mirror of
https://github.com/langgenius/dify.git
synced 2024-11-16 19:59:50 +08:00
4588831bff
Co-authored-by: jyong <jyong@dify.ai>
900 lines
36 KiB
Python
900 lines
36 KiB
Python
# -*- coding:utf-8 -*-
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from datetime import datetime
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from typing import List
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from flask import request, current_app
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from flask_login import current_user
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from libs.login import login_required
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from flask_restful import Resource, fields, marshal, marshal_with, reqparse
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from sqlalchemy import desc, asc
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from werkzeug.exceptions import NotFound, Forbidden
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import services
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from controllers.console import api
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from controllers.console.app.error import ProviderNotInitializeError, ProviderQuotaExceededError, \
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ProviderModelCurrentlyNotSupportError
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from controllers.console.datasets.error import DocumentAlreadyFinishedError, InvalidActionError, DocumentIndexingError, \
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InvalidMetadataError, ArchivedDocumentImmutableError
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from controllers.console.setup import setup_required
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from controllers.console.wraps import account_initialization_required
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from core.indexing_runner import IndexingRunner
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from core.model_providers.error import ProviderTokenNotInitError, QuotaExceededError, ModelCurrentlyNotSupportError, \
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LLMBadRequestError
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from core.model_providers.model_factory import ModelFactory
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from extensions.ext_redis import redis_client
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from fields.document_fields import document_with_segments_fields, document_fields, \
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dataset_and_document_fields, document_status_fields
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from extensions.ext_database import db
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from models.dataset import DatasetProcessRule, Dataset
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from models.dataset import Document, DocumentSegment
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from models.model import UploadFile
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from services.dataset_service import DocumentService, DatasetService
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from tasks.add_document_to_index_task import add_document_to_index_task
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from tasks.remove_document_from_index_task import remove_document_from_index_task
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class DocumentResource(Resource):
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def get_document(self, dataset_id: str, document_id: str) -> Document:
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dataset = DatasetService.get_dataset(dataset_id)
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if not dataset:
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raise NotFound('Dataset not found.')
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try:
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DatasetService.check_dataset_permission(dataset, current_user)
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except services.errors.account.NoPermissionError as e:
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raise Forbidden(str(e))
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document = DocumentService.get_document(dataset_id, document_id)
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if not document:
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raise NotFound('Document not found.')
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if document.tenant_id != current_user.current_tenant_id:
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raise Forbidden('No permission.')
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return document
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def get_batch_documents(self, dataset_id: str, batch: str) -> List[Document]:
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dataset = DatasetService.get_dataset(dataset_id)
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if not dataset:
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raise NotFound('Dataset not found.')
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try:
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DatasetService.check_dataset_permission(dataset, current_user)
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except services.errors.account.NoPermissionError as e:
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raise Forbidden(str(e))
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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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return documents
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class GetProcessRuleApi(Resource):
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@setup_required
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@login_required
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@account_initialization_required
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def get(self):
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req_data = request.args
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document_id = req_data.get('document_id')
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# get default rules
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mode = DocumentService.DEFAULT_RULES['mode']
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rules = DocumentService.DEFAULT_RULES['rules']
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if document_id:
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# get the latest process rule
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document = Document.query.get_or_404(document_id)
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dataset = DatasetService.get_dataset(document.dataset_id)
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if not dataset:
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raise NotFound('Dataset not found.')
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try:
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DatasetService.check_dataset_permission(dataset, current_user)
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except services.errors.account.NoPermissionError as e:
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raise Forbidden(str(e))
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# get the latest process rule
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dataset_process_rule = db.session.query(DatasetProcessRule). \
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filter(DatasetProcessRule.dataset_id == document.dataset_id). \
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order_by(DatasetProcessRule.created_at.desc()). \
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limit(1). \
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one_or_none()
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if dataset_process_rule:
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mode = dataset_process_rule.mode
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rules = dataset_process_rule.rules_dict
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return {
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'mode': mode,
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'rules': rules
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}
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class DatasetDocumentListApi(Resource):
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@setup_required
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@login_required
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@account_initialization_required
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def get(self, dataset_id):
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dataset_id = str(dataset_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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sort = request.args.get('sort', default='-created_at', type=str)
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fetch = request.args.get('fetch', default=False, type=bool)
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dataset = DatasetService.get_dataset(dataset_id)
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if not dataset:
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raise NotFound('Dataset not found.')
