Update app.py

app.py

@@ -2080,8 +2080,7 @@ def create_enhanced_ui():
                 if not allowed:
                     logger.warning(f"Rate limit exceeded")
                     metrics = business_metrics.get_metrics()
-                    return (
-                        rate_msg, {}, {}, gr.Dataframe(value=[]),
+                    return (rate_msg, {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2101,8 +2100,7 @@ def create_enhanced_ui():
                     error_msg = f"❌ Invalid input types: {str(e)}"
                     logger.warning(error_msg)
                     metrics = business_metrics.get_metrics()
-                    return (
-                        error_msg, {}, {}, gr.Dataframe(value=[]),
+                    return (error_msg, {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2118,8 +2116,7 @@ def create_enhanced_ui():
                 if not is_valid:
                     logger.warning(f"Invalid input: {error_msg}")
                     metrics = business_metrics.get_metrics()
-                    return (
-                        error_msg, {}, {}, gr.Dataframe(value=[]),
+                    return (error_msg, {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2136,8 +2133,7 @@ def create_enhanced_ui():
                 # Handle errors
                 if 'error' in result:
                     metrics = business_metrics.get_metrics()
-                    return (
-                        f"❌ {result['error']}", {}, {}, gr.Dataframe(value=[]),
+                    return (f"❌ {result['error']}", {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2199,11 +2195,7 @@ def create_enhanced_ui():
                     output_msg,
                     agent_insights_data,
                     predictive_insights_data,
-                    gr.Dataframe(
-                        headers=["Timestamp", "Component", "Latency", "Error Rate", "Throughput", "Severity", "Analysis"],
-                        value=table_data,
-                        wrap=True
-                    ),
+                    gr.update(value=table_data),
                     metrics["total_incidents"],
                     metrics["incidents_auto_healed"],
                     metrics["auto_heal_rate"],
@@ -2216,8 +2208,7 @@ def create_enhanced_ui():
                 error_msg = f"❌ Error processing event: {str(e)}"
                 logger.error(error_msg, exc_info=True)
                 metrics = business_metrics.get_metrics()
-                return (
-                    error_msg, {}, {}, gr.Dataframe(value=[]),
+                return (error_msg, {}, {}, gr.update(value=[]),
                     metrics["total_incidents"],
                     metrics["incidents_auto_healed"],
                     metrics["auto_heal_rate"],