Fix data fetch 7

services/training/app/api/training.py

@@ -153,7 +153,8 @@ async def get_training_job(
     job_id: str,
     tenant_id: UUID = Path(..., description="Tenant ID"),
     current_user: Dict[str, Any] = Depends(get_current_user_dep),
-    training_service: TrainingService = Depends(get_training_service)
+    training_service: TrainingService = Depends(get_training_service),
+    db: AsyncSession = Depends(get_db_session)
 ):
     """Get specific training job details"""
     try:
@@ -164,17 +165,24 @@ async def get_training_job(
                     job_id=job_id,
                     tenant_id=tenant_id_str)
         
-        job = await training_service.get_training_job(job_id)
+        job_log = await training_service.get_job_status(db, job_id, tenant_id_str)
         
         # Verify tenant access
-        if job.tenant_id != tenant_id:
+        if job_log.tenant_id != tenant_id:
             logger.warning("Unauthorized job access attempt", 
                          job_id=job_id,
                          tenant_id=str(tenant_id),
                          job_tenant_id=job.tenant_id)
             raise HTTPException(status_code=404, detail="Job not found")
         
-        return job
+        return TrainingJobResponse(
+            job_id=job_log.job_id,
+            status=TrainingStatus(job_log.status),
+            message=_generate_status_message(job_log.status, job_log.current_step),
+            tenant_id=str(job_log.tenant_id),
+            created_at=job_log.start_time,
+            estimated_duration_minutes=_estimate_duration(job_log.status, job_log.progress)
+        )
         
     except HTTPException:
         raise
@@ -501,4 +509,31 @@ async def retrain_all_products(
         logger.error("Failed to start retraining", 
                     error=str(e),
                     tenant_id=tenant_id)
-        raise HTTPException(status_code=500, detail=f"Failed to start retraining: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Failed to start retraining: {str(e)}")
+    
+def _generate_status_message(status: str, current_step: str) -> str:
+    """Generate appropriate status message"""
+    status_messages = {
+        "pending": "Training job is queued",
+        "running": f"Training in progress: {current_step}",
+        "completed": "Training completed successfully",
+        "failed": "Training failed",
+        "cancelled": "Training was cancelled"
+    }
+    return status_messages.get(status, f"Status: {status}")
+
+def _estimate_duration(status: str, progress: int) -> int:
+    """Estimate remaining duration in minutes"""
+    if status == "completed":
+        return 0
+    elif status == "failed" or status == "cancelled":
+        return 0
+    elif status == "pending":
+        return 30  # Default estimate
+    else:  # running
+        if progress > 0:
+            # Rough estimate based on progress
+            remaining_progress = 100 - progress
+            return max(1, int((remaining_progress / max(progress, 1)) * 10))
+        else:
+            return 25  # Default for running jobs