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named_entity_recognition_post_prod_eval.yml
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name: named_entity_recognition_post_production_evaluation
on:
workflow_dispatch:
inputs:
flow_type:
description: "Flow type to execute"
required: true
default: "named_entity_recognition"
env_name:
description: "Environment name"
required: true
default: "postprodeval"
jobs:
post_production_evaluation:
runs-on: ubuntu-latest
env:
RESOURCE_GROUP_NAME: ${{ vars.RESOURCE_GROUP_NAME }}
WORKSPACE_NAME: ${{ vars.WORKSPACE_NAME }}
steps:
- name: Checkout Actions
uses: actions/checkout@v4
- name: Azure login
uses: azure/login@v1
with:
creds: ${{ secrets.azure_credentials }}
- name: Configure Azure ML Agent
uses: ./.github/actions/configure_azureml_agent
with:
versionSpec: "3.9"
base_path: ${{ inputs.flow_type }}
- name: load the current Azure subscription details
id: subscription_details
shell: bash
run: |
export subscriptionId=$(az account show --query id -o tsv)
echo "SUBSCRIPTION_ID=$subscriptionId" >> $GITHUB_OUTPUT
- name: Register experiment data asset
uses: ./.github/actions/execute_script
with:
step_name: "Register experiment data asset"
script_parameter: |
python -m llmops.common.register_data_asset \
--subscription_id ${{ steps.subscription_details.outputs.SUBSCRIPTION_ID }} \
--file "experiment-postprod.yaml" \
--base_path "named_entity_recognition" \
--env_name "postprodeval"
- name: Execute prompt flow bulk evaluation
uses: ./.github/actions/execute_script
with:
step_name: "Execute prompt flow bulk evaluation"
script_parameter: |
python -m llmops.common.prompt_pipeline \
--subscription_id ${{ steps.subscription_details.outputs.SUBSCRIPTION_ID }} \
--build_id ${{ github.run_id }} \
--base_path "named_entity_recognition" \
--file "experiment-postprod.yaml" \
--env_name "postprodeval" \
--output_file run_id.txt
- name: Archive CSV
uses: actions/upload-artifact@v3
with:
name: evaluation-reports
path: ./reports