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pythondatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learningannotation-tool
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43 lines
1.6 KiB
43 lines
1.6 KiB
import os
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from django.shortcuts import get_object_or_404
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from django_drf_filepond.api import store_upload
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from django_drf_filepond.models import TemporaryUpload
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from rest_framework import status
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from rest_framework.permissions import IsAuthenticated
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from rest_framework.response import Response
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from rest_framework.views import APIView
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from projects.models import Project
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from projects.permissions import IsProjectAdmin
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from .celery_tasks import import_dataset
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from .pipeline.catalog import Options
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class DatasetCatalog(APIView):
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permission_classes = [IsAuthenticated & IsProjectAdmin]
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def get(self, request, *args, **kwargs):
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project_id = kwargs["project_id"]
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project = get_object_or_404(Project, pk=project_id)
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options = Options.filter_by_task(project.project_type)
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return Response(data=options, status=status.HTTP_200_OK)
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class DatasetImportAPI(APIView):
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permission_classes = [IsAuthenticated & IsProjectAdmin]
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def post(self, request, *args, **kwargs):
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project_id = self.kwargs["project_id"]
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upload_ids = request.data.pop("uploadIds")
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file_format = request.data.pop("format")
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tus = [TemporaryUpload.objects.get(upload_id=upload_id) for upload_id in upload_ids]
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sus = [
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store_upload(tu.upload_id, destination_file_path=os.path.join(tu.file.name, tu.upload_name)) for tu in tus
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]
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filenames = [su.file.path for su in sus]
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task = import_dataset.delay(
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user_id=request.user.id, project_id=project_id, filenames=filenames, file_format=file_format, **request.data
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)
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return Response({"task_id": task.task_id})
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