import os from functools import reduce from typing import Dict, List import uuid_utils.compat as uuid from celery_once import AlreadyQueued from django.db import transaction from django.db.models import QuerySet, Model from django.db.models.functions import Substr, Reverse from django.utils.translation import gettext_lazy as _ from rest_framework import serializers from common.db.search import native_search from common.event import ListenerManagement from common.exception.app_exception import AppApiException from common.utils.common import post, get_file_content from knowledge.models import Knowledge, Paragraph, Problem, Document, KnowledgeType, ProblemParagraphMapping, State, \ TaskType from knowledge.serializers.common import ProblemParagraphManage from knowledge.serializers.paragraph import ParagraphSerializers, ParagraphInstanceSerializer from knowledge.task import embedding_by_document from maxkb.const import PROJECT_DIR class DocumentInstanceSerializer(serializers.Serializer): name = serializers.CharField(required=True, label=_('document name'), max_length=128, min_length=1) paragraphs = ParagraphInstanceSerializer(required=False, many=True, allow_null=True) class DocumentCreateRequest(serializers.Serializer): name = serializers.CharField(required=True, label=_('knowledge name'), max_length=64, min_length=1) desc = serializers.CharField(required=True, label=_('knowledge description'), max_length=256, min_length=1) embedding_model_id = serializers.UUIDField(required=True, label=_('embedding model')) documents = DocumentInstanceSerializer(required=False, many=True) class DocumentSerializers(serializers.Serializer): class Operate(serializers.Serializer): document_id = serializers.UUIDField(required=True, label=_('document id')) knowledge_id = serializers.UUIDField(required=True, label=_('knowledge id')) def is_valid(self, *, raise_exception=False): super().is_valid(raise_exception=True) document_id = self.data.get('document_id') if not QuerySet(Document).filter(id=document_id).exists(): raise AppApiException(500, _('document id not exist')) def one(self, with_valid=False): if with_valid: self.is_valid(raise_exception=True) query_set = QuerySet(model=Document) query_set = query_set.filter(**{'id': self.data.get("document_id")}) return native_search({ 'document_custom_sql': query_set, 'order_by_query': QuerySet(Document).order_by('-create_time', 'id') }, select_string=get_file_content( os.path.join(PROJECT_DIR, "apps", "knowledge", 'sql', 'list_document.sql')), with_search_one=True) def refresh(self, state_list=None, with_valid=True): if state_list is None: state_list = [State.PENDING.value, State.STARTED.value, State.SUCCESS.value, State.FAILURE.value, State.REVOKE.value, State.REVOKED.value, State.IGNORED.value] if with_valid: self.is_valid(raise_exception=True) knowledge = QuerySet(Knowledge).filter(id=self.data.get('knowledge_id')).first() embedding_model_id = knowledge.embedding_model_id knowledge_user_id = knowledge.user_id embedding_model = QuerySet(Model).filter(id=embedding_model_id).first() if embedding_model is None: raise AppApiException(500, _('Model does not exist')) if embedding_model.permission_type == 'PRIVATE' and knowledge_user_id != embedding_model.user_id: raise AppApiException(500, _('No permission to use this model') + f"{embedding_model.name}") document_id = self.data.get("document_id") ListenerManagement.update_status(QuerySet(Document).filter(id=document_id), TaskType.EMBEDDING, State.PENDING) ListenerManagement.update_status(QuerySet(Paragraph).annotate( reversed_status=Reverse('status'), task_type_status=Substr('reversed_status', TaskType.EMBEDDING.value, 1), ).filter(task_type_status__in=state_list, document_id=document_id).values('id'), TaskType.EMBEDDING, State.PENDING) ListenerManagement.get_aggregation_document_status(document_id)() try: embedding_by_document.delay(document_id, embedding_model_id, state_list) except AlreadyQueued as e: raise AppApiException(500, _('The task is being executed, please do not send it repeatedly.')) class Create(serializers.Serializer): knowledge_id = serializers.UUIDField(required=True, label=_('document id')) def is_valid(self, *, raise_exception=False): super().is_valid(raise_exception=True) if not QuerySet(Knowledge).filter(id=self.data.get('knowledge_id')).exists(): raise AppApiException(10000, _('knowledge id not exist')) return True @staticmethod def post_embedding(result, document_id, knowledge_id): DocumentSerializers.Operate( data={'knowledge_id': knowledge_id, 'document_id': document_id}).refresh() return result @post(post_function=post_embedding) @transaction.atomic def save(self, instance: Dict, with_valid=False, **kwargs): if with_valid: DocumentCreateRequest(data=instance).is_valid(raise_exception=True) self.is_valid(raise_exception=True) knowledge_id = self.data.get('knowledge_id') document_paragraph_model = self.get_document_paragraph_model(knowledge_id, instance) document_model = document_paragraph_model.get('document') paragraph_model_list = document_paragraph_model.get('paragraph_model_list') problem_paragraph_object_list = document_paragraph_model.get('problem_paragraph_object_list') problem_model_list, problem_paragraph_mapping_list = ( ProblemParagraphManage(problem_paragraph_object_list, knowledge_id).to_problem_model_list()) # 插入文档 document_model.save() # 批量插入段落 QuerySet(Paragraph).bulk_create(paragraph_model_list) if len(paragraph_model_list) > 0 else None # 批量插入问题 QuerySet(Problem).bulk_create(problem_model_list) if len(problem_model_list) > 0 else None # 批量插入关联问题 QuerySet(ProblemParagraphMapping).bulk_create(problem_paragraph_mapping_list) if len( problem_paragraph_mapping_list) > 0 else None document_id = str(document_model.id) return (DocumentSerializers.Operate( data={'knowledge_id': knowledge_id, 'document_id': document_id} ).one(with_valid=True), document_id, knowledge_id) @staticmethod def get_paragraph_model(document_model, paragraph_list: List): knowledge_id = document_model.knowledge_id paragraph_model_dict_list = [ ParagraphSerializers.Create( data={ 'knowledge_id': knowledge_id, 'document_id': str(document_model.id) }).get_paragraph_problem_model(knowledge_id, document_model.id, paragraph) for paragraph in paragraph_list] paragraph_model_list = [] problem_paragraph_object_list = [] for paragraphs in paragraph_model_dict_list: paragraph = paragraphs.get('paragraph') for problem_model in paragraphs.get('problem_paragraph_object_list'): problem_paragraph_object_list.append(problem_model) paragraph_model_list.append(paragraph) return { 'document': document_model, 'paragraph_model_list': paragraph_model_list, 'problem_paragraph_object_list': problem_paragraph_object_list } @staticmethod def get_document_paragraph_model(knowledge_id, instance: Dict): document_model = Document( **{ 'knowledge_id': knowledge_id, 'id': uuid.uuid7(), 'name': instance.get('name'), 'char_length': reduce(lambda x, y: x + y, [len(p.get('content')) for p in instance.get('paragraphs', [])], 0), 'meta': instance.get('meta') if instance.get('meta') is not None else {}, 'type': instance.get('type') if instance.get('type') is not None else KnowledgeType.BASE }) return DocumentSerializers.Create.get_paragraph_model(document_model, instance.get('paragraphs') if 'paragraphs' in instance else [])