| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434 | # -*- coding:utf-8 -*-import uuidfrom datetime import datetimefrom flask import requestfrom flask_login import current_userfrom flask_restful import Resource, reqparse, marshalfrom werkzeug.exceptions import NotFound, Forbiddenimport servicesfrom controllers.console import apifrom controllers.console.app.error import ProviderNotInitializeErrorfrom controllers.console.datasets.error import InvalidActionError, NoFileUploadedError, TooManyFilesErrorfrom controllers.console.setup import setup_requiredfrom controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_checkfrom core.errors.error import LLMBadRequestError, ProviderTokenNotInitErrorfrom core.model_manager import ModelManagerfrom core.model_runtime.entities.model_entities import ModelTypefrom libs.login import login_requiredfrom extensions.ext_database import dbfrom extensions.ext_redis import redis_clientfrom fields.segment_fields import segment_fieldsfrom models.dataset import DocumentSegmentfrom services.dataset_service import DatasetService, DocumentService, SegmentServicefrom tasks.enable_segment_to_index_task import enable_segment_to_index_taskfrom tasks.disable_segment_from_index_task import disable_segment_from_index_taskfrom tasks.batch_create_segment_to_index_task import batch_create_segment_to_index_taskimport pandas as pdclass DatasetDocumentSegmentListApi(Resource):    @setup_required    @login_required    @account_initialization_required    def get(self, dataset_id, document_id):        dataset_id = str(dataset_id)        document_id = str(document_id)        dataset = DatasetService.get_dataset(dataset_id)        if not dataset:            raise NotFound('Dataset not found.')        try:            DatasetService.check_dataset_permission(dataset, current_user)        except services.errors.account.NoPermissionError as e:            raise Forbidden(str(e))        document = DocumentService.get_document(dataset_id, document_id)        if not document:            raise NotFound('Document not found.')        parser = reqparse.RequestParser()        parser.add_argument('last_id', type=str, default=None, location='args')        parser.add_argument('limit', type=int, default=20, location='args')        parser.add_argument('status', type=str,                            action='append', default=[], location='args')        parser.add_argument('hit_count_gte', type=int,                            default=None, location='args')        parser.add_argument('enabled', type=str, default='all', location='args')        parser.add_argument('keyword', type=str, default=None, location='args')        args = parser.parse_args()        last_id = args['last_id']        limit = min(args['limit'], 100)        status_list = args['status']        hit_count_gte = args['hit_count_gte']        keyword = args['keyword']        query = DocumentSegment.query.filter(            DocumentSegment.document_id == str(document_id),            DocumentSegment.tenant_id == current_user.current_tenant_id        )        if last_id is not None:            last_segment = DocumentSegment.query.get(str(last_id))            if last_segment:                query = query.filter(                    DocumentSegment.position > last_segment.position)            else:                return {'data': [], 'has_more': False, 'limit': limit}, 200        if status_list:            query = query.filter(DocumentSegment.status.in_(status_list))        if hit_count_gte is not None:            query = query.filter(DocumentSegment.hit_count >= hit_count_gte)        if keyword:            query = query.where(DocumentSegment.content.ilike(f'%{keyword}%'))        if args['enabled'].lower() != 'all':            if args['enabled'].lower() == 'true':                query = query.filter(DocumentSegment.enabled == True)            elif args['enabled'].lower() == 'false':                query = query.filter(DocumentSegment.enabled == False)        total = query.count()        segments = query.order_by(DocumentSegment.position).limit(limit + 1).all()        has_more = False        if len(segments) > limit:            has_more = True            segments = segments[:-1]        return {            'data': marshal(segments, segment_fields),            'doc_form': document.doc_form,            'has_more': has_more,            'limit': limit,            'total': total        }, 200class DatasetDocumentSegmentApi(Resource):    @setup_required    @login_required    @account_initialization_required    @cloud_edition_billing_resource_check('vector_space')    def patch(self, dataset_id, segment_id, action):        dataset_id = str(dataset_id)        dataset = DatasetService.get_dataset(dataset_id)        if not dataset:            raise NotFound('Dataset not found.')        # check user's model setting        DatasetService.check_dataset_model_setting(dataset)        # 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()        try:            DatasetService.check_dataset_permission(dataset, current_user)        except services.errors.account.NoPermissionError as e:            raise Forbidden(str(e))        if dataset.indexing_technique == 'high_quality':            # check embedding model setting            try:                model_manager = ModelManager()                model_manager.get_model_instance(                    tenant_id=current_user.current_tenant_id,                    provider=dataset.embedding_model_provider,                    model_type=ModelType.TEXT_EMBEDDING,                    model=dataset.embedding_model                )            except LLMBadRequestError:                raise ProviderNotInitializeError(                    f"No Embedding Model available. Please configure a valid provider "                    f"in the Settings -> Model Provider.")            