UnisKB/apps/dataset/serializers/document_serializers.py

608 lines
31 KiB
Python
Raw Normal View History

# coding=utf-8
"""
@project: maxkb
@Author
@file document_serializers.py
@date2023/9/22 13:43
@desc:
"""
2024-01-03 03:51:48 +00:00
import logging
import os
2024-01-03 03:51:48 +00:00
import traceback
import uuid
from functools import reduce
from typing import List, Dict
from django.db import transaction
from django.db.models import QuerySet
from drf_yasg import openapi
from rest_framework import serializers
from common.db.search import native_search, native_page_search
2024-01-03 07:40:37 +00:00
from common.event.common import work_thread_pool
from common.event.listener_manage import ListenerManagement, SyncWebDocumentArgs
from common.exception.app_exception import AppApiException
from common.mixins.api_mixin import ApiMixin
from common.util.common import post
2024-03-04 02:12:18 +00:00
from common.util.field_message import ErrMessage
from common.util.file_util import get_file_content
2024-01-03 03:51:48 +00:00
from common.util.fork import Fork
from common.util.split_model import SplitModel, get_split_model
from dataset.models.data_set import DataSet, Document, Paragraph, Problem, Type, Status, ProblemParagraphMapping
2024-01-19 08:47:18 +00:00
from dataset.serializers.common_serializers import BatchSerializer, MetaSerializer
from dataset.serializers.paragraph_serializers import ParagraphSerializers, ParagraphInstanceSerializer
from smartdoc.conf import PROJECT_DIR
2024-01-19 08:47:18 +00:00
class DocumentEditInstanceSerializer(ApiMixin, serializers.Serializer):
meta = serializers.DictField(required=False)
2024-03-04 02:12:18 +00:00
name = serializers.CharField(required=False, max_length=128, min_length=1,
error_messages=ErrMessage.char(
"文档名称"))
is_active = serializers.BooleanField(required=False, error_messages=ErrMessage.char(
"文档是否可用"))
2024-01-19 08:47:18 +00:00
@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):
2024-03-04 02:12:18 +00:00
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_body_api():
return openapi.Schema(
type=openapi.TYPE_OBJECT,
required=['source_url_list'],
properties={
'source_url_list': openapi.Schema(type=openapi.TYPE_ARRAY, title="段落列表", description="段落列表",
items=openapi.Schema(type=openapi.TYPE_STRING)),
'selector': openapi.Schema(type=openapi.TYPE_STRING, title="文档名称", description="文档名称")
}
)
class DocumentInstanceSerializer(ApiMixin, serializers.Serializer):
name = serializers.CharField(required=True,
2024-03-04 02:12:18 +00:00
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 DocumentSerializers(ApiMixin, serializers.Serializer):
class Query(ApiMixin, serializers.Serializer):
2023-12-18 03:32:29 +00:00
# 知识库id
2024-03-04 02:12:18 +00:00
dataset_id = serializers.UUIDField(required=True,
error_messages=ErrMessage.char(
"知识库id"))
2024-03-04 02:12:18 +00:00
name = serializers.CharField(required=False, max_length=128,
min_length=1,
error_messages=ErrMessage.char(
"文档名称"))
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__contains': self.data.get('name')})
2023-12-14 02:43:34 +00:00
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')]
@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())
2024-01-03 03:51:48 +00:00
class Sync(ApiMixin, serializers.Serializer):
2024-03-04 02:12:18 +00:00
document_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char(
"文档id"))
2024-01-03 03:51:48 +00:00
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")
2024-01-03 07:40:37 +00:00
def sync(self, with_valid=True, with_embedding=True):
2024-01-03 03:51:48 +00:00
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
2024-01-03 03:51:48 +00:00
try:
document.status = Status.embedding
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 []
2024-01-03 03:51:48 +00:00
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()
2024-01-03 03:51:48 +00:00
# 删除向量库
ListenerManagement.delete_embedding_by_document_signal.send(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_model_list = document_paragraph_model.get('problem_model_list')
problem_paragraph_mapping_list = document_paragraph_model.get('problem_paragraph_mapping_list')
2024-01-03 03:51:48 +00:00
# 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
2024-01-03 07:40:37 +00:00
# 向量化
if with_embedding:
ListenerManagement.embedding_by_document_signal.send(document_id)
2024-01-03 03:51:48 +00:00
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):
2024-03-04 02:12:18 +00:00
document_id = serializers.UUIDField(required=True, error_messages=ErrMessage.char(
"文档id"))
@staticmethod
def get_request_params_api():
return [openapi.Parameter(name='dataset_id',
in_=openapi.IN_PATH,
type=openapi.TYPE_STRING,
required=True,
2023-12-18 03:32:29 +00:00
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 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:
2024-01-19 08:47:18 +00:00
self.is_valid(raise_exception=True)
_document = QuerySet(Document).get(id=self.data.get("document_id"))
2024-01-19 08:47:18 +00:00
if with_valid:
DocumentEditInstanceSerializer(data=instance).is_valid(document=_document)
update_keys = ['name', 'is_active', '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")
2024-01-03 03:51:48 +00:00
document = QuerySet(Document).filter(id=document_id).first()
if document.type == Type.web:
2024-01-03 07:40:37 +00:00
# 异步同步
work_thread_pool.submit(lambda x: DocumentSerializers.Sync(data={'document_id': document_id}).sync(),
{})
2024-01-03 03:51:48 +00:00
2024-01-03 07:40:37 +00:00
else:
ListenerManagement.embedding_by_document_signal.send(document_id)
