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pythonannotation-tooldatasetsactive-learningtext-annotationdatasetnatural-language-processingdata-labelingmachine-learning
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45 lines
1.7 KiB
45 lines
1.7 KiB
from celery.result import AsyncResult
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from django.http import FileResponse
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from django.shortcuts import get_object_or_404
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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 .celery_tasks import export_dataset
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from .pipeline.catalog import Options
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from projects.models import Project
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from projects.permissions import IsProjectAdmin
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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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use_relation = getattr(project, "use_relation", False)
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options = Options.filter_by_task(project.project_type, use_relation)
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return Response(data=options, status=status.HTTP_200_OK)
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class DatasetExportAPI(APIView):
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permission_classes = [IsAuthenticated & IsProjectAdmin]
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def get(self, request, *args, **kwargs):
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task_id = request.GET["taskId"]
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task = AsyncResult(task_id)
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ready = task.ready()
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if ready:
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filename = task.result
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return FileResponse(open(filename, mode="rb"), as_attachment=True)
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return Response({"status": "Not ready"})
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def post(self, request, *args, **kwargs):
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project_id = self.kwargs["project_id"]
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file_format = request.data.pop("format")
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export_approved = request.data.pop("exportApproved", False)
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task = export_dataset.delay(
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project_id=project_id, file_format=file_format, confirmed_only=export_approved, **request.data
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)
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return Response({"task_id": task.task_id})
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