How to use LangChain to load the index generated by LlamaIndex and perform a query?

[chenkuncloud]

I used LlamaIndex to generate an index for a section of text, which is stored in the myindex folder.
How should I use LangChain to load it and query it?

At present, I can only use LlamaIndex for querying, but this will lack the functionality of LangChain (such as Prompts, Chains, Agents).

build.py:

from llama_index import (
    Document,
    VectorStoreIndex
)
from langchain import OpenAI
import os.path as osp

text_list = ['Avery is a respiratory physician who specializes in addressing issues related to the novel coronavirus. His desire is for the number of patients in the world to decrease over time.']
documents = [Document(t) for t in text_list]

index = VectorStoreIndex.from_documents(documents)
index.storage_context.persist(persist_dir="myindex")

query.py:

from llama_index import StorageContext, load_index_from_storage

storage_context = StorageContext.from_defaults(persist_dir="myindex")
index = load_index_from_storage(storage_context)
query_engine = index.as_query_engine()
print(query_engine.query("Who is Avery?"))

Best regards