Update app.py

app.py

@@ -1,5 +1,4 @@
 from config import config
-from config import config
 """
 Enterprise Agentic Reliability Framework - Main Application (FIXED VERSION)
 Multi-Agent AI System for Production Reliability Monitoring
@@ -551,10 +550,6 @@ try:
     from sentence_transformers import SentenceTransformer
     import faiss
     
-# REMOVED:     logger.info("Loading SentenceTransformer model...")
-# REMOVED:     model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
-# REMOVED:     logger.info("SentenceTransformer model loaded successfully")
-    
     if os.path.exists(config.INDEX_FILE):
         logger.info(f"Loading existing FAISS index from {config.INDEX_FILE}")
         index = faiss.read_index(config.INDEX_FILE)
@@ -590,7 +585,7 @@ except Exception as e:
     model = None
     thread_safe_index = None
 
-    # === Predictive Models ===
+# === Predictive Models ===
 class SimplePredictiveEngine:
     """
     Lightweight forecasting engine with proper constant usage
@@ -929,7 +924,7 @@ class BusinessImpactCalculator:
             severity = "LOW"
         
         logger.info(
-            f"Business impact: \{revenue_loss:.2f} revenue loss, "
+            f"Business impact: \${revenue_loss:.2f} revenue loss, "
             f"{affected_users} users, {severity} severity"
         )
         
@@ -988,7 +983,7 @@ class AdvancedAnomalyDetector:
             self.adaptive_thresholds['latency_p99'] = new_threshold
             logger.debug(f"Updated adaptive latency threshold to {new_threshold:.2f}ms")
 
-            # === Multi-Agent System ===
+# === Multi-Agent System ===
 class AgentSpecialization(Enum):
     """Agent specialization types"""
     DETECTIVE = "anomaly_detection"
@@ -1515,7 +1510,7 @@ class OrchestrationManager:
                 unique_actions.append(action)
         return unique_actions[:5]
 
-        # === Enhanced Reliability Engine ===
+# === Enhanced Reliability Engine ===
 class EnhancedReliabilityEngine:
     """
     Main engine for processing reliability events
@@ -2080,7 +2075,8 @@ def create_enhanced_ui():
                 if not allowed:
                     logger.warning(f"Rate limit exceeded")
                     metrics = business_metrics.get_metrics()
-                    return (rate_msg, {}, {}, gr.update(value=[]),
+                    return (
+                        rate_msg, {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2100,7 +2096,8 @@ 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.update(value=[]),
+                    return (
+                        error_msg, {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2116,7 +2113,8 @@ def create_enhanced_ui():
                 if not is_valid:
                     logger.warning(f"Invalid input: {error_msg}")
                     metrics = business_metrics.get_metrics()
-                    return (error_msg, {}, {}, gr.update(value=[]),
+                    return (
+                        error_msg, {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2133,7 +2131,8 @@ def create_enhanced_ui():
                 # Handle errors
                 if 'error' in result:
                     metrics = business_metrics.get_metrics()
-                    return (f"❌ {result['error']}", {}, {}, gr.update(value=[]),
+                    return (
+                        f"❌ {result['error']}", {}, {}, gr.update(value=[]),
                         metrics["total_incidents"],
                         metrics["incidents_auto_healed"],
                         metrics["auto_heal_rate"],
@@ -2195,7 +2194,7 @@ def create_enhanced_ui():
                     output_msg,
                     agent_insights_data,
                     predictive_insights_data,
-                    gr.update(value=table_data),
+                    gr.update(value=table_data),  # FIXED: Using gr.update() instead of gr.Dataframe()
                     metrics["total_incidents"],
                     metrics["incidents_auto_healed"],
                     metrics["auto_heal_rate"],
@@ -2208,7 +2207,8 @@ 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.update(value=[]),
+                return (
+                    error_msg, {}, {}, gr.update(value=[]),
                     metrics["total_incidents"],
                     metrics["incidents_auto_healed"],
                     metrics["auto_heal_rate"],
@@ -2236,8 +2236,11 @@ def create_enhanced_ui():
         )
     
     return demo
-    
-    # === Main Entry Point ===
+
+# Create demo at module level for Hugging Face Spaces
+demo = create_enhanced_ui()
+
+# === Main Entry Point ===
 if __name__ == "__main__":
     logger.info("=" * 80)
     logger.info("Starting Enterprise Agentic Reliability Framework (DEMO READY VERSION)")
@@ -2253,8 +2256,6 @@ if __name__ == "__main__":
     logger.info("=" * 80)
     
     try:
-        demo = create_enhanced_ui()
-        
         logger.info("Launching Gradio UI on 0.0.0.0:7860...")
         demo.launch(
             server_name="0.0.0.0",