mlops-workflow.yml

name: ML Ops Workflow

on: [push]

env:
    workspace-name: aml-ws-mlops
    resource-group: rg-mlops
    sub-id: 20671c75-cecd-4a9d-9dfb-98defacfaec2

permissions:
    id-token: write
    contents: read

jobs:
  build-and-deploy:
    runs-on: ubuntu-latest
    environment:
        name: dev

    steps:
    - name: Checkout repository
      uses: actions/checkout@v2

    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: '3.8'

    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r ./ml/requirements.txt

    -   name: "Az CLI login"
        uses: azure/login@v1
        with:
            client-id: ${{ secrets.AZURE_CLIENT_ID }}
            tenant-id: ${{ secrets.AZURE_TENANT_ID }}
            subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}

    - name: Set up Azure Machine Learning
      run: |
        az extension add -n azure-cli-ml

    - name: Upload dataset
      run: |
        az ml dataset create -f ./ml/data.yaml --workspace-name ${{ env.workspace-name }} --resource-group ${{ env.resource-group }}

    - name: Submit training run
      run: |
        az ml job create --file ./ml/train.yaml --workspace-name ${{ env.workspace-name }} --resource-group ${{ env.resource-group }}

    # - name: Register the model
    #   run: |
    #     az ml job create --file register_model.yaml

    # - name: Deploy the model
    #   run: |
    #     az ml job create --file deploy_model.yaml

    # - name: Test the deployment
    #   run: |
    #     python test_deployment.py