UnisKB/apps/dataset/serializers/document_serializers.py

# coding=utf-8
"""
    @project: maxkb
    @Author：虎
    @file： document_serializers.py
    @date：2023/9/22 13:43
    @desc:
"""
import logging
import os
import re
import traceback
import uuid
from functools import reduce
from typing import List, Dict

import xlwt
from celery_once import AlreadyQueued
from django.core import validators
from django.db import transaction
from django.db.models import QuerySet
from django.http import HttpResponse
from drf_yasg import openapi
from rest_framework import serializers
from xlwt import Utils

from common.db.search import native_search, native_page_search
from common.event.common import work_thread_pool
from common.exception.app_exception import AppApiException
from common.handle.impl.doc_split_handle import DocSplitHandle
from common.handle.impl.html_split_handle import HTMLSplitHandle
from common.handle.impl.pdf_split_handle import PdfSplitHandle
from common.handle.impl.qa.csv_parse_qa_handle import CsvParseQAHandle
from common.handle.impl.qa.xls_parse_qa_handle import XlsParseQAHandle
from common.handle.impl.qa.xlsx_parse_qa_handle import XlsxParseQAHandle
from common.handle.impl.table.csv_parse_table_handle import CsvSplitHandle
from common.handle.impl.table.xlsx_parse_table_handle import XlsxSplitHandle
from common.handle.impl.table.xls_parse_table_handle import XlsSplitHandle
from common.handle.impl.text_split_handle import TextSplitHandle
from common.mixins.api_mixin import ApiMixin
from common.util.common import post, flat_map
from common.util.field_message import ErrMessage
from common.util.file_util import get_file_content
from common.util.fork import Fork
from common.util.split_model import get_split_model
from dataset.models.data_set import DataSet, Document, Paragraph, Problem, Type, Status, ProblemParagraphMapping, Image
from dataset.serializers.common_serializers import BatchSerializer, MetaSerializer, ProblemParagraphManage, \
    get_embedding_model_id_by_dataset_id
from dataset.serializers.paragraph_serializers import ParagraphSerializers, ParagraphInstanceSerializer
from dataset.task import sync_web_document
from embedding.task.embedding import embedding_by_document, delete_embedding_by_document_list, \
    delete_embedding_by_document, update_embedding_dataset_id, delete_embedding_by_paragraph_ids, \
    embedding_by_document_list
from smartdoc.conf import PROJECT_DIR

parse_qa_handle_list = [XlsParseQAHandle(), CsvParseQAHandle(), XlsxParseQAHandle()]
parse_table_handle_list = [CsvSplitHandle(), XlsSplitHandle(), XlsxSplitHandle()]


class FileBufferHandle:
    buffer = None

    def get_buffer(self, file):
        if self.buffer is None:
            self.buffer = file.read()
        return self.buffer


class DocumentEditInstanceSerializer(ApiMixin, serializers.Serializer):
    meta = serializers.DictField(required=False)
    name = serializers.CharField(required=False, max_length=128, min_length=1,
                                 error_messages=ErrMessage.char(
                                     "文档名称"))
    hit_handling_method = serializers.CharField(required=False, validators=[
        validators.RegexValidator(regex=re.compile("^optimization|directly_return$"),
                                  message="类型只支持optimization|directly_return",
                                  code=500)
    ], error_messages=ErrMessage.char("命中处理方式"))

    directly_return_similarity = serializers.FloatField(required=False,
                                                        max_value=2,
                                                        min_value=0,
                                                        error_messages=ErrMessage.float(
                                                            "直接返回分数"))

    is_active = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean(
        "文档是否可用"))

    @staticmethod
    def get_meta_valid_map():
        dataset_meta_valid_map = {
            Type.base: MetaSerializer.BaseMeta,
            Type.web: MetaSerializer.WebMeta
        }
        return dataset_meta_valid_map

    def is_valid(self, *, document: Document = None):
        super().is_valid(raise_exception=True)
        if 'meta' in self.data and self.data.get('meta') is not None:
            dataset_meta_valid_map = self.get_meta_valid_map()
            valid_class = dataset_meta_valid_map.get(document.type)
            valid_class(data=self.data.get('meta')).is_valid(raise_exception=True)


class DocumentWebInstanceSerializer(ApiMixin, serializers.Serializer):
    source_url_list = serializers.ListField(required=True,
                                            child=serializers.CharField(required=True, error_messages=ErrMessage.char(
                                                "文档地址")),
                                            error_messages=ErrMessage.char(
                                                "文档地址列表"))
    selector = serializers.CharField(required=False, allow_null=True, allow_blank=True,
                                     error_messages=ErrMessage.char(
                                         "选择器"))

