Update app.py

app.py

@@ -60,21 +60,37 @@ for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
-prompt = st.chat_input("What kind of class are you looking for?")
-
+if prompt := st.chat_input("What kind of class are you looking for?"):
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    response = filter_agent(prompt, OPENAI_API)
+    query = response
+
+    response = index.query(
+        vector= embeddings.embed_query(query),
+        # filter= build_filter(json),
+        top_k=5,
+        include_metadata=True
+    )
+    response = reranker(query, response)
+    result_query = 'Original Query:' + query + 'Query Results:' + str(response)
+    assistant_response = result_agent(result_query, OPENAI_API)
 
 ### GPT Response
 # Display assistant response in chat message container
 with st.chat_message("assistant"):
     message_placeholder = st.empty()
     full_response = ""
-    assistant_response = "Hello there! How can I assist you today?"
     # Simulate stream of response with milliseconds delay
     for chunk in assistant_response.split():
         full_response += chunk + " "
         time.sleep(0.05)
         # Add a blinking cursor to simulate typing
         message_placeholder.markdown(full_response + "▌")
-    message_placeholder.markdown(final_response)
+    message_placeholder.markdown(full_response)
 # Add assistant response to chat history
 st.session_state.messages.append({"role": "assistant", "content": final_response})