dataset.py 3.3 KB

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  1. from flask import request
  2. from flask_restful import reqparse, marshal
  3. import services.dataset_service
  4. from controllers.service_api import api
  5. from controllers.service_api.dataset.error import DatasetNameDuplicateError
  6. from controllers.service_api.wraps import DatasetApiResource
  7. from libs.login import current_user
  8. from core.model_providers.models.entity.model_params import ModelType
  9. from fields.dataset_fields import dataset_detail_fields
  10. from services.dataset_service import DatasetService
  11. from services.provider_service import ProviderService
  12. def _validate_name(name):
  13. if not name or len(name) < 1 or len(name) > 40:
  14. raise ValueError('Name must be between 1 to 40 characters.')
  15. return name
  16. class DatasetApi(DatasetApiResource):
  17. """Resource for get datasets."""
  18. def get(self, tenant_id):
  19. page = request.args.get('page', default=1, type=int)
  20. limit = request.args.get('limit', default=20, type=int)
  21. provider = request.args.get('provider', default="vendor")
  22. datasets, total = DatasetService.get_datasets(page, limit, provider,
  23. tenant_id, current_user)
  24. # check embedding setting
  25. provider_service = ProviderService()
  26. valid_model_list = provider_service.get_valid_model_list(current_user.current_tenant_id,
  27. ModelType.EMBEDDINGS.value)
  28. model_names = []
  29. for valid_model in valid_model_list:
  30. model_names.append(f"{valid_model['model_name']}:{valid_model['model_provider']['provider_name']}")
  31. data = marshal(datasets, dataset_detail_fields)
  32. for item in data:
  33. if item['indexing_technique'] == 'high_quality':
  34. item_model = f"{item['embedding_model']}:{item['embedding_model_provider']}"
  35. if item_model in model_names:
  36. item['embedding_available'] = True
  37. else:
  38. item['embedding_available'] = False
  39. else:
  40. item['embedding_available'] = True
  41. response = {
  42. 'data': data,
  43. 'has_more': len(datasets) == limit,
  44. 'limit': limit,
  45. 'total': total,
  46. 'page': page
  47. }
  48. return response, 200
  49. """Resource for datasets."""
  50. def post(self, tenant_id):
  51. parser = reqparse.RequestParser()
  52. parser.add_argument('name', nullable=False, required=True,
  53. help='type is required. Name must be between 1 to 40 characters.',
  54. type=_validate_name)
  55. parser.add_argument('indexing_technique', type=str, location='json',
  56. choices=('high_quality', 'economy'),
  57. help='Invalid indexing technique.')
  58. args = parser.parse_args()
  59. try:
  60. dataset = DatasetService.create_empty_dataset(
  61. tenant_id=tenant_id,
  62. name=args['name'],
  63. indexing_technique=args['indexing_technique'],
  64. account=current_user
  65. )
  66. except services.errors.dataset.DatasetNameDuplicateError:
  67. raise DatasetNameDuplicateError()
  68. return marshal(dataset, dataset_detail_fields), 200
  69. api.add_resource(DatasetApi, '/datasets')