ragflow / api /apps /sdk /dataset.py
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#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from flask import request
from api.db import StatusEnum, FileSource
from api.db.db_models import File
from api.db.services.document_service import DocumentService
from api.db.services.file2document_service import File2DocumentService
from api.db.services.file_service import FileService
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.db.services.llm_service import TenantLLMService,LLMService
from api.db.services.user_service import TenantService
from api.settings import RetCode
from api.utils import get_uuid
from api.utils.api_utils import get_result, token_required, get_error_data_result, valid,get_parser_config
@manager.route('/datasets', methods=['POST'])
@token_required
def create(tenant_id):
req = request.json
e, t = TenantService.get_by_id(tenant_id)
permission = req.get("permission")
language = req.get("language")
chunk_method = req.get("chunk_method")
parser_config = req.get("parser_config")
valid_permission = ["me", "team"]
valid_language =["Chinese", "English"]
valid_chunk_method = ["naive","manual","qa","table","paper","book","laws","presentation","picture","one","knowledge_graph","email"]
check_validation=valid(permission,valid_permission,language,valid_language,chunk_method,valid_chunk_method)
if check_validation:
return check_validation
req["parser_config"]=get_parser_config(chunk_method,parser_config)
if "tenant_id" in req:
return get_error_data_result(
retmsg="`tenant_id` must not be provided")
if "chunk_count" in req or "document_count" in req:
return get_error_data_result(retmsg="`chunk_count` or `document_count` must not be provided")
if "name" not in req:
return get_error_data_result(
retmsg="`name` is not empty!")
req['id'] = get_uuid()
req["name"] = req["name"].strip()
if req["name"] == "":
return get_error_data_result(
retmsg="`name` is not empty string!")
if KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value):
return get_error_data_result(
retmsg="Duplicated dataset name in creating dataset.")
req["tenant_id"] = req['created_by'] = tenant_id
if not req.get("embedding_model"):
req['embedding_model'] = t.embd_id
else:
valid_embedding_models=["BAAI/bge-large-zh-v1.5","BAAI/bge-base-en-v1.5","BAAI/bge-large-en-v1.5","BAAI/bge-small-en-v1.5",
"BAAI/bge-small-zh-v1.5","jinaai/jina-embeddings-v2-base-en","jinaai/jina-embeddings-v2-small-en",
"nomic-ai/nomic-embed-text-v1.5","sentence-transformers/all-MiniLM-L6-v2","text-embedding-v2",
"text-embedding-v3","maidalun1020/bce-embedding-base_v1"]
embd_model=LLMService.query(llm_name=req["embedding_model"],model_type="embedding")
if not embd_model:
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
if embd_model:
if req["embedding_model"] not in valid_embedding_models and not TenantLLMService.query(tenant_id=tenant_id,model_type="embedding", llm_name=req.get("embedding_model")):
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
key_mapping = {
"chunk_num": "chunk_count",
"doc_num": "document_count",
"parser_id": "chunk_method",
"embd_id": "embedding_model"
}
mapped_keys = {new_key: req[old_key] for new_key, old_key in key_mapping.items() if old_key in req}
req.update(mapped_keys)
if not KnowledgebaseService.save(**req):
return get_error_data_result(retmsg="Create dataset error.(Database error)")
renamed_data = {}
e, k = KnowledgebaseService.get_by_id(req["id"])
for key, value in k.to_dict().items():
new_key = key_mapping.get(key, key)
renamed_data[new_key] = value
return get_result(data=renamed_data)
@manager.route('/datasets', methods=['DELETE'])
@token_required
def delete(tenant_id):
req = request.json
if not req:
ids=None
else:
ids=req.get("ids")
if not ids:
id_list = []
kbs=KnowledgebaseService.query(tenant_id=tenant_id)
for kb in kbs:
id_list.append(kb.id)
else:
id_list=ids
for id in id_list:
kbs = KnowledgebaseService.query(id=id, tenant_id=tenant_id)
if not kbs:
return get_error_data_result(retmsg=f"You don't own the dataset {id}")
for doc in DocumentService.query(kb_id=id):
if not DocumentService.remove_document(doc, tenant_id):
return get_error_data_result(
retmsg="Remove document error.(Database error)")
f2d = File2DocumentService.get_by_document_id(doc.id)
FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id])
File2DocumentService.delete_by_document_id(doc.id)
if not KnowledgebaseService.delete_by_id(id):
return get_error_data_result(
retmsg="Delete dataset error.(Database error)")
return get_result(retcode=RetCode.SUCCESS)
@manager.route('/datasets/<dataset_id>', methods=['PUT'])
@token_required
def update(tenant_id,dataset_id):
if not KnowledgebaseService.query(id=dataset_id,tenant_id=tenant_id):
return get_error_data_result(retmsg="You don't own the dataset")
req = request.json
e, t = TenantService.get_by_id(tenant_id)
invalid_keys = {"id", "embd_id", "chunk_num", "doc_num", "parser_id"}
if any(key in req for key in invalid_keys):
return get_error_data_result(retmsg="The input parameters are invalid.")
