Model HMS to UC #1
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| # Name of the workflow | |
| name: Model HMS to UC | |
| # Trigger the workflow manually through the GitHub UI and accept input parameters | |
| on: | |
| workflow_dispatch: | |
| inputs: | |
| model_name: | |
| description: 'Model Name' # Input for the name of the model to export (source_catalog.schema.model) | |
| required: true | |
| default: 'fclrmodel' | |
| des_model_name: | |
| description: 'Destination Model Name' # Input for the name of the destination model (des_catalog.schema.model) | |
| required: true | |
| default: 'gannychan1.default.fclrmodel' | |
| experiment_name: | |
| description: 'Experiment Name' # Input for the name of the experiment associated with the model | |
| required: true | |
| default: 'fclrmodel_experiment1' | |
| stages: | |
| description: 'Stages' # Input for stages to export; None means all stages | |
| required: false | |
| default: 'None' | |
| export_latest_version_only: | |
| description: 'Export Latest Version Only' # Input for whether to export only the latest version of the model | |
| required: false | |
| default: 'True' | |
| notebook_format: | |
| description: 'Notebook Format' # Input for the format of the notebooks | |
| required: false | |
| default: 'SOURCE' | |
| jobs: | |
| export-import-model: | |
| runs-on: ubuntu-latest # Specify the environment to run this job, using the latest Ubuntu version | |
| env: | |
| # Environment variables sourced from the workflow dispatch inputs | |
| MODEL_NAME: ${{ github.event.inputs.model_name }} # Model name provided by the user | |
| DES_MODEL_NAME: ${{ github.event.inputs.des_model_name }} # Destination model name provided by the user | |
| EXPERIMENT_NAME: ${{ github.event.inputs.experiment_name }} # Experiment name provided by the user | |
| TMP_FOLDER_NAME: "/tmp/${{ github.event.inputs.model_name }}" # Temporary folder for storing the exported model | |
| EXPERIMENT_PATH: "/Shared/${{ github.event.inputs.experiment_name }}" # Path to the experiment in Databricks | |
| STAGES: ${{ github.event.inputs.stages }} # Stages to export, provided by the user | |
| EXPORT_LATEST_VERSION_ONLY: ${{ github.event.inputs.export_latest_version_only }} # Export latest version only, provided by the user | |
| NOTEBOOK_FORMAT: ${{ github.event.inputs.notebook_format }} # Notebook format, provided by the user | |
| # Environment variables sourced from GitHub Secrets for secure access | |
| DATABRICKS_SOURCE_HOST: ${{ secrets.DATABRICKS_SOURCE_HOST }} | |
| DATABRICKS_SOURCE_TOKEN: ${{ secrets.DATABRICKS_SOURCE_TOKEN }} | |
| DATABRICKS_DESTINATION_HOST: ${{ secrets.DATABRICKS_DESTINATION_HOST }} | |
| DATABRICKS_DESTINATION_TOKEN: ${{ secrets.DATABRICKS_DESTINATION_TOKEN }} | |
| steps: | |
| # Step 1: Check out the code from the repository | |
| - name: Check out code | |
| uses: actions/checkout@v4 | |
| # Step 2: Set up Python with the specified version (3.11) | |
| - name: Set up Python | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: '3.11' | |
| # Step 3: Install the mlflow-export-import library from GitHub | |
| - name: Install mlflow-export-import library | |
| run: | |
| pip install git+https://github.com/mlflow/mlflow-export-import/#egg=mlflow-export-import | |
| # Step 4: Display the name of the temporary folder for debugging | |
| - name: Displaying temporary folder name | |
| run: | | |
| echo "Temporary folder: ${{ env.TMP_FOLDER_NAME }}" | |
| # Step 5: Create the temporary folder if it doesn't already exist | |
| - name: Creating a Temp folder | |
| run: | | |
| mkdir -p ${{ env.TMP_FOLDER_NAME }} | |
| # Step 6: Export the model from the source Databricks workspace | |
| - name: Exporting given model | |
| run: | | |
| export MLFLOW_TRACKING_URI=databricks | |
| export DATABRICKS_HOST=${{ env.DATABRICKS_SOURCE_HOST }} | |
| export DATABRICKS_TOKEN=${{ env.DATABRICKS_SOURCE_TOKEN }} | |
| export-model --output-dir ${{ env.TMP_FOLDER_NAME }} --model ${{ env.MODEL_NAME }} --notebook-formats ${{ env.NOTEBOOK_FORMAT }} --export-latest-versions ${{ env.EXPORT_LATEST_VERSION_ONLY }} --stages ${{ env.STAGES }} | |
| # Step 7: List the contents of the temporary folder to verify the export | |
| - name: Listing temp model folder | |
| run: ls -lah ${{ env.TMP_FOLDER_NAME }} | |
| # Step 8: Import the model into the destination Databricks workspace | |
| - name: Importing the model | |
| run: | | |
| export MLFLOW_TRACKING_URI=databricks-uc | |
| export DATABRICKS_HOST=${{ env.DATABRICKS_DESTINATION_HOST }} | |
| export DATABRICKS_TOKEN=${{ env.DATABRICKS_DESTINATION_TOKEN }} | |
| import-model --input-dir ${{ env.TMP_FOLDER_NAME }} --model ${{ env.DES_MODEL_NAME }} --experiment-name ${{ env.EXPERIMENT_PATH }} --delete-model True --verbose True |