Feat/dataset service api (#1245)
Co-authored-by: jyong <jyong@dify.ai> Co-authored-by: StyleZhang <jasonapring2015@outlook.com>
This commit is contained in:
Jyong
@@ -1,114 +1,291 @@
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import datetime
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import json
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import uuid
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from flask import current_app
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from flask_restful import reqparse
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from flask import current_app, request
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from flask_restful import reqparse, marshal
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from sqlalchemy import desc
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from werkzeug.exceptions import NotFound
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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.app.error import ProviderNotInitializeError
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from controllers.service_api.dataset.error import ArchivedDocumentImmutableError, DocumentIndexingError, \
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DatasetNotInitedError
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NoFileUploadedError, TooManyFilesError
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from controllers.service_api.wraps import DatasetApiResource
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from core.login.login import current_user
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from core.model_providers.error import ProviderTokenNotInitError
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from extensions.ext_database import db
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from extensions.ext_storage import storage
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from fields.document_fields import document_fields, document_status_fields
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from models.dataset import Dataset, Document, DocumentSegment
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from models.model import UploadFile
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from services.dataset_service import DocumentService
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from services.file_service import FileService
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class DocumentListApi(DatasetApiResource):
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class DocumentAddByTextApi(DatasetApiResource):
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"""Resource for documents."""
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def post(self, dataset):
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"""Create document."""
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def post(self, tenant_id, dataset_id):
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"""Create document by text."""
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parser = reqparse.RequestParser()
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parser.add_argument('name', type=str, required=True, nullable=False, location='json')
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parser.add_argument('text', type=str, required=True, nullable=False, location='json')
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parser.add_argument('doc_type', type=str, location='json')
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parser.add_argument('doc_metadata', type=dict, location='json')
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parser.add_argument('process_rule', type=dict, required=False, nullable=True, location='json')
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parser.add_argument('original_document_id', type=str, required=False, location='json')
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parser.add_argument('doc_form', type=str, default='text_model', required=False, nullable=False, location='json')
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parser.add_argument('doc_language', type=str, default='English', required=False, nullable=False,
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location='json')
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parser.add_argument('indexing_technique', type=str, choices=Dataset.INDEXING_TECHNIQUE_LIST, nullable=False,
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location='json')
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args = parser.parse_args()
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dataset_id = str(dataset_id)
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tenant_id = str(tenant_id)
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset.indexing_technique:
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raise DatasetNotInitedError("Dataset indexing technique must be set.")
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if not dataset:
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raise ValueError('Dataset is not exist.')
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doc_type = args.get('doc_type')
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doc_metadata = args.get('doc_metadata')
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if not dataset.indexing_technique and not args['indexing_technique']:
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raise ValueError('indexing_technique is required.')
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if doc_type and doc_type not in DocumentService.DOCUMENT_METADATA_SCHEMA:
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raise ValueError('Invalid doc_type.')
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# user uuid as file name
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file_uuid = str(uuid.uuid4())
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file_key = 'upload_files/' + dataset.tenant_id + '/' + file_uuid + '.txt'
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# save file to storage
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storage.save(file_key, args.get('text'))
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# save file to db
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config = current_app.config
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upload_file = UploadFile(
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tenant_id=dataset.tenant_id,
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storage_type=config['STORAGE_TYPE'],
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key=file_key,
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name=args.get('name') + '.txt',
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size=len(args.get('text')),
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extension='txt',
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mime_type='text/plain',
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created_by=dataset.created_by,
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created_at=datetime.datetime.utcnow(),
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used=True,
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used_by=dataset.created_by,
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used_at=datetime.datetime.utcnow()
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)
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db.session.add(upload_file)
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db.session.commit()
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document_data = {
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'data_source': {
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'type': 'upload_file',
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'info': [
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{
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'upload_file_id': upload_file.id
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}
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]
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upload_file = FileService.upload_text(args.get('text'), args.get('name'))
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data_source = {
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'type': 'upload_file',
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'info_list': {
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'data_source_type': 'upload_file',
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'file_info_list': {
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'file_ids': [upload_file.id]
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}
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}
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}
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args['data_source'] = data_source
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# validate args
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DocumentService.document_create_args_validate(args)
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try:
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documents, batch = DocumentService.save_document_with_dataset_id(
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dataset=dataset,
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document_data=document_data,
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account=dataset.created_by_account,
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dataset_process_rule=dataset.latest_process_rule,
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document_data=args,
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account=current_user,
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dataset_process_rule=dataset.latest_process_rule if 'process_rule' not in args else None,
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created_from='api'
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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document = documents[0]
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if doc_type and doc_metadata:
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metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[doc_type]
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document.doc_metadata = {}
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for key, value_type in metadata_schema.items():
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value = doc_metadata.get(key)
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if value is not None and isinstance(value, value_type):
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document.doc_metadata[key] = value
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document.doc_type = doc_type
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document.updated_at = datetime.datetime.utcnow()
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db.session.commit()
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return {'id': document.id}
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documents_and_batch_fields = {
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'document': marshal(document, document_fields),
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'batch': batch
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}
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return documents_and_batch_fields, 200
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class DocumentApi(DatasetApiResource):
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def delete(self, dataset, document_id):
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class DocumentUpdateByTextApi(DatasetApiResource):
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"""Resource for update documents."""