except ProviderTokenNotInitError as ex:                raise ProviderNotInitializeError(ex.description)        segment = DocumentSegment.query.filter(            DocumentSegment.id == str(segment_id),            DocumentSegment.tenant_id == current_user.current_tenant_id        ).first()        if not segment:            raise NotFound('Segment not found.')        document_indexing_cache_key = 'document_{}_indexing'.format(segment.document_id)        cache_result = redis_client.get(document_indexing_cache_key)        if cache_result is not None:            raise InvalidActionError("Document is being indexed, please try again later")        indexing_cache_key = 'segment_{}_indexing'.format(segment.id)        cache_result = redis_client.get(indexing_cache_key)        if cache_result is not None:            raise InvalidActionError("Segment is being indexed, please try again later")        if action == "enable":            if segment.enabled:                raise InvalidActionError("Segment is already enabled.")            segment.enabled = True            segment.disabled_at = None            segment.disabled_by = None            db.session.commit()            # Set cache to prevent indexing the same segment multiple times            redis_client.setex(indexing_cache_key, 600, 1)            enable_segment_to_index_task.delay(segment.id)            return {'result': 'success'}, 200        elif action == "disable":            if not segment.enabled:                raise InvalidActionError("Segment is already disabled.")            segment.enabled = False            segment.disabled_at = datetime.utcnow()            segment.disabled_by = current_user.id            db.session.commit()            # Set cache to prevent indexing the same segment multiple times            redis_client.setex(indexing_cache_key, 600, 1)            disable_segment_from_index_task.delay(segment.id)            return {'result': 'success'}, 200        else:            raise InvalidActionError()class DatasetDocumentSegmentAddApi(Resource):    @setup_required    @login_required    @account_initialization_required    @cloud_edition_billing_resource_check('vector_space')    def post(self, dataset_id, document_id):        # check dataset        dataset_id = str(dataset_id)        dataset = DatasetService.get_dataset(dataset_id)        if not dataset:            raise NotFound('Dataset not found.')        # check document        document_id = str(document_id)        document = DocumentService.get_document(dataset_id, document_id)        if not document:            raise NotFound('Document not found.')        # 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()        # check embedding model setting        if dataset.indexing_technique == 'high_quality':            try:                model_manager = ModelManager()                model_manager.get_model_instance(                    tenant_id=current_user.current_tenant_id,                    provider=dataset.embedding_model_provider,                    model_type=ModelType.TEXT_EMBEDDING,                    model=dataset.embedding_model                )            except LLMBadRequestError:                raise ProviderNotInitializeError(                    f"No Embedding Model available. Please configure a valid provider "                    f"in the Settings -> Model Provider.")            except ProviderTokenNotInitError as ex:                raise ProviderNotInitializeError(ex.description)        try:            DatasetService.check_dataset_permission(dataset, current_user)        except services.errors.account.NoPermissionError as e:            raise Forbidden(str(e))        # validate args        parser = reqparse.RequestParser()        parser.add_argument('content', type=str, required=True, nullable=False, location='json')        parser.add_argument('answer', type=str, required=False, nullable=True, location='json')        parser.add_argument('keywords', type=list, required=False, nullable=True, location='json')        args = parser.parse_args()        SegmentService.segment_create_args_validate(args, document)        segment = SegmentService.create_segment(args, document, dataset)        return {            'data': marshal(segment, segment_fields),            'doc_form': document.doc_form        }, 200class DatasetDocumentSegmentUpdateApi(Resource):    @setup_required    @login_required    @account_initialization_required    @cloud_edition_billing_resource_check('vector_space')    def patch(self, dataset_id, document_id, segment_id):        # check dataset        dataset_id = str(dataset_id)        dataset = DatasetService.get_dataset(dataset_id)        if not dataset:            raise NotFound('Dataset not found.')        # check user's model setting        DatasetService.check_dataset_model_setting(dataset)        # check document        document_id = str(document_id)        document = DocumentService.get_document(dataset_id, document_id)        if not document:            raise NotFound('Document not found.')        if dataset.indexing_technique == 'high_quality':            # check embedding model setting            try:                model_manager = ModelManager()                model_manager.get_model_instance(                    tenant_id=current_user.current_tenant_id,                    provider=dataset.embedding_model_provider,                    model_type=ModelType.TEXT_EMBEDDING,                    model=dataset.embedding_model                )            except LLMBadRequestError:                raise ProviderNotInitializeError(                    f"No Embedding Model available. Please configure a valid provider "                    f"in the Settings -> Model Provider.")            