ML/.github/workflows/MLPipelinePostMerge.yml

name: Register the model for the given pipeline branch

on:
  push:
    branches:
      - "model-**"

# on:
#   pull_request:
#     types:
#       - closed
#     branches:
#       - "master"

permissions: write-all

jobs:

  # Promote-Model-To-Dev:
  #   if: github.event.pull_request.merged == true
  #   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

  #   - name: Push artifacts to Dev
  #     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 push -r dev


  Register-New-Model-Dev:
    # if: github.event.pull_request.merged == true
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v3
      with:
        fetch-depth: 0

    - name: Install packages to register model
      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: Register Model
      # env:
      #   ACTIONS_STEP_DEBUG: true
      #   GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
      #   token: ${{ secrets.PAT }}
      run: |

        # REGISTER_MODEL_NAME=$(echo ${{ github.event.pull_request.head.ref }} | awk -F"-" '{print $1}')
        REGISTER_MODEL_NAME=$(echo ${{github.ref_name}} | awk -F"-" '{print $1}')

        git config user.name "Github-Bot"
        git config user.email "Github-Bot@no-reply.com"

        gto register test --force --push
        # echo "chicken" >> test.md

        # git fetch --prune
        # git pull origin master
        # git add .
        # git commit -m "test"

        # git push

        # git branch
        # git tag model@v0.0.1
        # git push origin model@v0.0.1
        # git checkout master

        # git remote show origin
        # git status
        # git push origin regression@v0.0.1

        # gto register ${REGISTER_MODEL_NAME} --force
        # gto assign ${REGISTER_MODEL_NAME} --stage dev
        # gto show

  # Register-Prediction-Image-Dev:
  #   needs: Promote-Model-To-Dev
  #   # needs: [Promote-Model-To-Dev, Register-New-Model-Dev] WILL ADD BACK ONCE REGISTER WORKS
  #   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 dev

  #   - name: Build Prediction docker image (TODO - NEED LAMBDA IMAGE, need to add version from gto registry)
  #     run: |
  #       cd modules/ml-pipeline/src/pipeline/
  #       REGISTER_MODEL_NAME=$(echo ${{ github.event.pull_request.head.ref }} | awk -F"-" '{print $1}')
  #       docker build . --file Prediction.Dockerfile --tag ${REGISTER_MODEL_NAME}

  #   - name: ECR Login - Dev
  #     env:
  #       AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
  #       AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
  #     run: |
  #       echo "LOGIN TO ECR"

  #   - name: Push Prediction image to ECR - Dev
  #     env:
  #       AWS_ACCESS_KEY_ID: ${{ secrets.ROBOT_AWS_ACCESS_KEY_ID }}
  #       AWS_SECRET_ACCESS_KEY: ${{ secrets.ROBOT_AWS_SECRET_ACCESS_KEY }}
  #     run: |
  #       echo "PUSH TO ECR"