Update app.py

app.py

@@ -261,12 +261,24 @@ with gr.Blocks(title="DataForge - AI CodeAct Agent") as demo:
     )
     
     gr.Markdown("---")
-    gr.Markdown("## 💡 **Example Questions**")
+    gr.Markdown("## 💡 **Real CodeAct Use Cases - When LLMs Fail, Code Succeeds**")
     gr.Markdown("""
-    **🔐 Security:** "Find failed login attempts and suspicious IPs"  
-    **⚡ Performance:** "Identify slowest API endpoints and bottlenecks"  
-    **📊 Data:** "Analyze statistical patterns and outliers"  
-    **🔍 General:** "Summarize key insights and anomalies"
+    **🔥 Real Problem:** You have a 500MB server log file and want to ask: *"Which IP addresses made the most requests yesterday?"*
+    
+    ❌ **Traditional LLM:** "File too large, please upload smaller chunks"  
+    ✅ **DataForge CodeAct:** AI writes Python code with regex + Counter to process entire file → Gets exact answer
+    
+    **🔥 Real Problem:** You have a 2GB CSV with sales data and ask: *"How many orders were placed in each month of 2024?"*
+    
+    ❌ **Traditional LLM:** Crashes on upload or hits token limits  
+    ✅ **DataForge CodeAct:** AI writes pandas code to parse dates and count by month → Simple monthly breakdown
+    
+    **🔥 Real Problem:** You have 1GB of JSON API logs and ask: *"Find all 500 errors and group them by endpoint and time of day"*
+    
+    ❌ **Traditional LLM:** "Cannot process this much data"  
+    ✅ **DataForge CodeAct:** AI writes JSON parsing + datetime analysis code → Complete error breakdown
+    
+    **🎯 The Key:** Instead of sending your data to an LLM, the LLM writes code that processes your data locally!
     """)
 
 if __name__ == "__main__":