Update app.py

app.py

@@ -1,3 +1,6 @@
+# https://github.com/logan-markewich/llama_index_starter_pack/blob/main/streamlit_vector/streamlit_demo.py
+#
+
 import os
 import streamlit as st
 from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader, ServiceContext
@@ -5,8 +8,7 @@ from llama_index.llm_predictor.chatgpt import ChatGPTLLMPredictor
 
 
 index_name = "./index.json"
-documents_folder = "./documents"
-
+documents_folder = "/data/python.langchain.com/en/latest"
 
 @st.cache_resource
 def initialize_index(index_name, documents_folder):
@@ -28,9 +30,9 @@ def query_index(_index, query_text):
     return str(response)
 
 
-st.title("🦙 Llama Index Demo 🦙")
-st.header("Welcome to the Llama Index Streamlit Demo")
-st.write("Enter a query about Paul Graham's essays. You can check out the original essay [here](https://raw.githubusercontent.com/jerryjliu/llama_index/main/examples/paul_graham_essay/data/paul_graham_essay.txt). Your query will be answered using the essay as context, using embeddings from text-ada-002 and LLM completions from ChatGPT. You can read more about Llama Index and how this works in [our docs!](https://gpt-index.readthedocs.io/en/latest/index.html)")
+st.title("🦙 Llama Index LangChain 🦙")
+st.header("Welcome to the Llama Index Streamlit LangChain")
+st.write("Enter a query about LangChain python document. You can check out the latest python doc [here](https://python.langchain.com/en/latest/). Your query will be answered using the document as context, using embeddings from text-ada-002 and LLM completions from ChatGPT.")
 
 index = None
 api_key = st.text_input("Enter your OpenAI API key here:", type="password")
@@ -53,4 +55,4 @@ if st.button("Run Query") and text is not None:
         st.markdown(f"LLM Tokens Used: {index.service_context.llm_predictor._last_token_usage}")
     
     with embed_col:
-        st.markdown(f"Embedding Tokens Used: {index.service_context.embed_model._last_token_usage}")
+        st.markdown(f"Embedding Tokens Used: {index.service_context.embed_model._last_token_usage}")