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def post(self, tenant_id, dataset_id, document_id):
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"""Update document by text."""
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parser = reqparse.RequestParser()
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parser.add_argument('name', type=str, required=False, nullable=True, location='json')
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parser.add_argument('text', type=str, required=False, nullable=True, location='json')
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parser.add_argument('process_rule', type=dict, required=False, nullable=True, location='json')
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parser.add_argument('doc_form', type=str, default='text_model', required=False, nullable=False, location='json')
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parser.add_argument('doc_language', type=str, default='English', required=False, nullable=False,
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location='json')
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args = parser.parse_args()
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dataset_id = str(dataset_id)
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tenant_id = str(tenant_id)
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset:
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raise ValueError('Dataset is not exist.')
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if args['text']:
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upload_file = FileService.upload_text(args.get('text'), args.get('name'))
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data_source = {
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'type': 'upload_file',
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'info_list': {
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'data_source_type': 'upload_file',
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'file_info_list': {
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'file_ids': [upload_file.id]
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}
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}
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}
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args['data_source'] = data_source
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# validate args
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args['original_document_id'] = str(document_id)
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DocumentService.document_create_args_validate(args)
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try:
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documents, batch = DocumentService.save_document_with_dataset_id(
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dataset=dataset,
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document_data=args,
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account=current_user,
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dataset_process_rule=dataset.latest_process_rule if 'process_rule' not in args else None,
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created_from='api'
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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document = documents[0]
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documents_and_batch_fields = {
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'document': marshal(document, document_fields),
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'batch': batch
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}
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return documents_and_batch_fields, 200
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class DocumentAddByFileApi(DatasetApiResource):
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"""Resource for documents."""
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def post(self, tenant_id, dataset_id):
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"""Create document by upload file."""
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args = {}
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if 'data' in request.form:
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args = json.loads(request.form['data'])
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if 'doc_form' not in args:
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args['doc_form'] = 'text_model'
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if 'doc_language' not in args:
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args['doc_language'] = 'English'
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# get dataset info
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dataset_id = str(dataset_id)
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tenant_id = str(tenant_id)
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset:
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raise ValueError('Dataset is not exist.')
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if not dataset.indexing_technique and not args['indexing_technique']:
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raise ValueError('indexing_technique is required.')
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# save file info
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file = request.files['file']
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# check file
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if 'file' not in request.files:
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raise NoFileUploadedError()
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if len(request.files) > 1:
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raise TooManyFilesError()
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upload_file = FileService.upload_file(file)
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data_source = {
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'type': 'upload_file',
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'info_list': {
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'file_info_list': {
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'file_ids': [upload_file.id]
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}
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}
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}
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args['data_source'] = data_source
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# validate args
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DocumentService.document_create_args_validate(args)
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try:
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documents, batch = DocumentService.save_document_with_dataset_id(
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dataset=dataset,
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document_data=args,
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account=dataset.created_by_account,
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dataset_process_rule=dataset.latest_process_rule if 'process_rule' not in args else None,
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created_from='api'
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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document = documents[0]
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documents_and_batch_fields = {
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'document': marshal(document, document_fields),
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'batch': batch
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}
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return documents_and_batch_fields, 200
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class DocumentUpdateByFileApi(DatasetApiResource):
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"""Resource for update documents."""
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def post(self, tenant_id, dataset_id, document_id):
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"""Update document by upload file."""
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args = {}
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if 'data' in request.form:
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args = json.loads(request.form['data'])
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if 'doc_form' not in args:
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args['doc_form'] = 'text_model'
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if 'doc_language' not in args:
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args['doc_language'] = 'English'
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# get dataset info
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dataset_id = str(dataset_id)
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tenant_id = str(tenant_id)
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset:
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raise ValueError('Dataset is not exist.')