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try:
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DatasetService.check_dataset_permission(dataset, current_user)
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except services.errors.account.NoPermissionError as e:
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raise Forbidden(str(e))
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query = Document.query.filter_by(
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dataset_id=str(dataset_id), tenant_id=current_user.current_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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if sort.startswith('-'):
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sort_logic = desc
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sort = sort[1:]
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else:
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sort_logic = asc
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if sort == 'hit_count':
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sub_query = db.select(DocumentSegment.document_id,
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db.func.sum(DocumentSegment.hit_count).label("total_hit_count")) \
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.group_by(DocumentSegment.document_id) \
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.subquery()
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query = query.outerjoin(sub_query, sub_query.c.document_id == Document.id) \
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.order_by(sort_logic(db.func.coalesce(sub_query.c.total_hit_count, 0)))
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elif sort == 'created_at':
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query = query.order_by(sort_logic(Document.created_at))
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else:
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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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if fetch:
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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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data = marshal(documents, document_with_segments_fields)
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else:
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data = marshal(documents, document_fields)
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response = {
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'data': data,
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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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documents_and_batch_fields = {
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'documents': fields.List(fields.Nested(document_fields)),
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'batch': fields.String
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}
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@setup_required
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@login_required
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@account_initialization_required
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@marshal_with(documents_and_batch_fields)
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def post(self, dataset_id):
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dataset_id = str(dataset_id)
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dataset = DatasetService.get_dataset(dataset_id)
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if not dataset:
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raise NotFound('Dataset not found.')
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# The role of the current user in the ta table must be admin or owner
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if current_user.current_tenant.current_role not in ['admin', 'owner']:
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raise Forbidden()
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try:
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DatasetService.check_dataset_permission(dataset, current_user)
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except services.errors.account.NoPermissionError as e:
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raise Forbidden(str(e))
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parser = reqparse.RequestParser()
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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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parser.add_argument('data_source', type=dict, required=False, location='json')
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parser.add_argument('process_rule', type=dict, required=False, location='json')
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parser.add_argument('duplicate', type=bool, nullable=False, 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('retrieval_model', type=dict, required=False, nullable=False,
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location='json')
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args = parser.parse_args()
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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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# 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(dataset, args, current_user)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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except QuotaExceededError:
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raise ProviderQuotaExceededError()
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except ModelCurrentlyNotSupportError:
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raise ProviderModelCurrentlyNotSupportError()
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return {
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'documents': documents,
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'batch': batch
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}
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class DatasetInitApi(Resource):
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@setup_required
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@login_required
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@account_initialization_required
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@marshal_with(dataset_and_document_fields)
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def post(self):
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# The role of the current user in the ta table must be admin or owner
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if current_user.current_tenant.current_role not in ['admin', 'owner']:
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raise Forbidden()
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parser = reqparse.RequestParser()
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parser.add_argument('indexing_technique', type=str, choices=Dataset.INDEXING_TECHNIQUE_LIST, required=True,
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nullable=False, location='json')
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parser.add_argument('data_source', type=dict, required=True, nullable=True, location='json')
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parser.add_argument('process_rule', type=dict, required=True, 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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parser.add_argument('retrieval_model', type=dict, required=False, nullable=False,
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location='json')
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args = parser.parse_args()
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if args['indexing_technique'] == 'high_quality':
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try:
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ModelFactory.get_embedding_model(
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tenant_id=current_user.current_tenant_id
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)
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except LLMBadRequestError:
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raise ProviderNotInitializeError(
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f"No Embedding Model available. Please configure a valid provider "
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f"in the Settings -> Model Provider.")
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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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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dataset, documents, batch = DocumentService.save_document_without_dataset_id(
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tenant_id=current_user.current_tenant_id,
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document_data=args,
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account=current_user
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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except QuotaExceededError:
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raise ProviderQuotaExceededError()
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except ModelCurrentlyNotSupportError:
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raise ProviderModelCurrentlyNotSupportError()
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response = {
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'dataset': dataset,
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'documents': documents,
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'batch': batch
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}
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return response
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class DocumentIndexingEstimateApi(DocumentResource):
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@setup_required
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@login_required
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@account_initialization_required
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def get(self, dataset_id, document_id):
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dataset_id = str(dataset_id)
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document_id = str(document_id)
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document = self.get_document(dataset_id, document_id)
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if document.indexing_status in ['completed', 'error']:
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raise DocumentAlreadyFinishedError()
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data_process_rule = document.dataset_process_rule
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data_process_rule_dict = data_process_rule.to_dict()
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response = {
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"tokens": 0,
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"total_price": 0,
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"currency": "USD",
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"total_segments": 0,
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"preview": []
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}
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if document.data_source_type == 'upload_file':
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data_source_info = document.data_source_info_dict
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if data_source_info and 'upload_file_id' in data_source_info:
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file_id = data_source_info['upload_file_id']
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file = db.session.query(UploadFile).filter(
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UploadFile.tenant_id == document.tenant_id,
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UploadFile.id == file_id
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).first()
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# raise error if file not found
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if not file:
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raise NotFound('File not found.')
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indexing_runner = IndexingRunner()
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try:
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response = indexing_runner.file_indexing_estimate(current_user.current_tenant_id, [file],
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data_process_rule_dict, None,
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'English', dataset_id)
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except LLMBadRequestError:
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raise ProviderNotInitializeError(
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f"No Embedding Model available. Please configure a valid provider "
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f"in the Settings -> Model Provider.")
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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return response
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class DocumentBatchIndexingEstimateApi(DocumentResource):
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@setup_required
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@login_required
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@account_initialization_required
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def get(self, dataset_id, batch):
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dataset_id = str(dataset_id)
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batch = str(batch)
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dataset = DatasetService.get_dataset(dataset_id)
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if dataset is None:
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raise NotFound("Dataset not found.")
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documents = self.get_batch_documents(dataset_id, batch)
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response = {
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"tokens": 0,
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"total_price": 0,
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"currency": "USD",
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"total_segments": 0,
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"preview": []
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}
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if not documents:
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return response
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data_process_rule = documents[0].dataset_process_rule
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data_process_rule_dict = data_process_rule.to_dict()
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info_list = []
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for document in documents:
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if document.indexing_status in ['completed', 'error']:
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raise DocumentAlreadyFinishedError()
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data_source_info = document.data_source_info_dict
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# format document files info
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if data_source_info and 'upload_file_id' in data_source_info:
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file_id = data_source_info['upload_file_id']
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info_list.append(file_id)
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# format document notion info
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elif data_source_info and 'notion_workspace_id' in data_source_info and 'notion_page_id' in data_source_info:
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pages = []
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page = {
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'page_id': data_source_info['notion_page_id'],
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'type': data_source_info['type']
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}
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pages.append(page)
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notion_info = {
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'workspace_id': data_source_info['notion_workspace_id'],
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'pages': pages
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}
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info_list.append(notion_info)
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if dataset.data_source_type == 'upload_file':
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file_details = db.session.query(UploadFile).filter(
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UploadFile.tenant_id == current_user.current_tenant_id,
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UploadFile.id in info_list
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).all()
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if file_details is None:
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raise NotFound("File not found.")
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indexing_runner = IndexingRunner()
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try:
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response = indexing_runner.file_indexing_estimate(current_user.current_tenant_id, file_details,
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data_process_rule_dict, None,
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'English', dataset_id)
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except LLMBadRequestError:
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raise ProviderNotInitializeError(
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f"No Embedding Model available. Please configure a valid provider "
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f"in the Settings -> Model Provider.")
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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elif dataset.data_source_type == 'notion_import':
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indexing_runner = IndexingRunner()
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try:
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response = indexing_runner.notion_indexing_estimate(current_user.current_tenant_id,
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info_list,
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data_process_rule_dict,
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None, 'English', dataset_id)
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except LLMBadRequestError:
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raise ProviderNotInitializeError(
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f"No Embedding Model available. Please configure a valid provider "
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f"in the Settings -> Model Provider.")
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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else:
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raise ValueError('Data source type not support')
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return response
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class DocumentBatchIndexingStatusApi(DocumentResource):
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@setup_required
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@login_required
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@account_initialization_required
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def get(self, dataset_id, batch):
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dataset_id = str(dataset_id)
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batch = str(batch)
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documents = self.get_batch_documents(dataset_id, batch)
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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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class DocumentIndexingStatusApi(DocumentResource):
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@setup_required
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@login_required
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@account_initialization_required
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def get(self, dataset_id, document_id):
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dataset_id = str(dataset_id)
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document_id = str(document_id)
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document = self.get_document(dataset_id, document_id)
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completed_segments = DocumentSegment.query \
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.filter(DocumentSegment.completed_at.isnot(None),
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DocumentSegment.document_id == str(document_id),
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DocumentSegment.status != 're_segment') \
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.count()
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total_segments = DocumentSegment.query \
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.filter(DocumentSegment.document_id == str(document_id),
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DocumentSegment.status != 're_segment') \
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.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:
|
|
document.indexing_status = 'paused'
|
|
return marshal(document, document_status_fields)
|
|
|
|
|
|
class DocumentDetailApi(DocumentResource):
|
|
METADATA_CHOICES = {'all', 'only', 'without'}
|
|
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def get(self, dataset_id, document_id):
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
document = self.get_document(dataset_id, document_id)
|
|
|
|
metadata = request.args.get('metadata', 'all')
|
|
if metadata not in self.METADATA_CHOICES:
|
|
raise InvalidMetadataError(f'Invalid metadata value: {metadata}')
|
|
|
|
if metadata == 'only':
|
|
response = {
|
|
'id': document.id,
|
|
'doc_type': document.doc_type,
|
|
'doc_metadata': document.doc_metadata
|
|
}
|
|
elif metadata == 'without':
|
|
process_rules = DatasetService.get_process_rules(dataset_id)
|
|
data_source_info = document.data_source_detail_dict
|
|
response = {
|
|
'id': document.id,
|
|
'position': document.position,
|
|
'data_source_type': document.data_source_type,
|
|
'data_source_info': data_source_info,
|
|
'dataset_process_rule_id': document.dataset_process_rule_id,
|
|
'dataset_process_rule': process_rules,
|
|
'name': document.name,
|
|
'created_from': document.created_from,
|
|
'created_by': document.created_by,
|
|
'created_at': document.created_at.timestamp(),
|
|
'tokens': document.tokens,
|
|
'indexing_status': document.indexing_status,
|
|
'completed_at': int(document.completed_at.timestamp()) if document.completed_at else None,
|
|
'updated_at': int(document.updated_at.timestamp()) if document.updated_at else None,
|
|
'indexing_latency': document.indexing_latency,
|
|
'error': document.error,
|
|
'enabled': document.enabled,
|
|
'disabled_at': int(document.disabled_at.timestamp()) if document.disabled_at else None,
|
|
'disabled_by': document.disabled_by,
