Skip to content

Refactor update train-deploy project #4

Refactor update train-deploy project

Refactor update train-deploy project #4

name: Staging Trigger Train and Deploy Pipeline
on:
pull_request:
types: [opened, synchronize]
branches: [staging, main]
paths:
- 'train_and_deploy/**'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
run-staging-workflow:
runs-on: ubuntu-latest
env:
ZENML_STORE_URL: ${{ secrets.ZENML_PROJECTS_HOST }}
ZENML_STORE_API_KEY: ${{ secrets.ZENML_PROJECTS_API_KEY }}
ZENML_STAGING_STACK : ef6c474d-b6e7-49a7-a046-0dab39f7969a # Set this to your staging stack ID
ZENML_GITHUB_SHA: ${{ github.event.pull_request.head.sha }}
ZENML_GITHUB_URL_PR: ${{ github.event.pull_request._links.html.href }}
ZENML_DEBUG: true
ZENML_ANALYTICS_OPT_IN: false
ZENML_LOGGING_VERBOSITY: INFO
ZENML_DISABLE_CLIENT_SERVER_MISMATCH_WARNING: True
steps:
- name: Check out repository code
uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install requirements
working-directory: ./train_and_deploy
run: |
pip3 install -r requirements.txt
zenml integration install bentoml skypilot_kubernetes s3 aws evidently --uv -y
- name: Connect to ZenML server
working-directory: ./train_and_deploy
run: |
zenml init
- name: Set stack (Staging)
working-directory: ./train_and_deploy
run: |
zenml stack set ${{ env.ZENML_STAGING_STACK }}
- name: Run pipeline (Staging)
working-directory: ./train_and_deploy
run: |
python run.py --training