@st .cache_data doesn't work because hugging face uses an older streamlit version

app.py

@@ -12,7 +12,7 @@ from langchain import OpenAI
 from langchain import PromptTemplate
 
 
-@st.cache_data
+@st.experimental_memo
 def load_vectorstore():
     # download from hugging face
     snapshot_download(repo_id="calmgoose/orwell-1984_faiss-instructembeddings",
@@ -43,7 +43,7 @@ def load_vectorstore():
 
     return docsearch
 
-@st.cache_data
+@st.experimental_memo
 def load_chain():
 
     BOOK_NAME = "1984"
@@ -96,8 +96,6 @@ def get_answer(question):
     return result["result"] + "\n\n" + "From pages: " + sources_string
 
 
-# chain = load_chain()
-
 # From here down is all the StreamLit UI.
 st.set_page_config(page_title="Talk2Book: 1984", page_icon="📖")
 st.title("Talk2Book: 1984")