|
|
'archived': document.archived,
|
|
'segment_count': document.segment_count,
|
|
'average_segment_length': document.average_segment_length,
|
|
'hit_count': document.hit_count,
|
|
'display_status': document.display_status,
|
|
'doc_form': document.doc_form
|
|
}
|
|
else:
|
|
process_rules = DatasetService.get_process_rules(dataset_id)
|
|
data_source_info = document.data_source_detail_dict_()
|
|
response = {
|
|
'id': document.id,
|
|
'position': document.position,
|
|
'data_source_type': document.data_source_type,
|
|
'data_source_info': data_source_info,
|
|
'dataset_process_rule_id': document.dataset_process_rule_id,
|
|
'dataset_process_rule': process_rules,
|
|
'name': document.name,
|
|
'created_from': document.created_from,
|
|
'created_by': document.created_by,
|
|
'created_at': document.created_at.timestamp(),
|
|
'tokens': document.tokens,
|
|
'indexing_status': document.indexing_status,
|
|
'completed_at': int(document.completed_at.timestamp()) if document.completed_at else None,
|
|
'updated_at': int(document.updated_at.timestamp()) if document.updated_at else None,
|
|
'indexing_latency': document.indexing_latency,
|
|
'error': document.error,
|
|
'enabled': document.enabled,
|
|
'disabled_at': int(document.disabled_at.timestamp()) if document.disabled_at else None,
|
|
'disabled_by': document.disabled_by,
|
|
'archived': document.archived,
|
|
'doc_type': document.doc_type,
|
|
'doc_metadata': document.doc_metadata,
|
|
'segment_count': document.segment_count,
|
|
'average_segment_length': document.average_segment_length,
|
|
'hit_count': document.hit_count,
|
|
'display_status': document.display_status,
|
|
'doc_form': document.doc_form
|
|
}
|
|
|
|
return response, 200
|
|
|
|
|
|
class DocumentProcessingApi(DocumentResource):
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def patch(self, dataset_id, document_id, action):
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
document = self.get_document(dataset_id, document_id)
|
|
|
|
# The role of the current user in the ta table must be admin or owner
|
|
if current_user.current_tenant.current_role not in ['admin', 'owner']:
|
|
raise Forbidden()
|
|
|
|
if action == "pause":
|
|
if document.indexing_status != "indexing":
|
|
raise InvalidActionError('Document not in indexing state.')
|
|
|
|
document.paused_by = current_user.id
|
|
document.paused_at = datetime.utcnow()
|
|
document.is_paused = True
|
|
db.session.commit()
|
|
|
|
elif action == "resume":
|
|
if document.indexing_status not in ["paused", "error"]:
|
|
raise InvalidActionError('Document not in paused or error state.')
|
|
|
|
document.paused_by = None
|
|
document.paused_at = None
|
|
document.is_paused = False
|
|
db.session.commit()
|
|
else:
|
|
raise InvalidActionError()
|
|
|
|
return {'result': 'success'}, 200
|
|
|
|
|
|
class DocumentDeleteApi(DocumentResource):
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def delete(self, dataset_id, document_id):
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
dataset = DatasetService.get_dataset(dataset_id)
|
|
if dataset is None:
|
|
raise NotFound("Dataset not found.")
|
|
# check user's model setting
|
|
DatasetService.check_dataset_model_setting(dataset)
|
|
|
|
document = self.get_document(dataset_id, document_id)
|
|
|
|
try:
|
|
DocumentService.delete_document(document)
|
|
except services.errors.document.DocumentIndexingError:
|
|
raise DocumentIndexingError('Cannot delete document during indexing.')
|
|
|
|
return {'result': 'success'}, 204
|
|
|
|
|
|
class DocumentMetadataApi(DocumentResource):
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def put(self, dataset_id, document_id):
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
document = self.get_document(dataset_id, document_id)
|
|
|
|
req_data = request.get_json()
|
|
|
|
doc_type = req_data.get('doc_type')
|
|
doc_metadata = req_data.get('doc_metadata')
|
|
|
|
# The role of the current user in the ta table must be admin or owner
|
|
if current_user.current_tenant.current_role not in ['admin', 'owner']:
|
|
raise Forbidden()
|
|
|
|
if doc_type is None or doc_metadata is None:
|
|
raise ValueError('Both doc_type and doc_metadata must be provided.')
|
|
|
|
if doc_type not in DocumentService.DOCUMENT_METADATA_SCHEMA:
|
|
raise ValueError('Invalid doc_type.')
|
|
|
|
if not isinstance(doc_metadata, dict):
|
|
raise ValueError('doc_metadata must be a dictionary.')
