Add base kubernetes support final fix 4

frontend/src/components/domain/onboarding/steps/MLTrainingStep.tsx

@@ -1,7 +1,7 @@
 import React, { useState, useCallback, useEffect } from 'react';
 import { Button } from '../../../ui/Button';
 import { useCurrentTenant } from '../../../../stores/tenant.store';
-import { useCreateTrainingJob, useTrainingWebSocket } from '../../../../api/hooks/training';
+import { useCreateTrainingJob, useTrainingWebSocket, useTrainingJobStatus } from '../../../../api/hooks/training';
 
 interface MLTrainingStepProps {
   onNext: () => void;
@@ -85,6 +85,63 @@ export const MLTrainingStep: React.FC<MLTrainingStepProps> = ({
     } : undefined
   );
 
+  // Smart fallback polling - automatically disabled when WebSocket is connected
+  const { data: jobStatus } = useTrainingJobStatus(
+    currentTenant?.id || '',
+    jobId || '',
+    {
+      enabled: !!jobId && !!currentTenant?.id,
+      isWebSocketConnected: isConnected, // This will disable HTTP polling when WebSocket is connected
+    }
+  );
+
+  // Handle training status updates from HTTP polling (fallback only)
+  useEffect(() => {
+    if (!jobStatus || !jobId || trainingProgress?.stage === 'completed') {
+      return;
+    }
+
+    console.log('📊 HTTP fallback status update:', jobStatus);
+
+    // Check if training completed via HTTP polling fallback
+    if (jobStatus.status === 'completed' && trainingProgress?.stage !== 'completed') {
+      console.log('✅ Training completion detected via HTTP fallback');
+      setTrainingProgress({
+        stage: 'completed',
+        progress: 100,
+        message: 'Entrenamiento completado exitosamente (detectado por verificación HTTP)'
+      });
+      setIsTraining(false);
+
+      setTimeout(() => {
+        onComplete({
+          jobId: jobId,
+          success: true,
+          message: 'Modelo entrenado correctamente',
+          detectedViaPolling: true
+        });
+      }, 2000);
+    } else if (jobStatus.status === 'failed') {
+      console.log('❌ Training failure detected via HTTP fallback');
+      setError('Error detectado durante el entrenamiento (verificación de estado)');
+      setIsTraining(false);
+      setTrainingProgress(null);
+    } else if (jobStatus.status === 'running' && jobStatus.progress !== undefined) {
+      // Update progress if we have newer information from HTTP polling fallback
+      const currentProgress = trainingProgress?.progress || 0;
+      if (jobStatus.progress > currentProgress) {
+        console.log(`📈 Progress update via HTTP fallback: ${jobStatus.progress}%`);
+        setTrainingProgress(prev => ({
+          ...prev,
+          stage: 'training',
+          progress: jobStatus.progress,
+          message: jobStatus.message || 'Entrenando modelo...',
+          currentStep: jobStatus.current_step
+        }) as TrainingProgress);
+      }
+    }
+  }, [jobStatus, jobId, trainingProgress?.stage, onComplete]);
+
   // Auto-trigger training when component mounts
   useEffect(() => {
     if (currentTenant?.id && !isTraining && !trainingProgress && !error) {