Update guardian-pipeline-aws.yml

Author: ShudarshanKongkham

.github/workflows/guardian-pipeline-aws.yml

@@ -89,100 +89,4 @@ jobs:
         run: |
           python Guardian_pipeline_github.py
 
-  deploy-model:
-    runs-on: [self-hosted, Linux, X64, guardian, gpu]
-    needs: run-pipeline
-    if: success()
-    timeout-minutes: 30
-    steps:
-      - name: Check out code
-        uses: actions/checkout@v4
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.11'
-
-      - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install clearml
-
-      - name: Check deployment status
-        env:
-          CLEARML_API_ACCESS_KEY: ${{ secrets.CLEARML_API_ACCESS_KEY }}
-          CLEARML_API_SECRET_KEY: ${{ secrets.CLEARML_API_SECRET_KEY }}
-          CLEARML_API_HOST: ${{ secrets.CLEARML_API_HOST }}
-        run: |
-          echo "🚀 Checking model deployment status..."
-          
-          python3 << 'EOF'
-          from clearml import Model
-          import sys
-          
-          try:
-              print('🔍 Searching for deployed models...')
-              
-              # First check for any published models
-              all_models = Model.query_models(
-                  project_name='Guardian_Training',
-                  model_name='BiLSTM_ActionRecognition',
-                  only_published=True,
-                  max_results=5,
-                  order_by=['-created']
-              )
-              
-              print(f'📋 Found {len(all_models)} published models')
-              
-              deployed_model = None
-              for model in all_models:
-                  print(f'   Model ID: {model.id}')
-                  print(f'   Created: {model.created}')
-                  print(f'   Tags: {model.tags}')
-                  
-                  # Check if this model has deployment tags
-                  if model.tags and any(tag in ['deployed', 'production'] for tag in model.tags):
-                      deployed_model = model
-                      break
-              
-              if deployed_model:
-                  print(f'✅ Found deployed model!')
-                  print(f'🏷️  Model ID: {deployed_model.id}')
-                  print(f'📅 Created: {deployed_model.created}')
-                  print(f'🏷️  Tags: {deployed_model.tags}')
-                  
-                  # Try to get model metadata
-                  try:
-                      design = deployed_model.get_model_design()
-                      if design and 'test_accuracy' in design:
-                          accuracy = design['test_accuracy']
-                          print(f'📊 Test Accuracy: {accuracy:.2f}%')
-                      else:
-                          print('📊 Test Accuracy: Not available in model metadata')
-                  except Exception as e:
-                      print(f'⚠️  Could not get model design: {e}')
-              else:
-                  print('❌ No deployed models found')
-                  if all_models:
-                      print('⚠️  Found published models but none are marked as deployed')
-                      latest = all_models[0]
-                      print(f'   Latest model: {latest.id}')
-                      print(f'   Created: {latest.created}')
-                  else:
-                      print('❌ No published models found at all')
-                  sys.exit(1)
-                  
-          except Exception as e:
-              print(f'❌ Error checking deployment: {e}')
-              import traceback
-              traceback.print_exc()
-              sys.exit(1)
-          EOF
-
-      - name: Notify deployment success
-        if: success()
-        run: |
-          echo "🎉 Guardian AI Pipeline completed successfully!"
-          echo "✅ Model training, optimization, evaluation, and deployment finished"
-          echo "📈 Check ClearML dashboard for detailed results and metrics" 
-          
+