codefuse-chatbot/dev_opsgpt/service/base_service.py

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2023-09-28 10:58:58 +08:00
from abc import ABC, abstractmethod
from typing import List
import os
from langchain.embeddings.base import Embeddings
from langchain.docstore.document import Document
from configs.model_config import (
kbs_config, VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD,
EMBEDDING_MODEL, EMBEDDING_DEVICE
)
from dev_opsgpt.orm.commands import *
from dev_opsgpt.utils.path_utils import *
from dev_opsgpt.orm.utils import DocumentFile
from dev_opsgpt.embeddings.utils import load_embeddings
from dev_opsgpt.text_splitter import LCTextSplitter
class SupportedVSType:
FAISS = 'faiss'
# MILVUS = 'milvus'
# DEFAULT = 'default'
# PG = 'pg'
class KBService(ABC):
def __init__(self,
knowledge_base_name: str,
embed_model: str = EMBEDDING_MODEL,
):
self.kb_name = knowledge_base_name
self.embed_model = embed_model
self.kb_path = get_kb_path(self.kb_name)
self.doc_path = get_doc_path(self.kb_name)
self.do_init()
def _load_embeddings(self, embed_device: str = EMBEDDING_DEVICE) -> Embeddings:
return load_embeddings(self.embed_model, embed_device)
def create_kb(self):
"""
创建知识库
"""
if not os.path.exists(self.doc_path):
os.makedirs(self.doc_path)
self.do_create_kb()
status = add_kb_to_db(self.kb_name, self.vs_type(), self.embed_model)
return status
def clear_vs(self):
"""
删除向量库中所有内容
"""
self.do_clear_vs()
status = delete_files_from_db(self.kb_name)
return status
def drop_kb(self):
"""
删除知识库
"""
self.do_drop_kb()
status = delete_kb_from_db(self.kb_name)
return status
def add_doc(self, kb_file: DocumentFile, **kwargs):
"""
向知识库添加文件
"""
lctTextSplitter = LCTextSplitter(kb_file.filepath)
docs = lctTextSplitter.file2text()
if docs:
self.delete_doc(kb_file)
embeddings = self._load_embeddings()
self.do_add_doc(docs, embeddings, **kwargs)
status = add_doc_to_db(kb_file)
else:
status = False
return status
def delete_doc(self, kb_file: DocumentFile, delete_content: bool = False, **kwargs):
"""
从知识库删除文件
"""
self.do_delete_doc(kb_file, **kwargs)
status = delete_file_from_db(kb_file)
if delete_content and os.path.exists(kb_file.filepath):
os.remove(kb_file.filepath)
return status
def update_doc(self, kb_file: DocumentFile, **kwargs):
"""
使用content中的文件更新向量库
"""
if os.path.exists(kb_file.filepath):
self.delete_doc(kb_file, **kwargs)
return self.add_doc(kb_file, **kwargs)
def exist_doc(self, file_name: str):
return doc_exists(DocumentFile(knowledge_base_name=self.kb_name,
filename=file_name))
def list_docs(self):
return list_docs_from_db(self.kb_name)
def search_docs(self,
query: str,
top_k: int = VECTOR_SEARCH_TOP_K,
score_threshold: float = SCORE_THRESHOLD,
):
embeddings = self._load_embeddings()
docs = self.do_search(query, top_k, score_threshold, embeddings)
return docs
@abstractmethod
def do_create_kb(self):
"""
创建知识库子类实自己逻辑
"""
pass
@staticmethod
def list_kbs_type():
return list(kbs_config.keys())
@classmethod
def list_kbs(cls):
return list_kbs_from_db()
def exists(self, kb_name: str = None):
kb_name = kb_name or self.kb_name
return kb_exists(kb_name)
@abstractmethod
def vs_type(self) -> str:
pass
@abstractmethod
def do_init(self):
pass
@abstractmethod
def do_drop_kb(self):
"""
删除知识库子类实自己逻辑
"""
pass
@abstractmethod
def do_search(self,
query: str,
top_k: int,
embeddings: Embeddings,
) -> List[Document]:
"""
搜索知识库子类实自己逻辑
"""
pass
@abstractmethod
def do_add_doc(self,
docs: List[Document],
embeddings: Embeddings,
):
"""
向知识库添加文档子类实自己逻辑
"""
pass
@abstractmethod
def do_delete_doc(self,
kb_file: DocumentFile):
"""
从知识库删除文档子类实自己逻辑
"""
pass
@abstractmethod
def do_clear_vs(self):
"""
从知识库删除全部向量子类实自己逻辑
"""
pass