    @staticmethod
    def get_request_params_api():
        return [openapi.Parameter(name='file',
                                  in_=openapi.IN_FORM,
                                  type=openapi.TYPE_ARRAY,
                                  items=openapi.Items(type=openapi.TYPE_FILE),
                                  required=True,
                                  description='上传文件'),
                openapi.Parameter(name='dataset_id',
                                  in_=openapi.IN_PATH,
                                  type=openapi.TYPE_STRING,
                                  required=True,
                                  description='知识库id'),
                ]


class DocumentInstanceSerializer(ApiMixin, serializers.Serializer):
    name = serializers.CharField(required=True,
                                 error_messages=ErrMessage.char("文档名称"),
                                 max_length=128,
                                 min_length=1)

    paragraphs = ParagraphInstanceSerializer(required=False, many=True, allow_null=True)

    @staticmethod
    def get_request_body_api():
        return openapi.Schema(
            type=openapi.TYPE_OBJECT,
            required=['name', 'paragraphs'],
            properties={
                'name': openapi.Schema(type=openapi.TYPE_STRING, title="文档名称", description="文档名称"),
                'paragraphs': openapi.Schema(type=openapi.TYPE_ARRAY, title="段落列表", description="段落列表",
                                             items=ParagraphSerializers.Create.get_request_body_api())
            }
        )


class DocumentInstanceQASerializer(ApiMixin, serializers.Serializer):
    file_list = serializers.ListSerializer(required=True,
                                           error_messages=ErrMessage.list("文件列表"),
                                           child=serializers.FileField(required=True,
                                                                       error_messages=ErrMessage.file("文件")))


class DocumentInstanceTableSerializer(ApiMixin, serializers.Serializer):
    file_list = serializers.ListSerializer(required=True,
                                           error_messages=ErrMessage.list("文件列表"),
                                           child=serializers.FileField(required=True,
                                                                       error_messages=ErrMessage.file("文件")))


class DocumentSerializers(ApiMixin, serializers.Serializer):
    class Export(ApiMixin, serializers.Serializer):
        type = serializers.CharField(required=True, validators=[
            validators.RegexValidator(regex=re.compile("^csv|excel$"),
                                      message="模版类型只支持excel|csv",
                                      code=500)
        ], error_messages=ErrMessage.char("模版类型"))

        @staticmethod
        def get_request_params_api():
            return [openapi.Parameter(name='type',
                                      in_=openapi.IN_QUERY,
                                      type=openapi.TYPE_STRING,
                                      required=True,
                                      description='导出模板类型csv|excel'),

                    ]

        def export(self, with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)

            if self.data.get('type') == 'csv':
                file = open(os.path.join(PROJECT_DIR, "apps", "dataset", 'template', 'csv_template.csv'), "rb")
                content = file.read()
                file.close()
                return HttpResponse(content, status=200, headers={'Content-Type': 'text/cxv',
                                                                  'Content-Disposition': 'attachment; filename="csv_template.csv"'})
            elif self.data.get('type') == 'excel':
                file = open(os.path.join(PROJECT_DIR, "apps", "dataset", 'template', 'excel_template.xlsx'), "rb")
                content = file.read()
                file.close()
                return HttpResponse(content, status=200, headers={'Content-Type': 'application/vnd.ms-excel',
                                                                  'Content-Disposition': 'attachment; filename="excel_template.xlsx"'})

        def table_export(self, with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)

            if self.data.get('type') == 'csv':
                file = open(os.path.join(PROJECT_DIR, "apps", "dataset", 'template', 'MaxKB表格模板.csv'), "rb")
                content = file.read()
                file.close()
                return HttpResponse(content, status=200, headers={'Content-Type': 'text/cxv',
                                                                  'Content-Disposition': 'attachment; filename="csv_template.csv"'})
            elif self.data.get('type') == 'excel':
                file = open(os.path.join(PROJECT_DIR, "apps", "dataset", 'template', 'MaxKB表格模板.xlsx'), "rb")
                content = file.read()
                file.close()
                return HttpResponse(content, status=200, headers={'Content-Type': 'application/vnd.ms-excel',
                                                                  'Content-Disposition': 'attachment; filename="excel_template.xlsx"'})

    class Migrate(ApiMixin, serializers.Serializer):
        dataset_id = serializers.UUIDField(required=True,
                                           error_messages=ErrMessage.char(
                                               "知识库id"))
        target_dataset_id = serializers.UUIDField(required=True,
                                                  error_messages=ErrMessage.char(
                                                      "目标知识库id"))
        document_id_list = serializers.ListField(required=True, error_messages=ErrMessage.char("文档列表"),
                                                 child=serializers.UUIDField(required=True,
                                                                             error_messages=ErrMessage.uuid("文档id")))

