I am using cromadb for vectorization in my flask application.
below is my vectordb.py code:-

import os
import shutil
from dotenv import load_dotenv
load_dotenv()

import re
from llama_index import (
    SimpleDirectoryReader, 
    VectorStoreIndex, 
    ServiceContext, 
    StorageContext
)
from llama_index.vector_stores import ChromaVectorStore
from llama_index.llms import OpenAI
from llama_index.embeddings import OpenAIEmbedding
from llama_index.prompts import PromptTemplate
import chromadb

import logging
import sys
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

def regenrate_tokens(collection_name, persist_directory):
    if os.path.isdir(persist_directory):
        print("directory existed, replacing previous directory")
        
        # Close the chroma_client connection
        chroma_client = chromadb.PersistentClient(path=persist_directory)
        chroma_client.close()  # Ensure the database connection is closed
        
        shutil.rmtree(persist_directory)
    
    print("Recreating Embeddings...")
    chroma_client = chromadb.PersistentClient(path=persist_directory)
    embed_model = OpenAIEmbedding()
    documents = SimpleDirectoryReader('./static/upload/').load_data()
    chroma_collection = chroma_client.get_or_create_collection(collection_name)
    vector_store = ChromaVectorStore(chroma_collection=chroma_collection)
    storage_context = StorageContext.from_defaults(vector_store=vector_store)
    service_context = ServiceContext.from_defaults(embed_model=embed_model)
    index = VectorStoreIndex.from_documents(
        documents, storage_context=storage_context, service_context=service_context
    )

    return 'Data refreshed, you can ask the questions. 😄'

getting this error in the UIenter image description here ‘SegmentAPI’ object has no attribute ‘close’

I am uploading a zip file containing pdf for vectorization.
I want to get a result according to my query but getting this error