Update app.py

app.py

@@ -1,5 +1,7 @@
 import os
 import streamlit as st
+import random
+import time
 from langchain.chat_models import ChatOpenAI
 from langchain.chains import ConversationalRetrievalChain
 from langchain.prompts import PromptTemplate
@@ -88,7 +90,7 @@ st.markdown("""
         margin: 5px 0;
         text-align: left;
     }
-    .bot-message {
+    .assistant-message {
         background-color: #e2e3e5;
         border-radius: 10px;
         padding: 10px;
@@ -99,30 +101,36 @@ st.markdown("""
 """, unsafe_allow_html=True)
 
 # Initialize chat history in session state
-if 'chat_history' not in st.session_state:
-    st.session_state.chat_history = []
-
-# User input for course interests
-user_query = st.text_input("What are you looking to learn?", "")
-
-# Button to get course recommendations
-if st.button("Get Recommendation"):
-    if user_query:
-        response = qa_chain({"question": user_query})
-        recommendation = response["answer"]
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Accept user input
+if prompt := st.chat_input("What are you looking to learn?"):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Assistant response generator with streaming effect
+    with st.chat_message("assistant"):
+        response = qa_chain({"question": prompt})
+        response_text = response["answer"]
         
-        # Update chat history with user's query and recommendation
-        st.session_state.chat_history.append({"user": user_query, "bot": recommendation})
+        # Simulate streaming response
+        for word in response_text.split():
+            st.markdown(word + " ", unsafe_allow_html=True)
+            time.sleep(0.05)  # Delay for effect
 
-# Display chat history in a styled format
-with st.container():
-    st.markdown('<div class="chat-container">', unsafe_allow_html=True)
-    for chat in st.session_state.chat_history:
-        st.markdown(f'<div class="user-message"><strong>You:</strong> {chat["user"]}</div>', unsafe_allow_html=True)
-        st.markdown(f'<div class="bot-message"><strong>AI Recommendation:</strong> {chat["bot"]}</div>', unsafe_allow_html=True)
-    st.markdown('</div>', unsafe_allow_html=True)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": response_text})
 
 # Optional: Add a button to clear the chat history
 if st.button("Clear Chat History"):
-    st.session_state.chat_history.clear()
+    st.session_state.messages.clear()
     st.experimental_rerun()