name: Build and test model using a dummy prediction pipeline

on:
  # push:
  #   branches:
  #     - "model-**"
  pull_request:
    branches: ["sap-dev", "heat-dev", "carbon-dev"]
  label:
    types: ["created", "edited"]

permissions: write-all

jobs:

  Check-Label:
    runs-on: ubuntu-latest
    steps:
    - uses: yogevbd/enforce-label-action@2.1.0
      with:
        REQUIRED_LABELS_ANY: "major,minor,patch"
        REQUIRED_LABELS_ANY_DESCRIPTION: "Select at least one label ['major','minor','patch']"
        BANNED_LABELS: "banned"

  # 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/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
        dvc pull -r experiments

    - name: Build Prediction docker Image
      run: |
        cd modules/ml-pipeline/src/
        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/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
        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 }}
        TARGET_BRANCH: ${{ github.base_ref }}
      run: |
        cd modules/ml-pipeline/src/pipeline
        echo "## Model metrics" > report.md

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

        echo "## Scenario comparison" >> report.md

        cat metrics/scenario_table.md >> report.md

        echo "" >> report.md

        echo "## Scenario metrics" >> report.md

        cat metrics/scenario_metrics.md >> 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