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Test and Evaulate Contoso-Chat with Promptflow #18

Test and Evaulate Contoso-Chat with Promptflow

Test and Evaulate Contoso-Chat with Promptflow #18

name: Test and Evaulate Contoso-Chat with Promptflow
on:
workflow_dispatch:
env:
GROUP: ${{secrets.GROUP}}
WORKSPACE: ${{secrets.WORKSPACE}}
SUBSCRIPTION: ${{secrets.SUBSCRIPTION}}
RUN_NAME: contoso_chat
EVAL_RUN_NAME: contoso_chat_eval
jobs:
login-runpf-evalpf-assertpf-registermodel:
runs-on: ubuntu-latest
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: Set up Python
uses: actions/setup-python@v2
with:
python-version: '3.11.4'
- name: List current directory
run: ls
- name: Install promptflow
run: pip install -r contoso-chat/requirements.txt
- name: Run promptflow
run: |
pfazure run create -f contoso-chat/run.yml --subscription ${{env.SUBSCRIPTION}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}} --stream > run_info.txt
cat run_info.txt
- name: List current directory
run: ls
- name: Set run name
run: |
echo "RUN_NAME=$(python deployment/llmops-helper/parse_run_output.py run_info.txt)" >> "$GITHUB_ENV"
- name: Show the current run name
run: echo "Run name is:" ${{env.RUN_NAME}}
- name: Show promptflow results
run: pfazure run show-details --name ${{env.RUN_NAME}} --subscription ${{env.SUBSCRIPTION}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}}
- name: Run promptflow evaluations
run: |
pfazure run create -f contoso-chat/run_evaluation_multi.yml --run ${{env.RUN_NAME}} --subscription ${{env.SUBSCRIPTION}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}} --stream > eval_info.txt
cat eval_info.txt
- name: Get eval run name
run: echo "EVAL_RUN_NAME=$(python deployment/llmops-helper/parse_run_output.py eval_info.txt)" >> "$GITHUB_ENV"
- name: Show the current eval run name
run: echo "Eval run name is:" ${{env.EVAL_RUN_NAME}}
- name: Show promptflow details
run: pfazure run show-details --name ${{env.EVAL_RUN_NAME}} --subscription ${{env.SUBSCRIPTION}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}}
- name: Show promptflow metrics
run: |
pfazure run show-metrics --name ${{env.EVAL_RUN_NAME}} --subscription ${{env.SUBSCRIPTION}} -g ${{env.GROUP}} -w ${{env.WORKSPACE}} > eval_result.json
cat eval_result.json
- name: List current directory
run: ls
- name: Get assert eval results
id: jobMetricAssert
run: |
# NOTE The number after the file is the threshold score to pass the assertion.
export ASSERT=$(python deployment/llmops-helper/assert.py eval_result.json 3) # NOTE <file>.json is the file name and decimal is the threshold for the assertion
echo "::debug::Assert has returned the following value: $ASSERT"
# assert.py will return True or False, but bash expects lowercase.
if ${ASSERT,,} ; then
echo "::debug::Prompt flow run met the quality bar and can be deployed."
echo "::set-output name=result::true"
else
echo "::warning::Prompt flow run didn't meet quality bar."
echo "::set-output name=result::false"
fi
- name: Show the assert result
run: echo "Assert result is:" ${{ steps.jobMetricAssert.outputs.result }}
- name: Register promptflow model
if: ${{ steps.jobMetricAssert.outputs.result == 'true' }}
run: az ml model create --file deployment/chat-model.yaml -g ${{env.GROUP}} -w ${{env.WORKSPACE}}