        @transaction.atomic
        def migrate(self, with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)
            dataset_id = self.data.get('dataset_id')
            target_dataset_id = self.data.get('target_dataset_id')
            dataset = QuerySet(DataSet).filter(id=dataset_id).first()
            target_dataset = QuerySet(DataSet).filter(id=target_dataset_id).first()
            document_id_list = self.data.get('document_id_list')
            document_list = QuerySet(Document).filter(dataset_id=dataset_id, id__in=document_id_list)
            paragraph_list = QuerySet(Paragraph).filter(dataset_id=dataset_id, document_id__in=document_id_list)

            problem_paragraph_mapping_list = QuerySet(ProblemParagraphMapping).filter(paragraph__in=paragraph_list)
            problem_list = QuerySet(Problem).filter(
                id__in=[problem_paragraph_mapping.problem_id for problem_paragraph_mapping in
                        problem_paragraph_mapping_list])
            target_problem_list = list(
                QuerySet(Problem).filter(content__in=[problem.content for problem in problem_list],
                                         dataset_id=target_dataset_id))
            target_handle_problem_list = [
                self.get_target_dataset_problem(target_dataset_id, problem_paragraph_mapping,
                                                problem_list, target_problem_list) for
                problem_paragraph_mapping
                in
                problem_paragraph_mapping_list]

            create_problem_list = [problem for problem, is_create in target_handle_problem_list if
                                   is_create is not None and is_create]
            # 插入问题
            QuerySet(Problem).bulk_create(create_problem_list)
            # 修改mapping
            QuerySet(ProblemParagraphMapping).bulk_update(problem_paragraph_mapping_list, ['problem_id', 'dataset_id'])
            # 修改文档
            if dataset.type == Type.base.value and target_dataset.type == Type.web.value:
                document_list.update(dataset_id=target_dataset_id, type=Type.web,
                                     meta={'source_url': '', 'selector': ''})
            elif target_dataset.type == Type.base.value and dataset.type == Type.web.value:
                document_list.update(dataset_id=target_dataset_id, type=Type.base,
                                     meta={})
            else:
                document_list.update(dataset_id=target_dataset_id)
            model_id = None
            if dataset.embedding_mode_id != target_dataset.embedding_mode_id:
                model_id = get_embedding_model_id_by_dataset_id(target_dataset_id)

            pid_list = [paragraph.id for paragraph in paragraph_list]
            # 修改段落信息
            paragraph_list.update(dataset_id=target_dataset_id)
            # 修改向量信息
            if model_id:
                delete_embedding_by_paragraph_ids(pid_list)
                QuerySet(Document).filter(id__in=document_id_list).update(status=Status.queue_up)
                embedding_by_document_list.delay(document_id_list, model_id)
            else:
                update_embedding_dataset_id(pid_list, target_dataset_id)

        @staticmethod
        def get_target_dataset_problem(target_dataset_id: str,
                                       problem_paragraph_mapping,
                                       source_problem_list,
                                       target_problem_list):
            source_problem_list = [source_problem for source_problem in source_problem_list if
                                   source_problem.id == problem_paragraph_mapping.problem_id]
            problem_paragraph_mapping.dataset_id = target_dataset_id
            if len(source_problem_list) > 0:
                problem_content = source_problem_list[-1].content
                problem_list = [problem for problem in target_problem_list if problem.content == problem_content]
                if len(problem_list) > 0:
                    problem = problem_list[-1]
                    problem_paragraph_mapping.problem_id = problem.id
                    return problem, False
                else:
                    problem = Problem(id=uuid.uuid1(), dataset_id=target_dataset_id, content=problem_content)
                    target_problem_list.append(problem)
                    problem_paragraph_mapping.problem_id = problem.id
                    return problem, True
            return None

        @staticmethod
        def get_request_params_api():
            return [openapi.Parameter(name='dataset_id',
                                      in_=openapi.IN_PATH,
                                      type=openapi.TYPE_STRING,
                                      required=True,
                                      description='知识库id'),
                    openapi.Parameter(name='target_dataset_id',
                                      in_=openapi.IN_PATH,
                                      type=openapi.TYPE_STRING,
                                      required=True,
                                      description='目标知识库id')
                    ]

        @staticmethod
        def get_request_body_api():
            return openapi.Schema(
                type=openapi.TYPE_ARRAY,
                items=openapi.Schema(type=openapi.TYPE_STRING),
                title='文档id列表',
                description="文档id列表"
            )

    class Query(ApiMixin, serializers.Serializer):
        # 知识库id
        dataset_id = serializers.UUIDField(required=True,
                                           error_messages=ErrMessage.char(
                                               "知识库id"))

        name = serializers.CharField(required=False, max_length=128,
                                     min_length=1,
                                     error_messages=ErrMessage.char(
                                         "文档名称"))
        hit_handling_method = serializers.CharField(required=False, error_messages=ErrMessage.char("命中处理方式"))
        is_active = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean("文档是否可用"))
        status = serializers.CharField(required=False, error_messages=ErrMessage.char("文档状态"))

        def get_query_set(self):
            query_set = QuerySet(model=Document)
            query_set = query_set.filter(**{'dataset_id': self.data.get("dataset_id")})
            if 'name' in self.data and self.data.get('name') is not None:
                query_set = query_set.filter(**{'name__icontains': self.data.get('name')})
            if 'hit_handling_method' in self.data and self.data.get('hit_handling_method') is not None:
                query_set = query_set.filter(**{'hit_handling_method': self.data.get('hit_handling_method')})
            if 'is_active' in self.data and self.data.get('is_active') is not None:
                query_set = query_set.filter(**{'is_active': self.data.get('is_active')})
            if 'status' in self.data and self.data.get('status') is not None:
                query_set = query_set.filter(**{'status': self.data.get('status')})
            query_set = query_set.order_by('-create_time')
            return query_set

        def list(self, with_valid=False):
            if with_valid:
                self.is_valid(raise_exception=True)
            query_set = self.get_query_set()
            return native_search(query_set, select_string=get_file_content(
                os.path.join(PROJECT_DIR, "apps", "dataset", 'sql', 'list_document.sql')))

        def page(self, current_page, page_size):
            query_set = self.get_query_set()
            return native_page_search(current_page, page_size, query_set, select_string=get_file_content(
                os.path.join(PROJECT_DIR, "apps", "dataset", 'sql', 'list_document.sql')))