|
|
|
|
metadata_schema = DocumentService.DOCUMENT_METADATA_SCHEMA[doc_type]
|
|
|
|
document.doc_metadata = {}
|
|
if doc_type == 'others':
|
|
document.doc_metadata = doc_metadata
|
|
else:
|
|
for key, value_type in metadata_schema.items():
|
|
value = doc_metadata.get(key)
|
|
if value is not None and isinstance(value, value_type):
|
|
document.doc_metadata[key] = value
|
|
|
|
document.doc_type = doc_type
|
|
document.updated_at = datetime.utcnow()
|
|
db.session.commit()
|
|
|
|
return {'result': 'success', 'message': 'Document metadata updated.'}, 200
|
|
|
|
|
|
class DocumentStatusApi(DocumentResource):
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def patch(self, dataset_id, document_id, action):
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
dataset = DatasetService.get_dataset(dataset_id)
|
|
if dataset is None:
|
|
raise NotFound("Dataset not found.")
|
|
# check user's model setting
|
|
DatasetService.check_dataset_model_setting(dataset)
|
|
|
|
document = self.get_document(dataset_id, document_id)
|
|
|
|
# The role of the current user in the ta table must be admin or owner
|
|
if current_user.current_tenant.current_role not in ['admin', 'owner']:
|
|
raise Forbidden()
|
|
|
|
indexing_cache_key = 'document_{}_indexing'.format(document.id)
|
|
cache_result = redis_client.get(indexing_cache_key)
|
|
if cache_result is not None:
|
|
raise InvalidActionError("Document is being indexed, please try again later")
|
|
|
|
if action == "enable":
|
|
if document.enabled:
|
|
raise InvalidActionError('Document already enabled.')
|
|
|
|
document.enabled = True
|
|
document.disabled_at = None
|
|
document.disabled_by = None
|
|
document.updated_at = datetime.utcnow()
|
|
db.session.commit()
|
|
|
|
# Set cache to prevent indexing the same document multiple times
|
|
redis_client.setex(indexing_cache_key, 600, 1)
|
|
|
|
add_document_to_index_task.delay(document_id)
|
|
|
|
return {'result': 'success'}, 200
|
|
|
|
elif action == "disable":
|
|
if not document.completed_at or document.indexing_status != 'completed':
|
|
raise InvalidActionError('Document is not completed.')
|
|
if not document.enabled:
|
|
raise InvalidActionError('Document already disabled.')
|
|
|
|
document.enabled = False
|
|
document.disabled_at = datetime.utcnow()
|
|
document.disabled_by = current_user.id
|
|
document.updated_at = datetime.utcnow()
|
|
db.session.commit()
|
|
|
|
# Set cache to prevent indexing the same document multiple times
|
|
redis_client.setex(indexing_cache_key, 600, 1)
|
|
|
|
remove_document_from_index_task.delay(document_id)
|
|
|
|
return {'result': 'success'}, 200
|
|
|
|
elif action == "archive":
|
|
if document.archived:
|
|
raise InvalidActionError('Document already archived.')
|
|
|
|
document.archived = True
|
|
document.archived_at = datetime.utcnow()
|
|
document.archived_by = current_user.id
|
|
document.updated_at = datetime.utcnow()
|
|
db.session.commit()
|
|
|
|
if document.enabled:
|
|
# Set cache to prevent indexing the same document multiple times
|
|
redis_client.setex(indexing_cache_key, 600, 1)
|
|
|
|
remove_document_from_index_task.delay(document_id)
|
|
|
|
return {'result': 'success'}, 200
|
|
elif action == "un_archive":
|
|
if not document.archived:
|
|
raise InvalidActionError('Document is not archived.')
|
|
|
|
# check document limit
|
|
if current_app.config['EDITION'] == 'CLOUD':
|
|
documents_count = DocumentService.get_tenant_documents_count()
|
|
total_count = documents_count + 1
|
|
tenant_document_count = int(current_app.config['TENANT_DOCUMENT_COUNT'])
|
|
if total_count > tenant_document_count:
|
|
raise ValueError(f"All your documents have overed limit {tenant_document_count}.")
|
|
|
|
document.archived = False
|
|
document.archived_at = None
|
|
document.archived_by = None
|
|
document.updated_at = datetime.utcnow()
|
|
db.session.commit()
|
|
|
|
# Set cache to prevent indexing the same document multiple times
|
|
redis_client.setex(indexing_cache_key, 600, 1)
|
|
|
|
add_document_to_index_task.delay(document_id)
|
|
|
|
return {'result': 'success'}, 200
|
|
else:
|
|
raise InvalidActionError()
|
|
|
|
|
|
class DocumentPauseApi(DocumentResource):
|
|
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def patch(self, dataset_id, document_id):
|
|
"""pause document."""
