login_label_studio(
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mapping_id: str,
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db: AsyncSession = Depends(get_db)
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):
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try:
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ls_client = LabelStudioClient(base_url=settings.label_studio_base_url,
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token=settings.label_studio_user_token)
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target_response = await ls_client.login_label_studio()
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headers = dict(target_response.headers)
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set_cookies = target_response.headers.get_list("set-cookie")
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# 删除合并的 Set-Cookie
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if "set-cookie" in headers:
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del headers["set-cookie"]
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# 创建新响应，添加多个 Set-Cookie
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response = Response(
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content=target_response.content,
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status_code=target_response.status_code,
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headers=headers
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)
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# 分别添加每个 Set-Cookie
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for cookie in set_cookies:
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response.headers.append("set-cookie", cookie)
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return response
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Error while logining in LabelStudio: {e}", e)
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raise HTTPException(status_code=500, detail="Internal server error")
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raise HTTPException(status_code=410, detail="当前为内嵌编辑器模式，不再支持 Label Studio 登录代理接口")
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@router.post("", response_model=StandardResponse[DatasetMappingCreateResponse], status_code=201)
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async def create_mapping(
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@@ -70,8 +41,7 @@ async def create_mapping(
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"""
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创建数据集映射
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根据指定的DM程序中的数据集，创建Label Studio中的数据集，
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在数据库中记录这一关联关系，返回Label Studio数据集的ID
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在 DataMate 中创建标注项目（t_dm_labeling_projects），用于内嵌 Label Studio 编辑器。
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注意：一个数据集可以创建多个标注项目
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@@ -79,10 +49,7 @@ async def create_mapping(
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"""
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try:
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dm_client = DatasetManagementService(db)
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ls_client = LabelStudioClient(base_url=settings.label_studio_base_url,
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token=settings.label_studio_user_token)
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mapping_service = DatasetMappingService(db)
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sync_service = SyncService(dm_client, ls_client, mapping_service)
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template_service = AnnotationTemplateService()
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logger.info(f"Create dataset mapping request: {request.dataset_id}")
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@@ -116,51 +83,28 @@ async def create_mapping(
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label_config = template.label_config
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logger.debug(f"Template label config loaded for template: {template.name}")
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# 在Label Studio中创建项目
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project_data = await ls_client.create_project(
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title=project_name,
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description=project_description,
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label_config=label_config # 传递模板配置
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)
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# DataMate-only：不再创建/依赖 Label Studio Server 项目。
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# 为兼容既有 schema 字段（labeling_project_id 长度 8），生成一个 8 位数字 ID。
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labeling_project_id = str(uuid.uuid4().int % 10**8).zfill(8)
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if not project_data:
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raise HTTPException(
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status_code=500,
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detail="Fail to create Label Studio project."
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)
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project_id = project_data["id"]
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# 配置本地存储：dataset/<id>
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local_storage_path = f"{settings.label_studio_local_document_root}/{request.dataset_id}"
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storage_result = await ls_client.create_local_storage(
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project_id=project_id,
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path=local_storage_path,
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title="Dataset_BLOB",
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use_blob_urls=True,
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description=f"Local storage for dataset {dataset_info.name}"
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)
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if not storage_result:
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# 本地存储配置失败，记录警告但不中断流程
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logger.warning(f"Failed to configure local storage for project {project_id}")
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else:
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logger.info(f"Local storage configured for project {project_id}: {local_storage_path}")
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project_configuration = {}
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if label_config:
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project_configuration["label_config"] = label_config
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if project_description:
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project_configuration["description"] = project_description
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labeling_project = LabelingProject(
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id=str(uuid.uuid4()), # Generate UUID here
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dataset_id=request.dataset_id,
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labeling_project_id=str(project_id),
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labeling_project_id=labeling_project_id,
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name=project_name,
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template_id=request.template_id, # Save template_id to database
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configuration=project_configuration or None,
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)
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# 创建映射关系，包含项目名称（先持久化映射以获得 mapping.id）
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mapping = await mapping_service.create_mapping(labeling_project)
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# 进行一次同步，使用创建后的 mapping.id
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await sync_service.sync_dataset_files(mapping.id, 100)
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response_data = DatasetMappingCreateResponse(
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id=mapping.id,
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labeling_project_id=str(mapping.labeling_project_id),
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@@ -347,19 +291,15 @@ async def delete_mapping(
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db: AsyncSession = Depends(get_db)
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):
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"""
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删除映射关系和对应的 Label Studio 项目
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删除映射关系（软删除）
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通过 path 参数 `project_id` 指定要删除的映射（映射的 UUID）。
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此操作会：
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1. 删除 Label Studio 中的项目
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2. 软删除数据库中的映射记录
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内嵌编辑器模式下仅软删除 DataMate 标注项目记录，不再删除/依赖 Label Studio Server 项目。
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"""
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try:
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logger.debug(f"Delete mapping request received: project_id={project_id!r}")
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ls_client = LabelStudioClient(base_url=settings.label_studio_base_url,
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token=settings.label_studio_user_token)
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service = DatasetMappingService(db)
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# 使用 mapping UUID 查询映射记录
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@@ -375,23 +315,9 @@ async def delete_mapping(
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)
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id = mapping.id
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labeling_project_id = mapping.labeling_project_id
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logger.debug(f"Found mapping: {id}")
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logger.debug(f"Found mapping: {id}, Label Studio project ID: {labeling_project_id}")
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# 1. 删除 Label Studio 项目
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try:
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logger.debug(f"Deleting Label Studio project: {labeling_project_id}")
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delete_success = await ls_client.delete_project(int(labeling_project_id))
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if delete_success:
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logger.debug(f"Successfully deleted Label Studio project: {labeling_project_id}")
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else:
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logger.warning(f"Failed to delete Label Studio project or project not found: {labeling_project_id}")
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except Exception as e:
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logger.error(f"Error deleting Label Studio project: {e}")
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# 继续执行，即使 Label Studio 项目删除失败也要删除映射记录
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# 2. 软删除映射记录
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# 软删除映射记录
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soft_delete_success = await service.soft_delete_mapping(id)
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logger.debug(f"Soft delete result for mapping {id}: {soft_delete_success}")
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@@ -401,7 +327,7 @@ async def delete_mapping(
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detail="Failed to delete mapping record"
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)
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logger.info(f"Successfully deleted mapping: {id}, Label Studio project: {labeling_project_id}")
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logger.info(f"Successfully deleted mapping: {id}")
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return StandardResponse(
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code=200,
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