        @staticmethod
        def get_request_params_api():
            return [openapi.Parameter(name='name',
                                      in_=openapi.IN_QUERY,
                                      type=openapi.TYPE_STRING,
                                      required=False,
                                      description='文档名称'),
                    openapi.Parameter(name='hit_handling_method', in_=openapi.IN_QUERY,
                                      type=openapi.TYPE_STRING,
                                      required=False,
                                      description='文档命中处理方式')]

        @staticmethod
        def get_response_body_api():
            return openapi.Schema(type=openapi.TYPE_ARRAY,
                                  title="文档列表", description="文档列表",
                                  items=DocumentSerializers.Operate.get_response_body_api())

    class Sync(ApiMixin, serializers.Serializer):
        document_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char(
            "文档id"))

        def is_valid(self, *, raise_exception=False):
            super().is_valid(raise_exception=True)
            document_id = self.data.get('document_id')
            first = QuerySet(Document).filter(id=document_id).first()
            if first is None:
                raise AppApiException(500, "文档id不存在")
            if first.type != Type.web:
                raise AppApiException(500, "只有web站点类型才支持同步")

        def sync(self, with_valid=True, with_embedding=True):
            if with_valid:
                self.is_valid(raise_exception=True)
            document_id = self.data.get('document_id')
            document = QuerySet(Document).filter(id=document_id).first()
            if document.type != Type.web:
                return True
            try:
                document.status = Status.queue_up
                document.save()
                source_url = document.meta.get('source_url')
                selector_list = document.meta.get('selector').split(
                    " ") if 'selector' in document.meta and document.meta.get('selector') is not None else []
                result = Fork(source_url, selector_list).fork()
                if result.status == 200:
                    # 删除段落
                    QuerySet(model=Paragraph).filter(document_id=document_id).delete()
                    # 删除问题
                    QuerySet(model=ProblemParagraphMapping).filter(document_id=document_id).delete()
                    # 删除向量库
                    delete_embedding_by_document(document_id)
                    paragraphs = get_split_model('web.md').parse(result.content)
                    document.char_length = reduce(lambda x, y: x + y,
                                                  [len(p.get('content')) for p in paragraphs],
                                                  0)
                    document.save()
                    document_paragraph_model = DocumentSerializers.Create.get_paragraph_model(document, paragraphs)

                    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, document.dataset_id).to_problem_model_list()
                    # 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
                    # 插入关联问题
                    QuerySet(ProblemParagraphMapping).bulk_create(problem_paragraph_mapping_list) if len(
                        problem_paragraph_mapping_list) > 0 else None
                    # 向量化
                    if with_embedding:
                        embedding_model_id = get_embedding_model_id_by_dataset_id(document.dataset_id)
                        embedding_by_document.delay(document_id, embedding_model_id)
                else:
                    document.status = Status.error
                    document.save()
            except Exception as e:
                logging.getLogger("max_kb_error").error(f'{str(e)}:{traceback.format_exc()}')
                document.status = Status.error
                document.save()
            return True

    class Operate(ApiMixin, serializers.Serializer):
        document_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char(
            "文档id"))
        dataset_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char("数据集id"))

        @staticmethod
        def get_request_params_api():
            return [openapi.Parameter(name='dataset_id',
                                      in_=openapi.IN_PATH,
                                      type=openapi.TYPE_STRING,
                                      required=True,
                                      description='知识库id'),
                    openapi.Parameter(name='document_id',
                                      in_=openapi.IN_PATH,
                                      type=openapi.TYPE_STRING,
                                      required=True,
                                      description='文档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, "文档id不存在")

        def export(self, with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)
            document = QuerySet(Document).filter(id=self.data.get("document_id")).first()
            paragraph_list = native_search(QuerySet(Paragraph).filter(document_id=self.data.get("document_id")),
                                           get_file_content(
                                               os.path.join(PROJECT_DIR, "apps", "dataset", 'sql',
                                                            'list_paragraph_document_name.sql')))
            problem_mapping_list = native_search(
                QuerySet(ProblemParagraphMapping).filter(document_id=self.data.get("document_id")), get_file_content(
                    os.path.join(PROJECT_DIR, "apps", "dataset", 'sql', 'list_problem_mapping.sql')),
                with_table_name=True)
            data_dict, document_dict = self.merge_problem(paragraph_list, problem_mapping_list, [document])
            workbook = self.get_workbook(data_dict, document_dict)
            response = HttpResponse(content_type='application/vnd.ms-excel')
            response['Content-Disposition'] = f'attachment; filename="data.xls"'
            workbook.save(response)
            return response

