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92 lines
3.4 KiB
Python
92 lines
3.4 KiB
Python
from flask import request
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from flask_restful import marshal, reqparse
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import services.dataset_service
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from controllers.service_api import api
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from controllers.service_api.dataset.error import DatasetNameDuplicateError
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from controllers.service_api.wraps import DatasetApiResource
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from core.model_runtime.entities.model_entities import ModelType
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from core.provider_manager import ProviderManager
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from fields.dataset_fields import dataset_detail_fields
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from libs.login import current_user
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from models.dataset import Dataset
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from services.dataset_service import DatasetService
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def _validate_name(name):
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if not name or len(name) < 1 or len(name) > 40:
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raise ValueError('Name must be between 1 to 40 characters.')
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return name
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class DatasetApi(DatasetApiResource):
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"""Resource for get datasets."""
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def get(self, tenant_id):
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page = request.args.get('page', default=1, type=int)
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limit = request.args.get('limit', default=20, type=int)
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provider = request.args.get('provider', default="vendor")
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datasets, total = DatasetService.get_datasets(page, limit, provider,
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tenant_id, current_user)
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# check embedding setting
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provider_manager = ProviderManager()
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configurations = provider_manager.get_configurations(
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tenant_id=current_user.current_tenant_id
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)
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embedding_models = configurations.get_models(
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model_type=ModelType.TEXT_EMBEDDING,
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only_active=True
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)
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model_names = []
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for embedding_model in embedding_models:
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model_names.append(f"{embedding_model.model}:{embedding_model.provider.provider}")
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data = marshal(datasets, dataset_detail_fields)
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for item in data:
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if item['indexing_technique'] == 'high_quality':
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item_model = f"{item['embedding_model']}:{item['embedding_model_provider']}"
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if item_model in model_names:
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item['embedding_available'] = True
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else:
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item['embedding_available'] = False
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else:
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item['embedding_available'] = True
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response = {
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'data': data,
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'has_more': len(datasets) == limit,
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'limit': limit,
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'total': total,
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'page': page
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}
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return response, 200
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"""Resource for datasets."""
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def post(self, tenant_id):
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parser = reqparse.RequestParser()
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parser.add_argument('name', nullable=False, required=True,
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help='type is required. Name must be between 1 to 40 characters.',
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type=_validate_name)
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parser.add_argument('indexing_technique', type=str, location='json',
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choices=Dataset.INDEXING_TECHNIQUE_LIST,
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help='Invalid indexing technique.')
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args = parser.parse_args()
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try:
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dataset = DatasetService.create_empty_dataset(
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tenant_id=tenant_id,
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name=args['name'],
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indexing_technique=args['indexing_technique'],
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account=current_user
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)
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except services.errors.dataset.DatasetNameDuplicateError:
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raise DatasetNameDuplicateError()
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return marshal(dataset, dataset_detail_fields), 200
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api.add_resource(DatasetApi, '/datasets')
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