name: MLflow Prompts Integration Tests

run-name: Run the integration test suite with MLflow Prompt Registry provider

on:
  push:
    branches:
      - main
      - 'release-[0-9]+.[0-9]+.x'
  pull_request:
    branches:
      - main
      - 'release-[0-9]+.[0-9]+.x'
    paths:
      - 'src/llama_stack/providers/remote/prompts/mlflow/**'
      - 'tests/integration/providers/remote/prompts/mlflow/**'
      - 'tests/unit/providers/remote/prompts/mlflow/**'
      - 'uv.lock'
      - 'pyproject.toml'
      - 'requirements.txt'
      - '.github/workflows/integration-mlflow-tests.yml' # This workflow
  schedule:
    - cron: '0 0 * * *'  # Daily at 12 AM UTC

concurrency:
  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
  cancel-in-progress: true

jobs:
  test-mlflow:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        python-version: ${{ github.event.schedule == '0 0 * * *' && fromJSON('["3.12", "3.13"]') || fromJSON('["3.12"]') }}
      fail-fast: false

    steps:
      - name: Checkout repository
        uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0

      - name: Install dependencies
        uses: ./.github/actions/setup-runner
        with:
          python-version: ${{ matrix.python-version }}

      - name: Setup MLflow Server
        run: |
          docker run --rm -d --pull always \
            --name mlflow \
            -p 5555:5555 \
            ghcr.io/mlflow/mlflow:latest \
            mlflow server \
              --host 0.0.0.0 \
              --port 5555 \
              --backend-store-uri sqlite:///mlflow.db \
              --default-artifact-root ./mlruns

      - name: Wait for MLflow to be ready
        run: |
          echo "Waiting for MLflow to be ready..."
          for i in {1..60}; do
            if curl -s http://localhost:5555/health | grep -q '"status": "OK"'; then
              echo "MLflow is ready!"
              exit 0
            fi
            echo "Not ready yet... ($i/60)"
            sleep 2
          done
          echo "MLflow failed to start"
          docker logs mlflow
          exit 1

      - name: Verify MLflow API
        run: |
          echo "Testing MLflow API..."
          curl -X GET http://localhost:5555/api/2.0/mlflow/experiments/list
          echo ""
          echo "MLflow API is responding!"

      - name: Build Llama Stack
        run: |
          uv run --no-sync llama stack list-deps ci-tests | xargs -L1 uv pip install

      - name: Install MLflow Python client
        run: |
          uv pip install 'mlflow>=3.4.0'

      - name: Check Storage and Memory Available Before Tests
        if: ${{ always() }}
        run: |
          free -h
          df -h

      - name: Run MLflow Integration Tests
        env:
          MLFLOW_TRACKING_URI: http://localhost:5555
        run: |
          uv run --no-sync \
            pytest -sv \
            tests/integration/providers/remote/prompts/mlflow/

      - name: Check Storage and Memory Available After Tests
        if: ${{ always() }}
        run: |
          free -h
          df -h

      - name: Write MLflow logs to file
        if: ${{ always() }}
        run: |
          docker logs mlflow > mlflow.log 2>&1 || true

      - name: Upload all logs to artifacts
        if: ${{ always() }}
        uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
        with:
          name: mlflow-logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ matrix.python-version }}
          path: |
            *.log
          retention-days: 1

      - name: Stop MLflow container
        if: ${{ always() }}
        run: |
          docker stop mlflow || true