        @staticmethod
        def get_workbook(data_dict, document_dict):
            # 创建工作簿对象
            workbook = xlwt.Workbook(encoding='utf-8')
            for sheet_id in data_dict:
                # 添加工作表
                worksheet = workbook.add_sheet(document_dict.get(sheet_id))
                data = [
                    ['分段标题（选填）', '分段内容（必填，问题答案，最长不超过4096个字符）', '问题（选填，单元格内一行一个）'],
                    *data_dict.get(sheet_id)
                ]
                # 写入数据到工作表
                for row_idx, row in enumerate(data):
                    for col_idx, col in enumerate(row):
                        worksheet.write(row_idx, col_idx, col)
                    # 创建HttpResponse对象返回Excel文件
            return workbook

        @staticmethod
        def merge_problem(paragraph_list: List[Dict], problem_mapping_list: List[Dict], document_list):
            result = {}
            document_dict = {}

            for paragraph in paragraph_list:
                problem_list = [problem_mapping.get('content') for problem_mapping in problem_mapping_list if
                                problem_mapping.get('paragraph_id') == paragraph.get('id')]
                document_sheet = result.get(paragraph.get('document_id'))
                document_name = DocumentSerializers.Operate.reset_document_name(paragraph.get('document_name'))
                d = document_dict.get(document_name)
                if d is None:
                    document_dict[document_name] = {paragraph.get('document_id')}
                else:
                    d.add(paragraph.get('document_id'))

                if document_sheet is None:
                    result[paragraph.get('document_id')] = [[paragraph.get('title'), paragraph.get('content'),
                                                             '\n'.join(problem_list)]]
                else:
                    document_sheet.append([paragraph.get('title'), paragraph.get('content'), '\n'.join(problem_list)])
            for document in document_list:
                if document.id not in result:
                    document_name = DocumentSerializers.Operate.reset_document_name(document.name)
                    result[document.id] = [[]]
                    d = document_dict.get(document_name)
                    if d is None:
                        document_dict[document_name] = {document.id}
                    else:
                        d.add(document.id)
            result_document_dict = {}
            for d_name in document_dict:
                for index, d_id in enumerate(document_dict.get(d_name)):
                    result_document_dict[d_id] = d_name if index == 0 else d_name + str(index)
            return result, result_document_dict

        @staticmethod
        def reset_document_name(document_name):
            if document_name is None or not Utils.valid_sheet_name(document_name):
                return "Sheet"
            return document_name.strip()

        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(query_set, select_string=get_file_content(
                os.path.join(PROJECT_DIR, "apps", "dataset", 'sql', 'list_document.sql')), with_search_one=True)

        def edit(self, instance: Dict, with_valid=False):
            if with_valid:
                self.is_valid(raise_exception=True)
            _document = QuerySet(Document).get(id=self.data.get("document_id"))
            if with_valid:
                DocumentEditInstanceSerializer(data=instance).is_valid(document=_document)
            update_keys = ['name', 'is_active', 'hit_handling_method', 'directly_return_similarity', 'meta']
            for update_key in update_keys:
                if update_key in instance and instance.get(update_key) is not None:
                    _document.__setattr__(update_key, instance.get(update_key))
            _document.save()
            return self.one()

        def refresh(self, with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)
            document_id = self.data.get("document_id")
            QuerySet(Document).filter(id=document_id).update(**{'status': Status.queue_up})
            QuerySet(Paragraph).filter(document_id=document_id).update(**{'status': Status.queue_up})
            embedding_model_id = get_embedding_model_id_by_dataset_id(dataset_id=self.data.get('dataset_id'))
            try:
                embedding_by_document.delay(document_id, embedding_model_id)
            except AlreadyQueued as e:
                raise AppApiException(500, "任务正在执行中,请勿重复下发")

        @transaction.atomic
        def delete(self):
            document_id = self.data.get("document_id")
            QuerySet(model=Document).filter(id=document_id).delete()
            # 删除段落
            QuerySet(model=Paragraph).filter(document_id=document_id).delete()
            # 删除问题
            QuerySet(model=ProblemParagraphMapping).filter(document_id=document_id).delete()
            # 删除向量库
            delete_embedding_by_document(document_id)
            return True

        @staticmethod
        def get_response_body_api():
            return openapi.Schema(
                type=openapi.TYPE_OBJECT,
                required=['id', 'name', 'char_length', 'user_id', 'paragraph_count', 'is_active'
                                                                                     'update_time', 'create_time'],
                properties={
                    'id': openapi.Schema(type=openapi.TYPE_STRING, title="id",
                                         description="id", default="xx"),
                    'name': openapi.Schema(type=openapi.TYPE_STRING, title="名称",
                                           description="名称", default="测试知识库"),
                    'char_length': openapi.Schema(type=openapi.TYPE_INTEGER, title="字符数",
                                                  description="字符数", default=10),
                    'user_id': openapi.Schema(type=openapi.TYPE_STRING, title="用户id", description="用户id"),
                    'paragraph_count': openapi.Schema(type=openapi.TYPE_INTEGER, title="文档数量",
                                                      description="文档数量", default=1),
                    'is_active': openapi.Schema(type=openapi.TYPE_BOOLEAN, title="是否可用",
                                                description="是否可用", default=True),
                    'update_time': openapi.Schema(type=openapi.TYPE_STRING, title="修改时间",
                                                  description="修改时间",
                                                  default="1970-01-01 00:00:00"),
                    'create_time': openapi.Schema(type=openapi.TYPE_STRING, title="创建时间",
                                                  description="创建时间",
                                                  default="1970-01-01 00:00:00"
                                                  )
                }
            )

