Update app.py

app.py

@@ -56,58 +56,61 @@ units = st.slider(
 )
 
 
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
+# for message in st.session_state.messages:
+#     with st.chat_message(message["role"]):
+#         st.markdown(message["content"])
 
+assistant = st.chat_message("assistant")
+assistant.write("How can I help you today?")
 
-### GPT Response
-# Display assistant response in chat message container
-with st.chat_message("assistant"):
+def assistant_response(response):
     message_placeholder = st.empty()
     full_response = ""
-    assistant_response = "How can I help you today?"
+    assistant_response = response
     # 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})
-
-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)
-
-    if assistant_response:
-        with st.chat_message("assistant"):
-            message_placeholder = st.empty()
-            full_response = ""
-            # 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})
+        assistant.markdown(full_response + "▌")
+    assistant.markdown(full_response)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": full_response})
+
+assistant_response("Yah I'm tired af right now boi")
+
+
+# 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 = results_agent(result_query, OPENAI_API)
+
+#     if assistant_response:
+#         with st.chat_message("assistant"):
+#             message_placeholder = st.empty()
+#             full_response = ""
+#             # 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})