Create app.py

app.py

@@ -40,6 +40,7 @@ from models import (
 )
 from claude_adapter import get_claude_adapter
 from healing_policies import PolicyEngine, DEFAULT_HEALING_POLICIES
+from voice_narrator import VoiceHandler
 
 # === Logging Configuration ===
 logging.basicConfig(
@@ -1544,6 +1545,39 @@ class EnhancedReliabilityEngine:
             logger.error(f"Failed to enhance with Claude: {e}")
             # Continue without enhancement
         
+        # === Generate voice alert for anomalies ===
+        if is_anomaly and voice_handler:
+            try:
+                # Extract diagnosis and action from results
+                diagnosis = "System anomaly detected"
+                action = "INVESTIGATE"
+                
+                if agent_analysis and 'recommended_actions' in agent_analysis:
+                    actions = agent_analysis['recommended_actions']
+                    if actions:
+                        diagnosis = actions[0][:100]  # First recommendation, truncated
+                
+                if healing_actions:
+                    action = healing_actions[0].value if healing_actions else "INVESTIGATE"
+                
+                # Generate voice alert
+                logger.info(f"Generating voice alert for {component}")
+                audio_file = voice_handler.speak_alert(
+                    diagnosis=diagnosis,
+                    action=action,
+                    output_filename=f"alert_{component}_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.mp3"
+                )
+                
+                if audio_file:
+                    result['audio_file'] = audio_file
+                    logger.info(f"✅ Voice alert generated: {audio_file}")
+                else:
+                    logger.warning("Voice generation returned no file")
+                    
+            except Exception as e:
+                logger.error(f"Voice generation failed (non-critical): {e}", exc_info=True)
+        # === End voice integration ===
+        
         return result
     
     async def enhance_with_claude(
@@ -1631,6 +1665,9 @@ Focus on clarity, accuracy, and decisive recommendations."""
 # === Initialize Engine (with dependency injection) ===
 enhanced_engine = EnhancedReliabilityEngine()
 
+# === Initialize Voice Handler ===
+voice_handler = VoiceHandler()
+logger.info("Voice handler initialized")
 
 # === Rate Limiting ===
 class RateLimiter:
@@ -1725,6 +1762,15 @@ def create_enhanced_ui():
                     lines=6
                 )
                 
+                # === ADD AUDIO PLAYER ===
+                audio_output = gr.Audio(
+                    label="🔊 Voice Alert",
+                    type="filepath",
+                    visible=False,
+                    autoplay=True
+                )
+                # === END AUDIO PLAYER ===
+                
                 with gr.Accordion("🤖 Agent Specialists Analysis", open=False):
                     gr.Markdown("""
                     **Specialized AI Agents:**
@@ -1814,7 +1860,7 @@ def create_enhanced_ui():
                 allowed, rate_msg = rate_limiter.is_allowed()
                 if not allowed:
                     logger.warning(f"Rate limit exceeded")
-                    return rate_msg, {}, {}, "*Rate limit exceeded*", gr.Dataframe(value=[])
+                    return rate_msg, {}, {}, "*Rate limit exceeded*", gr.Dataframe(value=[]), gr.Audio(visible=False)
                 
                 # Type conversion
                 try:
@@ -1826,7 +1872,7 @@ def create_enhanced_ui():
                 except (ValueError, TypeError) as e:
                     error_msg = f"❌ Invalid input types: {str(e)}"
                     logger.warning(error_msg)
-                    return error_msg, {}, {}, "*Invalid input type*", gr.Dataframe(value=[])
+                    return error_msg, {}, {}, "*Invalid input type*", gr.Dataframe(value=[]), gr.Audio(visible=False)
                 
                 # Input validation
                 is_valid, error_msg = validate_inputs(
@@ -1834,7 +1880,7 @@ def create_enhanced_ui():
                 )
                 if not is_valid:
                     logger.warning(f"Invalid input: {error_msg}")
-                    return error_msg, {}, {}, "*Validation failed*", gr.Dataframe(value=[])
+                    return error_msg, {}, {}, "*Validation failed*", gr.Dataframe(value=[]), gr.Audio(visible=False)
                 
                 # FIXED: Direct async call - no event loop creation needed
                 result = await enhanced_engine.process_event_enhanced(
@@ -1843,7 +1889,7 @@ def create_enhanced_ui():
                 
                 # Handle errors
                 if 'error' in result:
-                    return f"❌ {result['error']}", {}, {}, "*Error occurred*", gr.Dataframe(value=[])
+                    return f"❌ {result['error']}", {}, {}, "*Error occurred*", gr.Dataframe(value=[]), gr.Audio(visible=False)
                 
                 # Build table data (THREAD-SAFE)
                 table_data = []
@@ -1905,6 +1951,14 @@ def create_enhanced_ui():
 *Model: {claude_synthesis.get('source', 'claude-opus-4')}*
 """
                 
+                # === Extract audio file if present ===
+                audio_file = result.get('audio_file', None)
+                audio_visible = audio_file is not None
+                
+                if audio_file:
+                    logger.info(f"Audio alert available: {audio_file}")
+                # === End audio extraction ===
+                
                 return (
                     output_msg,
                     agent_insights_data,
@@ -1914,19 +1968,20 @@ def create_enhanced_ui():
                         headers=["Timestamp", "Component", "Latency", "Error Rate", "Throughput", "Severity", "Analysis"],
                         value=table_data,
                         wrap=True
-                    )
+                    ),
+                    gr.Audio(value=audio_file, visible=audio_visible)
                 )
                 
             except Exception as e:
                 error_msg = f"❌ Error processing event: {str(e)}"
                 logger.error(error_msg, exc_info=True)
-                return error_msg, {}, {}, "*Processing error*", gr.Dataframe(value=[])
+                return error_msg, {}, {}, "*Processing error*", gr.Dataframe(value=[]), gr.Audio(visible=False)
         
         # FIXED: Use async handler directly
         submit_btn.click(
             fn=submit_event_enhanced_async,
             inputs=[component, latency, error_rate, throughput, cpu_util, memory_util],
-            outputs=[output_text, agent_insights, predictive_insights, claude_output, events_table]
+            outputs=[output_text, agent_insights, predictive_insights, claude_output, events_table, audio_output]
         )
     
     return demo