        @staticmethod
        def get_request_body_api():
            return openapi.Schema(
                type=openapi.TYPE_OBJECT,
                properties={
                    'name': openapi.Schema(type=openapi.TYPE_STRING, title="文档名称", description="文档名称"),
                    'is_active': openapi.Schema(type=openapi.TYPE_BOOLEAN, title="是否可用", description="是否可用"),
                    'hit_handling_method': openapi.Schema(type=openapi.TYPE_STRING, title="命中处理方式",
                                                          description="ai优化:optimization,直接返回:directly_return"),
                    'directly_return_similarity': openapi.Schema(type=openapi.TYPE_NUMBER, title="直接返回分数",
                                                                 default=0.9),
                    'meta': openapi.Schema(type=openapi.TYPE_OBJECT, title="文档元数据",
                                           description="文档元数据->web:{source_url:xxx,selector:'xxx'},base:{}"),
                }
            )

    class Create(ApiMixin, serializers.Serializer):
        dataset_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char(
            "文档id"))

        def is_valid(self, *, raise_exception=False):
            super().is_valid(raise_exception=True)
            if not QuerySet(DataSet).filter(id=self.data.get('dataset_id')).exists():
                raise AppApiException(10000, "知识库id不存在")
            return True

        @staticmethod
        def post_embedding(result, document_id, dataset_id):
            model_id = get_embedding_model_id_by_dataset_id(dataset_id)
            embedding_by_document.delay(document_id, model_id)
            return result

        @staticmethod
        def parse_qa_file(file):
            get_buffer = FileBufferHandle().get_buffer
            for parse_qa_handle in parse_qa_handle_list:
                if parse_qa_handle.support(file, get_buffer):
                    return parse_qa_handle.handle(file, get_buffer, save_image)
            raise AppApiException(500, '不支持的文件格式')

        @staticmethod
        def parse_table_file(file):
            get_buffer = FileBufferHandle().get_buffer
            for parse_table_handle in parse_table_handle_list:
                if parse_table_handle.support(file, get_buffer):
                    return parse_table_handle.handle(file, get_buffer, save_image)
            raise AppApiException(500, '不支持的文件格式')

        def save_qa(self, instance: Dict, with_valid=True):
            if with_valid:
                DocumentInstanceQASerializer(data=instance).is_valid(raise_exception=True)
                self.is_valid(raise_exception=True)
            file_list = instance.get('file_list')
            document_list = flat_map([self.parse_qa_file(file) for file in file_list])
            return DocumentSerializers.Batch(data={'dataset_id': self.data.get('dataset_id')}).batch_save(document_list)

        def save_table(self, instance: Dict, with_valid=True):
            if with_valid:
                DocumentInstanceTableSerializer(data=instance).is_valid(raise_exception=True)
                self.is_valid(raise_exception=True)
            file_list = instance.get('file_list')
            document_list = flat_map([self.parse_table_file(file) for file in file_list])
            return DocumentSerializers.Batch(data={'dataset_id': self.data.get('dataset_id')}).batch_save(document_list)

        @post(post_function=post_embedding)
        @transaction.atomic
        def save(self, instance: Dict, with_valid=False, **kwargs):
            if with_valid:
                DocumentInstanceSerializer(data=instance).is_valid(raise_exception=True)
                self.is_valid(raise_exception=True)
            dataset_id = self.data.get('dataset_id')
            document_paragraph_model = self.get_document_paragraph_model(dataset_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,
                                                                                         dataset_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={'dataset_id': dataset_id, 'document_id': document_id}).one(
                with_valid=True), document_id, dataset_id

        def save_web(self, instance: Dict, with_valid=True):
            if with_valid:
                DocumentWebInstanceSerializer(data=instance).is_valid(raise_exception=True)
                self.is_valid(raise_exception=True)
            dataset_id = self.data.get('dataset_id')
            source_url_list = instance.get('source_url_list')
            selector = instance.get('selector')
            sync_web_document.delay(dataset_id, source_url_list, selector)

        @staticmethod
        def get_paragraph_model(document_model, paragraph_list: List):
            dataset_id = document_model.dataset_id
            paragraph_model_dict_list = [ParagraphSerializers.Create(
                data={'dataset_id': dataset_id, 'document_id': str(document_model.id)}).get_paragraph_problem_model(
                dataset_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(dataset_id, instance: Dict):
            document_model = Document(
                **{'dataset_id': dataset_id,
                   'id': uuid.uuid1(),
                   '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 Type.base})

            return DocumentSerializers.Create.get_paragraph_model(document_model,
                                                                  instance.get('paragraphs') if
                                                                  'paragraphs' in instance else [])

