ML/.github/workflows/MLPipelinePullRequest.yml

name: Build and test model using a dummy prediction pipeline

on:
  # push:
  #   branches:
  #     - "model-**"
  pull_request:
    branches: [ "master" ]
  label:
    types: ["created", "edited"]

permissions: write-all

jobs:

  No-Label:
    if: ${{ github.event.label.name != 'major' }} || ${{ github.event.label.name != 'minor' }}  || ${{ github.event.label.name != 'patch' }}
    runs-on: ubuntu-latest

    steps:
    - name: No label associated with PR
      run: |
        echo "Please choose one of these tags: 'major', 'major', 'patch'"
        exit(1)

  # Verify-Model:

  #   runs-on: ubuntu-latest

  #   steps:
  #   - uses: actions/checkout@v3
  #   - name: Install packages to retrieve artifacts
  #     env:
  #       AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
  #       AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
  #     run: |
  #       pip install --upgrade pip
  #       pip install -r modules/ml-pipeline/src/pipeline/src/requirements/version_control/requirements.txt

  #   - name: Retrieve artifacts (dvc.lock)
  #     env:
  #       AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
  #       AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
  #     run: |
  #       cd modules/ml-pipeline/src/pipeline/src
  #       dvc pull -r experiments

  #   - name: Build Prediction docker Image
  #     run: |
  #       cd modules/ml-pipeline/src/pipeline/
  #       docker build . --file Prediction.Dockerfile --tag prediction_test

  #   - name: Run Prediction docker container
  #     run: |
  #       docker run prediction_test

  # Trigger-CML:

  #   runs-on: ubuntu-latest

  #   steps:
  #   - uses: actions/checkout@v3
  #   - name: Install packages to retrieve artifacts
  #     run: |
  #       pip install --upgrade pip
  #       pip install -r modules/ml-pipeline/src/pipeline/src/requirements/version_control/requirements.txt

  #   - name: Retrieve artifacts (dvc.lock)
  #     env:
  #       AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
  #       AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
  #     run: |
  #       cd modules/ml-pipeline/src/pipeline/src
  #       dvc pull -r experiments

  #   - uses: actions/setup-python@v4
  #   - uses: iterative/setup-cml@v1
  #   - name: Generate report
  #     env:
  #       AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
  #       AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
  #       REPO_TOKEN: ${{ secrets.GITHUB_TOKEN }}
  #     run: |
  #       cd modules/ml-pipeline/src/pipeline/src
  #       echo "## Model metrics" > report.md

  #       # Compare metrics to master
  #       git fetch --depth=1 origin master:master
  #       dvc metrics diff --md --all master >> report.md

  #       cml comment create report.md

    #     # echo "## Residuals plot from model" >> report.md
    #     # metrics_location=$(find . -maxdepth 10 -name "residuals.png")
    #     # echo $metrics_location
    #     # cd $metric_location
    #     # echo "![](./residuals.png)" >> report.md