Detect if MLFlow Model was updated

.github/workflows/assets-validation.yaml

@@ -7,6 +7,12 @@ on:
   pull_request:
     branches:
       - main
+    types:
+      - opened
+      - labeled
+      - unlabeled
+      - synchronize
+      - reopened
   workflow_dispatch:
     inputs:
       asset_dirs:
@@ -71,10 +77,17 @@ jobs:
         run: pip install -e $scripts_azureml_assets_dir
 
       - name: Validate assets
+        id: validate_assets
         run: python -u $scripts_assets_dir/validate_assets.py -i "${{ github.event.inputs.asset_dirs || env.default_asset_dirs }}" -a $asset_config_filename -c "${{ needs.check-directory-file-changes.outputs.files-changed }}" -n -I -C -b -t -e
         env:
           SUBSCRIPTION_ID: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
 
+      - name: Check PR labels for "mlflow noncompliant exception" label if MLFlow model was detected
+        if: fromJSON(steps.validate_assets.outputs.mlflow_model_detected || 'false') && !contains(github.event.pull_request.labels.*.name, 'mlflow noncompliant exception')
+        run: |
+          echo "::error::This PR contains an MLFlow model which is banned from the model catalog. Please reach out to System Registry Content team if you have any questions."
+          exit 1
+
       - name: Validate source tree
         run: python -u $scripts_assets_dir/validate_tree.py -i "${{ github.event.inputs.asset_dirs || env.default_asset_dirs }}"
 

scripts/azureml-assets/CHANGELOG.md

@@ -1,6 +1,10 @@
 ## 1.17.0 (Unreleased)
 ### 🚀 New Features
 
+## 1.16.84 (2025-05-29)
+### 🚀 New Features
+- [#4207](https://github.com/Azure/azureml-assets/pull/4207) Detect if MLFlow model was updated
+
 ## 1.16.83 (2025-05-22)
 ### 🚀 New Features
 - [#4208](https://github.com/Azure/azureml-assets/pull/4208) Fix for python 3.9 - remove union typing

scripts/azureml-assets/azureml/assets/validate_assets.py

@@ -946,6 +946,32 @@ def validate_model_spec(asset_config: assets.AssetConfig) -> int:
     return error_count
 
 
+def validate_mlflow_model(asset_config: assets.AssetConfig) -> int:
+    """Validate if model is of type MLFlow.
+
+    Args:
+        asset_config (assets.AssetConfig): asset config for model spec
+    """
+    model_config = None
+
+    try:
+        load_model(asset_config.spec_with_path)
+        model_config: assets.ModelConfig = asset_config.extra_config_as_object()
+    except Exception:
+        logger.log_warning("Could not validate if model is of type MLFlow due to invalid spec or model config")
+        return
+
+    if model_config.type == assets.config.ModelType.MLFLOW:
+        logger.log_warning(f"{asset_config.name} is a model of type {model_config.type.value} "
+                           f"which is banned from the model catalog")
+
+        # Update mlflow_model_detected variable for Github Actions only
+        if "GITHUB_OUTPUT" in os.environ:
+            logger.print("Setting GITHUB_OUTPUT env variable for mlflow_model_detected=true")
+            with open(os.environ["GITHUB_OUTPUT"], "a") as f:
+                print("mlflow_model_detected=true", file=f)
+
+
 def get_validated_models_assets_map(model_validation_results_dir: str):
     """Return model assets map."""
     try:
@@ -1083,6 +1109,10 @@ def validate_assets(input_dirs: List[Path],
             if check_tests:
                 error_count += validate_tests(asset_config)
 
+            # Validate if MLFlow model
+            if asset_config.type == assets.AssetType.MODEL:
+                validate_mlflow_model(asset_config)
+
             if asset_config.type == assets.AssetType.ENVIRONMENT:
                 # Validate Dockerfile
                 error_count += validate_dockerfile(asset_config.extra_config_as_object())

scripts/azureml-assets/setup.py

@@ -7,7 +7,7 @@
 
 setup(
    name="azureml-assets",
-   version="1.16.83",
+   version="1.16.84",
    description="Utilities for publishing assets to Azure Machine Learning system registries.",
    author="Microsoft Corp",
    packages=find_packages(),