kangda-robot-backend/ruoyi-fastapi-backend/module_admin/service/ragflow_service.py

182 lines
5.5 KiB
Python

from sqlalchemy.ext.asyncio import AsyncSession
from module_admin.entity.vo.ragflow_vo import RagflowListQueryModel, ListDocumentsQueryModel, UpdateFileModel, DeleteFileModel, CreateDatasetModel, DocumentIdsModel, UpdateChatAssistantModel \
,CreateSessionWithChatModel, ConverseWithChatAssistantModel
from utils.ragflow_client_manager import get_ragflow_client
class RAGFlowService:
"""
RAGFlow服务
"""
# 获取数据集列表
@classmethod
async def get_ragflow_dataset_list_services(cls, query_db: AsyncSession, rage_flow_query: RagflowListQueryModel):
"""
获取数据集列表
"""
client = await get_ragflow_client()
result = await client.list_datasets(**(rage_flow_query.model_dump()))
# 获取分页数据
return result
# 创建数据集
@classmethod
async def create_dataset_services(cls, create_dataset_params: CreateDatasetModel):
"""创建数据集
Args:
create_dataset_params (CreateDatasetModel): 创建参数
Returns:
_type_: _description_
"""
client = await get_ragflow_client()
result = await client.create_dataset(
**(create_dataset_params.model_dump())
)
return result
# 更新数据集
@classmethod
async def update_dataset_services(
cls,
dataset_id: str,
update_dataset_params: CreateDatasetModel,
):
"""更新数据集信息
Args:
dataset_id (str): 数据集id
update_dataset_params (CreateDatasetModel): 更新参数
Returns:
_type_: _description_
"""
client = await get_ragflow_client()
result = await client.update_dataset(
dataset_id=dataset_id, **(update_dataset_params.model_dump())
)
return result
# 获取数据集中文档列表
@classmethod
async def list_documents_services(
cls,
query_db: AsyncSession,
dataset_id: str,
list_documents_query: ListDocumentsQueryModel,
):
client = await get_ragflow_client()
result = await client.list_documents(dataset_id=dataset_id, **(list_documents_query.model_dump()))
return result
# 上传文档到数据集
@classmethod
async def upload_file_dataset_services(
cls,
dataset_id: str,
files,
):
client = await get_ragflow_client()
result = await client.upload_documents_bytes(dataset_id=dataset_id, file_bytes=files)
return result
# 开始解析文档
@classmethod
async def parse_documents_services(
cls,
dataset_id: str,
parse_params: DocumentIdsModel,
):
client = await get_ragflow_client()
result = await client.parse_documents(dataset_id=dataset_id, document_ids=parse_params.documnet_ids)
return result
# 停止解析文档
@classmethod
async def stop_parse_documents_services(
cls,
dataset_id: str,
parse_params: DocumentIdsModel,
):
client = await get_ragflow_client()
result = await client.stop_parsing_documents(dataset_id=dataset_id, document_ids=parse_params.documnet_ids)
return result
# 更新文档内容
@classmethod
async def update_file_dataset_services(
cls,
dataset_id: str,
document_id: str,
update_params: UpdateFileModel,
):
client = await get_ragflow_client()
result = await client.update_document(dataset_id=dataset_id, document_id=document_id, **(update_params.model_dump()))
return result
# 删除文档
@classmethod
async def delete_file_services(
cls,
dataset_id: str,
delete_params: DeleteFileModel,
):
client = await get_ragflow_client()
result = await client.delete_documents(dataset_id=dataset_id, **(delete_params.model_dump()))
return result
# 删除数据集
@classmethod
async def delete_datasets_services(
cls,
delete_params: DeleteFileModel,
):
client = await get_ragflow_client()
result = await client.delete_datasets(**(delete_params.model_dump()))
return result
# 查看聊天助手列表
@classmethod
async def get_chat_assistant_list_services(
cls,
query_params: RagflowListQueryModel,
):
client = await get_ragflow_client()
result = await client.list_chat_assistants(**(query_params.model_dump()))
return result
# 修改聊天助手
@classmethod
async def update_chat_assistant_services(cls, update_params: UpdateChatAssistantModel):
client = await get_ragflow_client()
result = await client.update_chat_assistant(**(update_params.model_dump()))
return result
# 创建助手会话
@classmethod
async def create_session_with_chat_services(cls, create_params: CreateSessionWithChatModel):
client = await get_ragflow_client()
result = await client.create_session_with_chat(**(create_params.model_dump()))
return result
# 与助手聊天
@classmethod
async def converse_with_chat_assistant_services(cls, converse_params: ConverseWithChatAssistantModel):
client = await get_ragflow_client()
return await client.converse_with_chat_assistant(**(converse_params.model_dump()))