Update app.py

app.py

@@ -13,10 +13,21 @@ st.set_page_config(page_title="SQL Agent with Streamlit", page_icon=":bar_chart:
 
 # Sidebar Information
 with st.sidebar:
+    st.write(""" # SQL Agent with Streamlit
+This web app allows you to interact with your data warehouse (DWH) using natural language queries. 
+Simply enter a question, and the app will generate and execute the corresponding SQL query. 
+You can also modify the generated SQL before execution, making it easy to analyze your sales data and view visualizations. 
+Hosted using Streamlit and integrated with Azure SQL Database and OpenAI's GPT-3.5 model, this tool bridges the gap between data analysis and natural language understanding.""")
+       st.write("""This web app allows you to interact with your data warehouse (DWH) using natural language queries. 
+                    Simply enter a question, and the app will generate and execute the corresponding SQL query. 
+                    You can also modify the generated SQL before execution, making it easy to analyze your sales data and view visualizations. 
+                    Hosted using Streamlit and integrated with Azure SQL Database and OpenAI's GPT-3.5 model, this tool bridges the gap between data analysis and natural language understanding.""")
+    
     st.write("## About Me")
     st.write("**Mahmoud Hassanen**") 
     st.write("**[LinkedIn Profile](https://www.linkedin.com/in/mahmoudhassanen99/)**")
 
+
 # Main Page
 st.title("SQL Agent with Streamlit")
 st.header("Analyze Sales Data with Natural Language Queries")
@@ -116,13 +127,6 @@ if "generated_sql" in st.session_state:
                 else:
                     st.warning("No suitable chart found for this data.")
 
-                # Static Seaborn Visualization (Optional)
-                if 'region' in result_df.columns and 'total_sales' in result_df.columns:
-                    st.write("### Total Sales by Region")
-                    fig, ax = plt.subplots()
-                    sns.barplot(x='region', y='total_sales', data=result_df, ax=ax)
-                    st.pyplot(fig)
-
             else:
                 st.error(f"Error executing SQL: {response.json().get('error')}")
         except Exception as e: