deploy-pf-online-endpoint-pipeline.yml

name: Deploy Prompts with Promptflow

on:
  workflow_dispatch:
  workflow_run:
    workflows: ["run-eval-pf-pipeline"]
    branches: [main]
    types:
      - completed

env: 
  GROUP: ${{secrets.GROUP}}
  WORKSPACE: ${{secrets.WORKSPACE}}
  SUBSCRIPTION: ${{secrets.SUBSCRIPTION}}
  RUN_NAME: web_classification_variant_1_20230816_215600_605116
  EVAL_RUN_NAME: classification_accuracy_eval_default_20230821_111809_077086
  ENDPOINT_NAME: web-classification
  DEPLOYMENT_NAME: blue

jobs:
  create-endpoint-and-deploy-pf:
    runs-on: ubuntu-latest
    if: ${{ github.event_name == 'workflow_dispatch' || github.event.workflow_run.conclusion == 'success' }} 
    steps:
    - name: Check out repo
      uses: actions/checkout@v2
    - name: Install az ml extension
      run: az extension add -n ml -y
    - name: Azure login
      uses: azure/login@v1
      with:
        creds: ${{secrets.AZURE_CREDENTIALS}}
    - name: List current directory
      run: ls
    - name: Set default subscription
      run: |
         az account set -s ${{env.SUBSCRIPTION}}
    - name: Create Hash
      run: echo "HASH=$(echo -n $RANDOM | sha1sum | cut -c 1-6)" >> "$GITHUB_ENV"
    - name: Create unique endpoint name   
      run: echo "ENDPOINT_NAME=$(echo 'web-classification-'$HASH)" >> "$GITHUB_ENV"
    - name: Display endpoint name
      run: echo "Endpoint name is:" ${{env.ENDPOINT_NAME}}
    - name: Setup endpoint
      run: az ml online-endpoint create --file promptflow/deployment/endpoint.yaml  --name ${{env.ENDPOINT_NAME}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}}
    - name: Update deployment PRT_CONFIG variable
      run: |
        PRT_CONFIG_OVERRIDE=deployment.subscription_id=${{ env.SUBSCRIPTION }},deployment.resource_group=${{ env.GROUP }},deployment.workspace_name=${{ env.WORKSPACE }},deployment.endpoint_name=${{ env.ENDPOINT_NAME }},deployment.deployment_name=${{ env.DEPLOYMENT_NAME }}
        sed -i "s/PRT_CONFIG_OVERRIDE:.*/PRT_CONFIG_OVERRIDE: $PRT_CONFIG_OVERRIDE/g" promptflow/deployment/deployment.yaml
    - name: Setup deployment
      run: az ml online-deployment create --file promptflow/deployment/deployment.yaml --endpoint-name ${{env.ENDPOINT_NAME}} --all-traffic -g ${{env.GROUP}} -w ${{env.WORKSPACE}}
    - name: Check the status of the endpoint
      run: az ml online-endpoint show -n ${{env.ENDPOINT_NAME}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}}
    - name: Check the status of the deployment
      run: az ml online-deployment get-logs --name blue --endpoint-name ${{env.ENDPOINT_NAME}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}}
    - name: Invoke model
      run: az ml online-endpoint invoke --name ${{env.ENDPOINT_NAME}} --request-file promptflow/deployment/sample-request.json  -g ${{env.GROUP}} -w ${{env.WORKSPACE}}