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