        @staticmethod
        def get_request_body_api():
            return DocumentInstanceSerializer.get_request_body_api()

        @staticmethod
        def get_request_params_api():
            return [openapi.Parameter(name='dataset_id',
                                      in_=openapi.IN_PATH,
                                      type=openapi.TYPE_STRING,
                                      required=True,
                                      description='知识库id')
                    ]

    class Split(ApiMixin, serializers.Serializer):
        file = serializers.ListField(required=True, error_messages=ErrMessage.list(
            "文件列表"))

        limit = serializers.IntegerField(required=False, error_messages=ErrMessage.integer(
            "分段长度"))

        patterns = serializers.ListField(required=False,
                                         child=serializers.CharField(required=True, error_messages=ErrMessage.char(
                                             "分段标识")),
                                         error_messages=ErrMessage.uuid(
                                             "分段标识列表"))

        with_filter = serializers.BooleanField(required=False, error_messages=ErrMessage.boolean(
            "自动清洗"))

        def is_valid(self, *, raise_exception=True):
            super().is_valid(raise_exception=True)
            files = self.data.get('file')
            for f in files:
                if f.size > 1024 * 1024 * 100:
                    raise AppApiException(500, "上传文件最大不能超过100MB")

        @staticmethod
        def get_request_params_api():
            return [
                openapi.Parameter(name='file',
                                  in_=openapi.IN_FORM,
                                  type=openapi.TYPE_ARRAY,
                                  items=openapi.Items(type=openapi.TYPE_FILE),
                                  required=True,
                                  description='上传文件'),
                openapi.Parameter(name='limit',
                                  in_=openapi.IN_FORM,
                                  required=False,
                                  type=openapi.TYPE_INTEGER, title="分段长度", description="分段长度"),
                openapi.Parameter(name='patterns',
                                  in_=openapi.IN_FORM,
                                  required=False,
                                  type=openapi.TYPE_ARRAY, items=openapi.Items(type=openapi.TYPE_STRING),
                                  title="分段正则列表", description="分段正则列表"),
                openapi.Parameter(name='with_filter',
                                  in_=openapi.IN_FORM,
                                  required=False,
                                  type=openapi.TYPE_BOOLEAN, title="是否清除特殊字符", description="是否清除特殊字符"),
            ]

        def parse(self):
            file_list = self.data.get("file")
            return list(
                map(lambda f: file_to_paragraph(f, self.data.get("patterns", None), self.data.get("with_filter", None),
                                                self.data.get("limit", 4096)), file_list))

    class SplitPattern(ApiMixin, serializers.Serializer):
        @staticmethod
        def list():
            return [{'key': "#", 'value': '(?<=^)# .*|(?<=\\n)# .*'},
                    {'key': '##', 'value': '(?<=\\n)(?<!#)## (?!#).*|(?<=^)(?<!#)## (?!#).*'},
                    {'key': '###', 'value': "(?<=\\n)(?<!#)### (?!#).*|(?<=^)(?<!#)### (?!#).*"},
                    {'key': '####', 'value': "(?<=\\n)(?<!#)#### (?!#).*|(?<=^)(?<!#)#### (?!#).*"},
                    {'key': '#####', 'value': "(?<=\\n)(?<!#)##### (?!#).*|(?<=^)(?<!#)##### (?!#).*"},
                    {'key': '######', 'value': "(?<=\\n)(?<!#)###### (?!#).*|(?<=^)(?<!#)###### (?!#).*"},
                    {'key': '-', 'value': '(?<! )- .*'},
                    {'key': '空格', 'value': '(?<! ) (?! )'},
                    {'key': '分号', 'value': '(?<!；)；(?!；)'}, {'key': '逗号', 'value': '(?<!，)，(?!，)'},
                    {'key': '句号', 'value': '(?<!。)。(?!。)'}, {'key': '回车', 'value': '(?<!\\n)\\n(?!\\n)'},
                    {'key': '空行', 'value': '(?<!\\n)\\n\\n(?!\\n)'}]

    class Batch(ApiMixin, serializers.Serializer):
        dataset_id = serializers.UUIDField(required=True, error_messages=ErrMessage.uuid("知识库id"))

        @staticmethod
        def get_request_body_api():
            return openapi.Schema(type=openapi.TYPE_ARRAY, items=DocumentSerializers.Create.get_request_body_api())

        @staticmethod
        def post_embedding(document_list, dataset_id):
            for document_dict in document_list:
                model_id = get_embedding_model_id_by_dataset_id(dataset_id)
                embedding_by_document.delay(document_dict.get('id'), model_id)
            return document_list