return True
@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
ListenerManagement.delete_embedding_by_document_signal.send(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",
2023-12-18 03:32:29 +00:00
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"),
2024-01-19 08:47:18 +00:00
'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):
2024-03-04 02:12:18 +00:00
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():
2023-12-18 03:32:29 +00:00
raise AppApiException(10000, "知识库id不存在")
return True
@staticmethod
def post_embedding(result, document_id):
ListenerManagement.embedding_by_document_signal.send(document_id)
return result
@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_model_list = document_paragraph_model.get('problem_model_list')
problem_paragraph_mapping_list = document_paragraph_model.get('problem_paragraph_mapping_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
@staticmethod
def get_sync_handler(dataset_id):
def handler(source_url: str, selector, response: Fork.Response):
if response.status == 200:
try:
paragraphs = get_split_model('web.md').parse(response.content)
# 插入
DocumentSerializers.Create(data={'dataset_id': dataset_id}).save(
{'name': source_url, 'paragraphs': paragraphs,
'meta': {'source_url': source_url, 'selector': selector},
'type': Type.web}, with_valid=True)
except Exception as e:
logging.getLogger("max_kb_error").error(f'{str(e)}:{traceback.format_exc()}')
else:
Document(name=source_url,
meta={'source_url': source_url, 'selector': selector},
type=Type.web,
char_length=0,
status=Status.error).save()
return handler
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')
args = SyncWebDocumentArgs(source_url_list, selector, self.get_sync_handler(dataset_id))
ListenerManagement.sync_web_document_signal.send(args)
@staticmethod
2024-01-03 03:51:48 +00:00
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(
2024-01-03 03:51:48 +00:00
dataset_id, document_model.id, paragraph) for paragraph in paragraph_list]
paragraph_model_list = []
problem_model_list = []
problem_paragraph_mapping_list = []
for paragraphs in paragraph_model_dict_list:
paragraph = paragraphs.get('paragraph')
for problem_model in paragraphs.get('problem_model_list'):
problem_model_list.append(problem_model)
for problem_paragraph_mapping in paragraphs.get('problem_paragraph_mapping_list'):
problem_paragraph_mapping_list.append(problem_paragraph_mapping)
paragraph_model_list.append(paragraph)
return {'document': document_model, 'paragraph_model_list': paragraph_model_list,
'problem_model_list': problem_model_list,
'problem_paragraph_mapping_list': problem_paragraph_mapping_list}
2024-01-03 03:51:48 +00:00
@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 [])
2024-01-03 03:51:48 +00:00
@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,
2023-12-18 03:32:29 +00:00
description='知识库id')
]
class Split(ApiMixin, serializers.Serializer):
2024-03-04 02:12:18 +00:00
file = serializers.ListField(required=True, error_messages=ErrMessage.list(
"文件列表"))
2024-03-04 02:12:18 +00:00
limit = serializers.IntegerField(required=False, error_messages=ErrMessage.integer(
"分段长度"))
patterns = serializers.ListField(required=False,
2024-03-04 02:12:18 +00:00
child=serializers.CharField(required=True, error_messages=ErrMessage.char(
"分段标识")),
error_messages=ErrMessage.uuid(
"分段标识列表"))
2024-03-04 02:12:18 +00:00
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 * 10:
raise AppApiException(500, "上传文件最大不能超过10m")
@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", None)), file_list))
class SplitPattern(ApiMixin, serializers.Serializer):
@staticmethod
def list():
2024-03-04 10:34:47 +00:00
return [{'key': "#", 'value': '(?<=^)# .*|(?<=\\n)# .*'}, {'key': '##', 'value': '(?<!#)## (?!#).*'},
{'key': '###', 'value': "(?<!#)### (?!#).*"}, {'key': '####', 'value': "(?<!#)#### (?!#).*"},
{'key': '#####', 'value': "(?<!#)##### (?!#).*"},
{'key': '######', 'value': "(?<!#)###### (?!#).*"},
{'key': '-', 'value': '(?<! )- .*'},
{'key': '空格', 'value': '(?<!\\s)\\s(?!\\s)'},
{'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):
2024-03-04 02:12:18 +00:00
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):
for document_dict in document_list:
ListenerManagement.embedding_by_document_signal.send(document_dict.get('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_model_list = []
problem_paragraph_mapping_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 in document_paragraph_dict_model.get('problem_model_list'):
problem_model_list.append(problem)
for problem_paragraph_mapping in document_paragraph_dict_model.get('problem_paragraph_mapping_list'):
problem_paragraph_mapping_list.append(problem_paragraph_mapping)
# 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)
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),
@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
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(Problem).filter(document_id__in=document_id_list).delete()
# 删除向量库
ListenerManagement.delete_embedding_by_document_list_signal.send(document_id_list)
return True
def file_to_paragraph(file, pattern_list: List, with_filter: bool, limit: int):
data = file.read()
if pattern_list is not None and len(pattern_list) > 0:
split_model = SplitModel(pattern_list, with_filter, limit)
else:
split_model = get_split_model(file.name, with_filter=with_filter, limit=limit)
try:
content = data.decode('utf-8')
except BaseException as e:
return {'name': file.name,
'content': []}
return {'name': file.name,
'content': split_model.parse(content)
}