revert to previous version

models/llamaCustom.py

@@ -5,8 +5,8 @@ from typing import Any, List, Mapping, Optional
 
 import numpy as np
 import openai
-import streamlit as st
 import pandas as pd
+import streamlit as st
 from dotenv import load_dotenv
 from huggingface_hub import HfFileSystem
 from langchain.llms.base import LLM
@@ -71,15 +71,13 @@ class CustomLLM(LLM):
     def _llm_type(self) -> str:
         return "custom"
 
-@st.cache_resource
 class LlamaCustom:
-
     def __init__(self, model_name: str) -> None:
         self.vector_index = self.initialize_index(model_name=model_name)
 
     def initialize_index(self, model_name: str):
         index_name = model_name.split("/")[-1]
-        
+
         file_path = f"./vectorStores/{index_name}"
         if os.path.exists(path=file_path):
             # rebuild storage context
@@ -103,7 +101,7 @@ class LlamaCustom:
             service_context = ServiceContext.from_defaults(
                 llm_predictor=llm_predictor, prompt_helper=prompt_helper
             )
-            
+
             # documents = prepare_data(r"./assets/regItems.json")
             documents = SimpleDirectoryReader(input_dir="./assets/pdf").load_data()
 
@@ -123,4 +121,4 @@ class LlamaCustom:
         print("query_str: ", query_str)
         query_engine = self.vector_index.as_query_engine()
         response = query_engine.query(query_str)
-        return str(response)
+        return str(response)