markdown graf

app.py

@@ -1,6 +1,5 @@
 # https://towardsai.net/p/machine-learning/deploying-a-langchain-large-language-model-llm-with-streamlit-pinecone?amp=1
 
-"""Python file to serve as the frontend"""
 import os
 import pinecone
 import streamlit as st
@@ -60,6 +59,11 @@ chain = load_chain()
 # From here down is all the StreamLit UI.
 st.set_page_config(page_title="Impromptu GPT", page_icon=":robot:")
 st.header("Impromptu GPT")
+'''
+A secondary UI written entirely in Python, so as to use LangChain's 
+new <code>SelfQueryRetriever</code>, which is currently only written 
+for LangChain's Python codebase.
+'''
 
 if "generated" not in st.session_state:
     st.session_state["generated"] = []
@@ -79,7 +83,6 @@ if user_input:
     st.session_state.generated.append(output)
 
 if st.session_state["generated"]:
-
     for i in range(len(st.session_state["generated"]) - 1, -1, -1):
         message(st.session_state["generated"][i], key=str(i), avatar_style="bottts")
         message(st.session_state["past"][i], is_user=True, key=str(i) + "_user", avatar_style="shapes")