permission = req.get("permission")
language = req.get("language")
chunk_method = req.get("chunk_method")
parser_config = req.get("parser_config")
valid_permission = ["me", "team"]
valid_language = ["Chinese", "English"]
valid_chunk_method = ["naive", "manual", "qa", "table", "paper", "book", "laws", "presentation", "picture", "one",
"knowledge_graph", "email"]
check_validation = valid(permission, valid_permission, language, valid_language, chunk_method, valid_chunk_method)
if check_validation:
return check_validation
if "tenant_id" in req:
if req["tenant_id"] != tenant_id:
return get_error_data_result(
retmsg="Can't change `tenant_id`.")
e, kb = KnowledgebaseService.get_by_id(dataset_id)
if "parser_config" in req:
temp_dict=kb.parser_config
temp_dict.update(req["parser_config"])
req["parser_config"] = temp_dict
if "chunk_count" in req:
if req["chunk_count"] != kb.chunk_num:
return get_error_data_result(
retmsg="Can't change `chunk_count`.")
req.pop("chunk_count")
if "document_count" in req:
if req['document_count'] != kb.doc_num:
return get_error_data_result(
retmsg="Can't change `document_count`.")
req.pop("document_count")
if "chunk_method" in req:
if kb.chunk_num != 0 and req['chunk_method'] != kb.parser_id:
return get_error_data_result(
retmsg="If `chunk_count` is not 0, `chunk_method` is not changeable.")
req['parser_id'] = req.pop('chunk_method')
if req['parser_id'] != kb.parser_id:
if not req.get("parser_config"):
req["parser_config"] = get_parser_config(chunk_method, parser_config)
if "embedding_model" in req:
if kb.chunk_num != 0 and req['embedding_model'] != kb.embd_id:
return get_error_data_result(
retmsg="If `chunk_count` is not 0, `embedding_model` is not changeable.")
if not req.get("embedding_model"):
return get_error_data_result("`embedding_model` can't be empty")
valid_embedding_models=["BAAI/bge-large-zh-v1.5","BAAI/bge-base-en-v1.5","BAAI/bge-large-en-v1.5","BAAI/bge-small-en-v1.5",
"BAAI/bge-small-zh-v1.5","jinaai/jina-embeddings-v2-base-en","jinaai/jina-embeddings-v2-small-en",
"nomic-ai/nomic-embed-text-v1.5","sentence-transformers/all-MiniLM-L6-v2","text-embedding-v2",
"text-embedding-v3","maidalun1020/bce-embedding-base_v1"]
embd_model=LLMService.query(llm_name=req["embedding_model"],model_type="embedding")
if not embd_model:
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
if embd_model:
if req["embedding_model"] not in valid_embedding_models and not TenantLLMService.query(tenant_id=tenant_id,model_type="embedding", llm_name=req.get("embedding_model")):
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
req['embd_id'] = req.pop('embedding_model')
if "name" in req:
req["name"] = req["name"].strip()
if req["name"].lower() != kb.name.lower() \
and len(KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id,
status=StatusEnum.VALID.value)) > 0:
return get_error_data_result(
retmsg="Duplicated dataset name in updating dataset.")
if not KnowledgebaseService.update_by_id(kb.id, req):
return get_error_data_result(retmsg="Update dataset error.(Database error)")
return get_result(retcode=RetCode.SUCCESS)
@manager.route('/datasets', methods=['GET'])
@token_required
def list(tenant_id):
id = request.args.get("id")
name = request.args.get("name")
kbs = KnowledgebaseService.query(id=id,name=name,status=1)
if not kbs:
return get_error_data_result(retmsg="The dataset doesn't exist")
page_number = int(request.args.get("page", 1))
items_per_page = int(request.args.get("page_size", 1024))
orderby = request.args.get("orderby", "create_time")
if request.args.get("desc") == "False" or request.args.get("desc") == "false" :
desc = False
else:
desc = True
tenants = TenantService.get_joined_tenants_by_user_id(tenant_id)
kbs = KnowledgebaseService.get_list(
[m["tenant_id"] for m in tenants], tenant_id, page_number, items_per_page, orderby, desc, id, name)
renamed_list = []
for kb in kbs:
key_mapping = {
"chunk_num": "chunk_count",
"doc_num": "document_count",
"parser_id": "chunk_method",
"embd_id": "embedding_model"
}
renamed_data = {}
for key, value in kb.items():
new_key = key_mapping.get(key, key)
renamed_data[new_key] = value
renamed_list.append(renamed_data)
return get_result(data=renamed_list)