        @post(post_function=post_embedding)
        @transaction.atomic
        def batch_save(self, instance_list: List[Dict], with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)
            DocumentInstanceSerializer(many=True, data=instance_list).is_valid(raise_exception=True)
            dataset_id = self.data.get("dataset_id")
            document_model_list = []
            paragraph_model_list = []
            problem_paragraph_object_list = []
            # 插入文档
            for document in instance_list:
                document_paragraph_dict_model = DocumentSerializers.Create.get_document_paragraph_model(dataset_id,
                                                                                                        document)
                document_model_list.append(document_paragraph_dict_model.get('document'))
                for paragraph in document_paragraph_dict_model.get('paragraph_model_list'):
                    paragraph_model_list.append(paragraph)
                for problem_paragraph_object in document_paragraph_dict_model.get('problem_paragraph_object_list'):
                    problem_paragraph_object_list.append(problem_paragraph_object)

            problem_model_list, problem_paragraph_mapping_list = (ProblemParagraphManage(problem_paragraph_object_list,
                                                                                         dataset_id)
                                                                  .to_problem_model_list())
            # 插入文档
            QuerySet(Document).bulk_create(document_model_list) if len(document_model_list) > 0 else None
            # 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
            # 查询文档
            query_set = QuerySet(model=Document)
            if len(document_model_list) == 0:
                return [],
            query_set = query_set.filter(**{'id__in': [d.id for d in document_model_list]})
            return native_search(query_set, select_string=get_file_content(
                os.path.join(PROJECT_DIR, "apps", "dataset", 'sql', 'list_document.sql')),
                                 with_search_one=False), dataset_id

        @staticmethod
        def _batch_sync(document_id_list: List[str]):
            for document_id in document_id_list:
                DocumentSerializers.Sync(data={'document_id': document_id}).sync()

        def batch_sync(self, instance: Dict, with_valid=True):
            if with_valid:
                BatchSerializer(data=instance).is_valid(model=Document, raise_exception=True)
                self.is_valid(raise_exception=True)
            # 异步同步
            work_thread_pool.submit(self._batch_sync,
                                    instance.get('id_list'))
            return True

        @transaction.atomic
        def batch_delete(self, instance: Dict, with_valid=True):
            if with_valid:
                BatchSerializer(data=instance).is_valid(model=Document, raise_exception=True)
                self.is_valid(raise_exception=True)
            document_id_list = instance.get("id_list")
            QuerySet(Document).filter(id__in=document_id_list).delete()
            QuerySet(Paragraph).filter(document_id__in=document_id_list).delete()
            QuerySet(ProblemParagraphMapping).filter(document_id__in=document_id_list).delete()
            # 删除向量库
            delete_embedding_by_document_list(document_id_list)
            return True

        def batch_edit_hit_handling(self, instance: Dict, with_valid=True):
            if with_valid:
                BatchSerializer(data=instance).is_valid(model=Document, raise_exception=True)
                hit_handling_method = instance.get('hit_handling_method')
                if hit_handling_method is None:
                    raise AppApiException(500, '命中处理方式必填')
                if hit_handling_method != 'optimization' and hit_handling_method != 'directly_return':
                    raise AppApiException(500, '命中处理方式必须为directly_return|optimization')
                self.is_valid(raise_exception=True)
            document_id_list = instance.get("id_list")
            hit_handling_method = instance.get('hit_handling_method')
            directly_return_similarity = instance.get('directly_return_similarity')
            update_dict = {'hit_handling_method': hit_handling_method}
            if directly_return_similarity is not None:
                update_dict['directly_return_similarity'] = directly_return_similarity
            QuerySet(Document).filter(id__in=document_id_list).update(**update_dict)

        def batch_refresh(self, instance: Dict, with_valid=True):
            if with_valid:
                self.is_valid(raise_exception=True)
            document_id_list = instance.get("id_list")
            with transaction.atomic():
                Document.objects.filter(id__in=document_id_list).update(status=Status.queue_up)
                Paragraph.objects.filter(document_id__in=document_id_list).update(status=Status.queue_up)
                dataset_id = self.data.get('dataset_id')
                embedding_model_id = get_embedding_model_id_by_dataset_id(dataset_id=dataset_id)
                for document_id in document_id_list:
                    try:
                        embedding_by_document.delay(document_id, embedding_model_id)
                    except AlreadyQueued as e:
                        raise AppApiException(500, "任务正在执行中,请勿重复下发")


class FileBufferHandle:
    buffer = None

    def get_buffer(self, file):
        if self.buffer is None:
            self.buffer = file.read()
        return self.buffer


default_split_handle = TextSplitHandle()
split_handles = [HTMLSplitHandle(), DocSplitHandle(), PdfSplitHandle(), default_split_handle]


def save_image(image_list):
    if image_list is not None and len(image_list) > 0:
        QuerySet(Image).bulk_create(image_list)


def file_to_paragraph(file, pattern_list: List, with_filter: bool, limit: int):
    get_buffer = FileBufferHandle().get_buffer
    for split_handle in split_handles:
        if split_handle.support(file, get_buffer):
            return split_handle.handle(file, pattern_list, with_filter, limit, get_buffer, save_image)
    return default_split_handle.handle(file, pattern_list, with_filter, limit, get_buffer, save_image)