changed python file for chatbot demo to 'demo_chatbot' and added some error handling in case the user has required files missing.

chatbotlib/{chatbot_demo.py → demo_chatbot.py}

@@ -28,12 +28,9 @@ def run_app():
     from streamlit_chat import message
 
     from keras.models import load_model
-    chatbot_model = load_model('chatbot_model.h5')
 
-    # Load commands and preprocessed data
+    # Load commands
     commands = json.loads(open('commands.json').read())
-    words = pickle.load(open('words.pkl', 'rb'))
-    classes = pickle.load(open('classes.pkl', 'rb'))
 
     ######################################
     # :: HELPER FUNCTIONS FOR PROCESSING #
@@ -212,6 +209,26 @@ def run_app():
     NLP Chatbot is a conversational chat bot. Begin by entering in a prompt below. 
     """
     )
+
+    try:
+        # Load preprocessed data and the model
+        words = pickle.load(open('words.pkl', 'rb'))
+        classes = pickle.load(open('classes.pkl', 'rb'))
+        chatbot_model = load_model('chatbot_model.h5')
+        
+    except Exception as e:
+            st.error("An error occurred from missing a generated file...")
+            st.error(str(e))
+            st.info("""
+                    Double check if you followed all the steps in **Train the Chatbot Model** prior to running the demo.
+                    
+                    - Upload the commands.json file for processing
+                    - Load the pickle data
+                    - Create training data
+                    - Build the model
+                    
+                    """)
+    
     # Explanation of code using st.markdown with bullet points
     st.markdown("""
     - This chatbot app offers the following options:

index.py

@@ -1,6 +1,6 @@
 import streamlit as st
 from streamlit_option_menu import option_menu
-from chatbotlib import (train_chatbot, chatbot_demo)
+from chatbotlib import (train_chatbot, demo_chatbot)
 
 # displaying the icon image on streamlit app and set the page config.
 st.set_page_config(
@@ -40,4 +40,4 @@ match page_selection:
         train_chatbot.run_app()
 
     case "Demo the Chatbot":
-        chatbot_demo.run_app()
+        demo_chatbot.run_app()