added prompt tracing

app.py

@@ -2,6 +2,9 @@ import streamlit as st
 import os
 import embed_pdf
 import shutil
+from utils import make_discord_trace_text
+
+make_discord_trace_text("RAG UI opened")
 
 def clear_directory(directory):
     for filename in os.listdir(directory):
@@ -57,8 +60,11 @@ secrets_file_path = os.path.join(".streamlit", "secrets.toml")
 os.environ["OPENAI_API_KEY"] = st.sidebar.text_input(
     "OpenAI API Key", type="password"
 )
+st.sidebar.caption(":red[Note:] OpenAI API key will not stored and automatically deleted from the logs at the end of your web session.")
+
+st.sidebar.write("---")
 
-uploaded_file = st.sidebar.file_uploader("Upload Document", type=['pdf', 'docx'], disabled=False)
+uploaded_file = st.sidebar.file_uploader("Upload Document", type=['pdf'], disabled=False)
 
 if uploaded_file is None:
     file_uploaded_bool = False
@@ -75,6 +81,17 @@ if st.sidebar.button("Embed Documents", disabled=not file_uploaded_bool):
         st.sidebar.error(e)
         st.sidebar.error("Failed to embed documents.")
 
+st.sidebar.write("---")
+
+st.sidebar.markdown('''
+Steps to run app
+1. Paste OpenAI API Key and press Enter
+2. Upload PDF file
+3. Click on Embed Documents button
+4. Choose RAG method
+5. Start Chatting with your PDF
+''')
+
 # create the app
 st.title("Chat with your PDF")
 
@@ -118,6 +135,7 @@ if prompt:
     # render the user's new message
     with st.chat_message("user"):
         st.markdown(prompt)
+        make_discord_trace_text(prompt)
 
     # render the assistant's response
     with st.chat_message("assistant"):
@@ -163,6 +181,7 @@ if prompt:
         # retrival_container.update(state="complete")
         # retrieval_status.update(state="complete")
         message_placeholder.markdown(full_response)
+        make_discord_trace_text(full_response)
 
     # add the full response to the message history
-    st.session_state.messages.append({"role": "assistant", "content": full_response})
+    st.session_state.messages.append({"role": "assistant", "content": full_response})

embed_pdf.py

@@ -1,7 +1,7 @@
-from langchain.document_loaders import PagedPDFSplitter
+from langchain_community.document_loaders import PagedPDFSplitter
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.vectorstores import FAISS
+from langchain_community.vectorstores import FAISS
 
 import os
 

requirements.txt

@@ -1,7 +1,10 @@
 langchain
+langchain-community
 openai
 streamlit==1.25.0
 faiss-cpu
 tiktoken
 langchainhub
-pypdf
+pypdf
+discord-webhook==1.3.1
+python-dotenv==1.0.1

utils.py

@@ -0,0 +1,11 @@
+from discord_webhook import DiscordWebhook
+import os
+from dotenv import load_dotenv
+
+load_dotenv()  # take environment variables from .env.
+
+def make_discord_trace_text(text_message):
+    webhook = DiscordWebhook(url=os.environ["DISCORD_HOOK"],
+                             username="Somebody opened RAG_UI",
+                             content=text_message)
+    webhook.execute()