使用 AI 套件上传文件并检索

import json
import time
from typing import Optional

import tcvectordb
from tcvectordb import exceptions
from tcvectordb.model.ai_database import AIDatabase
from tcvectordb.model.collection_view import Embedding, SplitterProcess, Language, CollectionView
from tcvectordb.model.document import Filter, Document
from tcvectordb.model.document_set import DocumentSet, Rerank
from tcvectordb.model.enum import FieldType, IndexType, ReadConsistency
from tcvectordb.model.index import Index, FilterIndex

#create vdb client
vdbclient = tcvectordb.VectorDBClient(url="your vdb url",
                                    key="your vdb api_key",
                                    username="root")

def vdbInit():
    # create database
    db = vdbclient.create_ai_database("test_db")
    # create collectionView
    collView = db.create_collection_view("test_collView")
    # upload and split text
    collView.load_and_split_text(local_file_path="/docs/fileName.md")
    print('upload file sucess')

def knowledgeSearch(query):
    db = vdbclient.database('test_db')
    collView = db.collection_view('test_collView')
    doc_list = collView.search(
            content=query,
            limit=3
        )
    knowledge = "以下是根据输入问题检索到的知识内容：\\n"
    knowledge_id = 1
    for item in doc_list:
            knowledge += ("知识内容%s:\\n%s"%(knowledge_id,item.data.text))
            knowledge_id += 1
    return(knowledge)

if __name__ == "__main__":
    vdbInit()
    query = input("请输入查询内容：")
    print("============================================")
    print(knowledgeSearch(query))