Update app.py

app.py

@@ -16,6 +16,15 @@ st.set_page_config(
         'About': "# Midjourney: https://discord.com/channels/@me/997514686608191558"
     }
 )
+
+# AI Query Begin!
+AIQuery = f"Create a streamlit python app which implements this in python functions and appropriate libraries using function based code with annotated parameters and language parts of speech and key words.  Include appropriate emojis for user interface labels with buttons, sidebar, dataframe, expander, and other ui controls. Use a CSV dataset user interface with an outline for **{term}** with subpoints highlighting key aspects, using emojis for visual engagement. Include methodical well ordered rules in code and boldface important entities (for data display use markdown outlines and tables with appropriate emojis for enumerated smart terms) and ruleset elements."
+# AI Query Complete! ---------------------------------------------------------------------------------------------------------------------------------------------------
+
+
+
+
+
 # -----------------------------------------------------------------Art Card Sidebar:
 import base64
 import requests
@@ -182,7 +191,7 @@ def display_buttons_with_scores():
                 query_prefix = f"{key}  **{term}:**"
                 # -----------------------------------------------------------------
                 # query_body = f"Create a detailed outline for **{term}** with subpoints highlighting key aspects, using emojis for visual engagement. Include step-by-step rules and boldface important entities and ruleset elements."
-                query_body = f"Create a streamlit python app.py that implements this in functions using python libraries and short function based code with smart parameters matching language model words including appropriate emojis for functions and a CSV dataset user interface with an outline for **{term}** with subpoints highlighting key aspects, using emojis for visual engagement. Include methodical step-by-step rules in code and always boldface important entities (using markdown outlines and tables for enumerated smart terms) and ruleset elements."
+                query_body = AIQuery
                 response = search_glossary(query_prefix + query_body)
                 
 def fetch_wikipedia_summary(keyword):