Update app.py

app.py

@@ -60,42 +60,37 @@ for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
-if prompt := st.chat_input("What kind of class are you looking for?"):
-    # Display user message in chat message container
+prompt = st.chat_input("What kind of class are you looking for?")
+
+if st.button("Submit"):
     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)
-
-print(results_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(full_response)
-# Add assistant response to chat history
-st.session_state.messages.append({"role": "assistant", "content": full_response})
+    st.session_state.message.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)
+    final_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()
+        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)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": final_response})