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
|
|
dataset = DatasetService.get_dataset(dataset_id)
|
|
if not dataset:
|
|
raise NotFound('Dataset not found.')
|
|
|
|
document = DocumentService.get_document(dataset.id, document_id)
|
|
|
|
# 404 if document not found
|
|
if document is None:
|
|
raise NotFound("Document Not Exists.")
|
|
|
|
# 403 if document is archived
|
|
if DocumentService.check_archived(document):
|
|
raise ArchivedDocumentImmutableError()
|
|
|
|
try:
|
|
# pause document
|
|
DocumentService.pause_document(document)
|
|
except services.errors.document.DocumentIndexingError:
|
|
raise DocumentIndexingError('Cannot pause completed document.')
|
|
|
|
return {'result': 'success'}, 204
|
|
|
|
|
|
class DocumentRecoverApi(DocumentResource):
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def patch(self, dataset_id, document_id):
|
|
"""recover document."""
|
|
dataset_id = str(dataset_id)
|
|
document_id = str(document_id)
|
|
dataset = DatasetService.get_dataset(dataset_id)
|
|
if not dataset:
|
|
raise NotFound('Dataset not found.')
|
|
document = DocumentService.get_document(dataset.id, document_id)
|
|
|
|
# 404 if document not found
|
|
if document is None:
|
|
raise NotFound("Document Not Exists.")
|
|
|
|
# 403 if document is archived
|
|
if DocumentService.check_archived(document):
|
|
raise ArchivedDocumentImmutableError()
|
|
try:
|
|
# pause document
|
|
DocumentService.recover_document(document)
|
|
except services.errors.document.DocumentIndexingError:
|
|
raise DocumentIndexingError('Document is not in paused status.')
|
|
|
|
return {'result': 'success'}, 204
|
|
|
|
|
|
class DocumentLimitApi(DocumentResource):
|
|
@setup_required
|
|
@login_required
|
|
@account_initialization_required
|
|
def get(self):
|
|
"""get document limit"""
|
|
documents_count = DocumentService.get_tenant_documents_count()
|
|
tenant_document_count = int(current_app.config['TENANT_DOCUMENT_COUNT'])
|
|
|
|
return {
|
|
'documents_count': documents_count,
|
|
'documents_limit': tenant_document_count
|
|
}, 200
|
|
|
|
|
|
api.add_resource(GetProcessRuleApi, '/datasets/process-rule')
|
|
api.add_resource(DatasetDocumentListApi,
|
|
'/datasets/<uuid:dataset_id>/documents')
|
|
api.add_resource(DatasetInitApi,
|
|
'/datasets/init')
|
|
api.add_resource(DocumentIndexingEstimateApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/indexing-estimate')
|
|
api.add_resource(DocumentBatchIndexingEstimateApi,
|
|
'/datasets/<uuid:dataset_id>/batch/<string:batch>/indexing-estimate')
|
|
api.add_resource(DocumentBatchIndexingStatusApi,
|
|
'/datasets/<uuid:dataset_id>/batch/<string:batch>/indexing-status')
|
|
api.add_resource(DocumentIndexingStatusApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/indexing-status')
|
|
api.add_resource(DocumentDetailApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>')
|
|
api.add_resource(DocumentProcessingApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/processing/<string:action>')
|
|
api.add_resource(DocumentDeleteApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>')
|
|
api.add_resource(DocumentMetadataApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/metadata')
|
|
api.add_resource(DocumentStatusApi,
|
|
'/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/status/<string:action>')
|
|
api.add_resource(DocumentPauseApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/processing/pause')
|
|
api.add_resource(DocumentRecoverApi, '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/processing/resume')
|
|
api.add_resource(DocumentLimitApi, '/datasets/limit')
|