except ProviderTokenNotInitError as ex:                raise ProviderNotInitializeError(ex.description)            # check segment        segment_id = str(segment_id)        segment = DocumentSegment.query.filter(            DocumentSegment.id == str(segment_id),            DocumentSegment.tenant_id == current_user.current_tenant_id        ).first()        if not segment:            raise NotFound('Segment not found.')        # 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()        try:            DatasetService.check_dataset_permission(dataset, current_user)        except services.errors.account.NoPermissionError as e:            raise Forbidden(str(e))        # validate args        parser = reqparse.RequestParser()        parser.add_argument('content', type=str, required=True, nullable=False, location='json')        parser.add_argument('answer', type=str, required=False, nullable=True, location='json')        parser.add_argument('keywords', type=list, required=False, nullable=True, location='json')        args = parser.parse_args()        SegmentService.segment_create_args_validate(args, document)        segment = SegmentService.update_segment(args, segment, document, dataset)        return {            'data': marshal(segment, segment_fields),            'doc_form': document.doc_form        }, 200    @setup_required    @login_required    @account_initialization_required    def delete(self, dataset_id, document_id, segment_id):        # check dataset        dataset_id = str(dataset_id)        dataset = DatasetService.get_dataset(dataset_id)        if not dataset:            raise NotFound('Dataset not found.')        # check user's model setting        DatasetService.check_dataset_model_setting(dataset)        # check document        document_id = str(document_id)        document = DocumentService.get_document(dataset_id, document_id)        if not document:            raise NotFound('Document not found.')        # check segment        segment_id = str(segment_id)        segment = DocumentSegment.query.filter(            DocumentSegment.id == str(segment_id),            DocumentSegment.tenant_id == current_user.current_tenant_id        ).first()        if not segment:            raise NotFound('Segment not found.')        # 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()        try:            DatasetService.check_dataset_permission(dataset, current_user)        except services.errors.account.NoPermissionError as e:            raise Forbidden(str(e))        SegmentService.delete_segment(segment, document, dataset)        return {'result': 'success'}, 200class DatasetDocumentSegmentBatchImportApi(Resource):    @setup_required    @login_required    @account_initialization_required    @cloud_edition_billing_resource_check('vector_space')    def post(self, dataset_id, document_id):        # check dataset        dataset_id = str(dataset_id)        dataset = DatasetService.get_dataset(dataset_id)        if not dataset:            raise NotFound('Dataset not found.')        # check document        document_id = str(document_id)        document = DocumentService.get_document(dataset_id, document_id)        if not document:            raise NotFound('Document not found.')        # get file from request        file = request.files['file']        # check file        if 'file' not in request.files:            raise NoFileUploadedError()        if len(request.files) > 1:            raise TooManyFilesError()        # check file type        if not file.filename.endswith('.csv'):            raise ValueError("Invalid file type. Only CSV files are allowed")        try:            # Skip the first row            df = pd.read_csv(file)            result = []            for index, row in df.iterrows():                if document.doc_form == 'qa_model':                    data = {'content': row[0], 'answer': row[1]}                else:                    data = {'content': row[0]}                result.append(data)            if len(result) == 0:                raise ValueError("The CSV file is empty.")            # async job            job_id = str(uuid.uuid4())            indexing_cache_key = 'segment_batch_import_{}'.format(str(job_id))            # send batch add segments task            redis_client.setnx(indexing_cache_key, 'waiting')            batch_create_segment_to_index_task.delay(str(job_id), result, dataset_id, document_id,                                                     current_user.current_tenant_id, current_user.id)        except Exception as e:            return {'error': str(e)}, 500        return {            'job_id': job_id,            'job_status': 'waiting'        }, 200    @setup_required    @login_required    @account_initialization_required    def get(self, job_id):        job_id = str(job_id)        indexing_cache_key = 'segment_batch_import_{}'.format(job_id)        cache_result = redis_client.get(indexing_cache_key)        if cache_result is None:            raise ValueError("The job is not exist.")        return {            'job_id': job_id,            'job_status': cache_result.decode()        }, 200api.add_resource(DatasetDocumentSegmentListApi,                 '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/segments')api.add_resource(DatasetDocumentSegmentApi,                 '/datasets/<uuid:dataset_id>/segments/<uuid:segment_id>/<string:action>')api.add_resource(DatasetDocumentSegmentAddApi,                 '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/segment')api.add_resource(DatasetDocumentSegmentUpdateApi,                 '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/segments/<uuid:segment_id>')api.add_resource(DatasetDocumentSegmentBatchImportApi,                 '/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/segments/batch_import',                 '/datasets/batch_import_status/<uuid:job_id>')
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