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if 'file' in request.files:
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# save file info
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file = request.files['file']
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if len(request.files) > 1:
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raise TooManyFilesError()
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upload_file = FileService.upload_file(file)
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data_source = {
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'type': 'upload_file',
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'info_list': {
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'file_info_list': {
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'file_ids': [upload_file.id]
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}
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}
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}
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args['data_source'] = data_source
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# validate args
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args['original_document_id'] = str(document_id)
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DocumentService.document_create_args_validate(args)
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try:
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documents, batch = DocumentService.save_document_with_dataset_id(
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dataset=dataset,
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document_data=args,
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account=dataset.created_by_account,
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dataset_process_rule=dataset.latest_process_rule if 'process_rule' not in args else None,
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created_from='api'
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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document = documents[0]
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documents_and_batch_fields = {
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'document': marshal(document, document_fields),
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'batch': batch
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}
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return documents_and_batch_fields, 200
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class DocumentDeleteApi(DatasetApiResource):
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def delete(self, tenant_id, dataset_id, document_id):
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"""Delete document."""
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document_id = str(document_id)
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dataset_id = str(dataset_id)
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tenant_id = str(tenant_id)
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# get dataset info
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset:
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raise ValueError('Dataset is not exist.')
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document = DocumentService.get_document(dataset.id, document_id)
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@@ -126,8 +303,85 @@ class DocumentApi(DatasetApiResource):
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except services.errors.document.DocumentIndexingError:
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raise DocumentIndexingError('Cannot delete document during indexing.')
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return {'result': 'success'}, 204
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return {'result': 'success'}, 200
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api.add_resource(DocumentListApi, '/documents')
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api.add_resource(DocumentApi, '/documents/<uuid:document_id>')
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class DocumentListApi(DatasetApiResource):
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def get(self, tenant_id, dataset_id):
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dataset_id = str(dataset_id)
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tenant_id = str(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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search = request.args.get('keyword', default=None, type=str)
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset:
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raise NotFound('Dataset not found.')
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query = Document.query.filter_by(
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dataset_id=str(dataset_id), tenant_id=tenant_id)
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if search:
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search = f'%{search}%'
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query = query.filter(Document.name.like(search))
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query = query.order_by(desc(Document.created_at))
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paginated_documents = query.paginate(
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page=page, per_page=limit, max_per_page=100, error_out=False)
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documents = paginated_documents.items
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response = {
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'data': marshal(documents, document_fields),
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'has_more': len(documents) == limit,
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'limit': limit,
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'total': paginated_documents.total,
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'page': page
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}
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return response
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class DocumentIndexingStatusApi(DatasetApiResource):
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def get(self, tenant_id, dataset_id, batch):
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dataset_id = str(dataset_id)
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batch = str(batch)
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tenant_id = str(tenant_id)
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# get dataset
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dataset = db.session.query(Dataset).filter(
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Dataset.tenant_id == tenant_id,
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Dataset.id == dataset_id
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).first()
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if not dataset:
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raise NotFound('Dataset not found.')
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# get documents
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documents = DocumentService.get_batch_documents(dataset_id, batch)
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if not documents:
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raise NotFound('Documents not found.')
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documents_status = []
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for document in documents:
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completed_segments = DocumentSegment.query.filter(DocumentSegment.completed_at.isnot(None),
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DocumentSegment.document_id == str(document.id),
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DocumentSegment.status != 're_segment').count()
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total_segments = DocumentSegment.query.filter(DocumentSegment.document_id == str(document.id),
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DocumentSegment.status != 're_segment').count()
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document.completed_segments = completed_segments
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document.total_segments = total_segments
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if document.is_paused:
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document.indexing_status = 'paused'
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documents_status.append(marshal(document, document_status_fields))
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data = {
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'data': documents_status
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}
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return data
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api.add_resource(DocumentAddByTextApi, '/datasets/<uuid:dataset_id>/document/create_by_text')
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api.add_resource(DocumentAddByFileApi, '/datasets/<uuid:dataset_id>/document/create_by_file')
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api.add_resource(DocumentUpdateByTextApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/update_by_text')
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api.add_resource(DocumentUpdateByFileApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/update_by_file')
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api.add_resource(DocumentDeleteApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>')
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api.add_resource(DocumentListApi, '/datasets/<uuid:dataset_id>/documents')
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api.add_resource(DocumentIndexingStatusApi, '/datasets/<uuid:dataset_id>/documents/<string:batch>/indexing-status')
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