name: 'Nightly Test (NPU) Single Node Template'

on:
  workflow_call:
    inputs:
      runner:
        required: true
        type: string
        default: linux-aarch64-a3-16
      test_type:
        required: false
        type: string
        default: perf
        description: perf or accuracy
      test_config_name:
        required: true
        type: string
        description: test config name
      test_case:
        required: true
        type: string
        description: path of test case file
      image:
        required: false
        type: string
        description: image for pods
        default: "swr.cn-southwest-2.myhuaweicloud.com/base_image/dockerhub/lmsysorg/sglang:main-cann9.0.0-a3"
      install_sglang_from_source:
        required: false
        type: boolean
        default: false
        description: use sglang from source code or from docker image
      install_sglang_deps:
        required: false
        type: boolean
        default: false
        description: install sglang dependencies (e.g. PyTorch, CANN packages) when using source installation
      device_type_for_deps:
        required: false
        type: string
        default: 'a3'
        description: device type for dependency installation (a3 or 910b)
      transformers_version:
        required: false
        type: string
        default: ""
        description: "The transformers version number for running sglang. Use default version in image if keep empty."

concurrency:
  group: ascend-nightly-e2e-singlenode-${{ github.workflow_ref }}-${{ github.ref }}-${{ inputs.test_config_name }}
  cancel-in-progress: true

jobs:
  e2e:
    name: ${{ inputs.test_config_name }}
    runs-on: ${{ inputs.runner }}
    container:
      image: ${{ inputs.image }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Check npu info
        run: |
          npu-smi info

      - name: Install sglang dependencies
        if: ${{ inputs.install_sglang_deps == true }}
        shell: bash
        env:
          TORCH_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/whl/cpu"
          PYPI_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          UV_INDEX_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local/pypi/simple"
          GITHUB_PROXY_URL: "https://gh-proxy.test.osinfra.cn/"
          RUSTUP_CACHE_URL: "http://cache-service.nginx-pypi-cache.svc.cluster.local:8082"
        run: |
          CACHING_URL="cache-service.nginx-pypi-cache.svc.cluster.local"
          sed -Ei "s@(ports|archive).ubuntu.com@${CACHING_URL}:8081@g" /etc/apt/sources.list
          pip config set global.index-url http://${CACHING_URL}/pypi/simple
          pip config set global.trusted-host "${CACHING_URL}"
          bash scripts/ci/npu/npu_ci_install_dependency.sh ${{ inputs.device_type_for_deps }}
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp

      - name: Run test
        timeout-minutes: 300
        env:
          SGLANG_USE_MODELSCOPE: true
          HF_ENDPOINT: https://hf-mirror.com
          SGLANG_IS_IN_CI: true
          TRANSFORMERS_VERBOSITY: "error"
          GDN_ATTN_BACKEND_TRITON: 1
          SGLANG_TEST_METRICS_OUTPUT: /root/.cache/tests/output/metrics/metrics
        shell: bash
        run: |
          sglang_source_path=$(pwd)
          echo "Source code path: ${sglang_source_path}"
          ln -sf ${sglang_source_path} /root/sglang

          test_case=${{ inputs.test_case }}
          if [ ! -f "${sglang_source_path}/${test_case}" ]; then
            echo "The testcase does not exit: ${sglang_source_path}/${test_case}"
            exit 1
          fi

          # prepare for output data
          current_date=$(date +%Y%m%d)
          test_data_output_path=/root/.cache/tests/output/${{ inputs.test_type }}/${current_date}
          mkdir -p ${test_data_output_path}
          tc_name=${test_case##*/}
          tc_name=${tc_name%.*}
          export METRICS_DATA_FILE=${test_data_output_path}/${tc_name}
          mkdir -p ${METRICS_DATA_FILE}
          echo "Metrics file path: ${METRICS_DATA_FILE}"

          # copy required file from our daily cache
          cp ~/.cache/modelscope/hub/datasets/otavia/ShareGPT_Vicuna_unfiltered/ShareGPT_V3_unfiltered_cleaned_split.json /tmp
          curl -o /tmp/test.jsonl -L https://gh-proxy.test.osinfra.cn/https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl

          export TRANSFORMERS_VERSION_FOR_SGLANG="${{ inputs.transformers_version }}"
          PYTHON_FOR_SGLANG="python"
          PIP_FOR_SGLANG="pip"
          if [ -n "${TRANSFORMERS_VERSION_FOR_SGLANG}" ];then
            echo "===== Install transformers for sglang - Begin ====="
            TRANSFORMERS_PKG_PATH_SOURCE=/root/.cache/.cache/transformers/${TRANSFORMERS_VERSION_FOR_SGLANG}
            if [ ! -d "${TRANSFORMERS_PKG_PATH_SOURCE}" ]; then
              echo "The dependent transformers package does not exist: ${TRANSFORMERS_PKG_PATH_SOURCE}."
              echo "Install transformers ${TRANSFORMERS_VERSION_FOR_SGLANG} online."
              pip install transformers=="${TRANSFORMERS_VERSION_FOR_SGLANG}" -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
            else
              echo "Install transformers ${TRANSFORMERS_VERSION_FOR_SGLANG} locally."
              TRANSFORMERS_PKG_PATH_TARGET=/tmp/transformers/${TRANSFORMERS_VERSION_FOR_SGLANG}
              mkdir -p "${TRANSFORMERS_PKG_PATH_TARGET}"
              cp "${TRANSFORMERS_PKG_PATH_SOURCE}/*" "${TRANSFORMERS_PKG_PATH_TARGET}/"
              pip install --no-index --find-links="${TRANSFORMERS_PKG_PATH_TARGET}" transformers=="${TRANSFORMERS_VERSION_FOR_SGLANG}"
            fi
            echo "===== Install transformers for sglang in virtual env - End ====="
          fi
          echo "Transformers version for sglang: $(${PIP_FOR_SGLANG} show transformers | grep Version | cut -d: -f2)"

          echo "scaling_governor performance num: \
            $(cat /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor | grep performance | wc -l)"
          echo "swappiness: $(cat /proc/sys/vm/swappiness)"
          echo "numa_balancing: $(cat /proc/sys/kernel/numa_balancing)"
          echo "sched_migration_cost_ns: $(cat /proc/sys/kernel/sched_migration_cost_ns)"

          export SGLANG_TEST_MAX_RETRY=0
          export SGLANG_SET_CPU_AFFINITY=1
          echo "SGLANG_SET_CPU_AFFINITY: $SGLANG_SET_CPU_AFFINITY"

          install_sglang_from_source=${{ inputs.install_sglang_from_source }}
          if [ "$install_sglang_from_source" = "true" ] || [ "$install_sglang_from_source" = "True" ];then
            echo "Install sglang from source"
            commit_id=${{ github.sha }}
            echo "commit id: ${commit_id}" > ${test_data_output_path}/commit_id
            export PYTHONPATH=${sglang_source_path}/python:$PYTHONPATH
          else
            echo "Use sglang from image: ${{ inputs.image }}"
            sglang_pkg_path=/sgl-workspace/sglang/python
            ascend_test_util_path=${sglang_pkg_path}/sglang/test/ascend
            mkdir -p ${ascend_test_util_path}
            mv ${ascend_test_util_path} ${ascend_test_util_path}_bak
            cp -r ${sglang_source_path}/python/sglang/test/ascend ${ascend_test_util_path}
          fi

          source /usr/local/Ascend/cann/set_env.sh || true
          source /usr/local/Ascend/nnal/atb/set_env.sh || true

          # Set environment of cann
          log_path="/root/.cache/tests/logs/log/${current_date}/${tc_name}/${HOSTNAME}"
          rm -rf ${log_path}
          mkdir -p ${log_path}
          echo "Log path: ${log_path}"

          echo "Running test case ${test_case}"
          test_exit_code=0
          ${PYTHON_FOR_SGLANG} -u ${test_case} 2>&1 | tee /tmp/test_output.log || test_exit_code=$?
          echo "Finished test case ${test_case}"

          if [ "${test_exit_code}" = "0" ]; then
            test_status="pass"
            status_icon="✅"
          else
            test_status="fail"
            status_icon="❌"
          fi

          echo "test_status=${test_status}" >> $GITHUB_ENV
          echo "tc_name=${tc_name}" >> $GITHUB_ENV
          export test_status tc_name

          echo "## ${tc_name}  ${status_icon} ${test_status}" >> $GITHUB_STEP_SUMMARY
          echo "" >> $GITHUB_STEP_SUMMARY
          metric_count=$(grep -c '\[METRIC\]' /tmp/test_output.log 2>/dev/null || echo 0)
          if [ "${metric_count}" -gt 0 ]; then
            echo "| Metric | Value | Pass |" >> $GITHUB_STEP_SUMMARY
            echo "|--------|-------|------|" >> $GITHUB_STEP_SUMMARY
            grep '\[METRIC\]' /tmp/test_output.log | while IFS= read -r line; do
              metric_name=$(echo "$line" | sed -E 's/.*\[METRIC\] ([^=]+)=.*/\1/')
              metric_value=$(echo "$line" | sed -E 's/.*\[METRIC\] [^=]+=([^ ]+).*/\1/')
              echo "| ${metric_name} | ${metric_value} | ${status_icon} |" >> $GITHUB_STEP_SUMMARY
            done
          else
            echo "No metrics collected (test may have failed before producing results)." >> $GITHUB_STEP_SUMMARY
          fi
          echo "" >> $GITHUB_STEP_SUMMARY

          echo "import json, re, os" > /tmp/dump_metrics.py
          echo "tc = os.environ.get('tc_name', 'unknown')" >> /tmp/dump_metrics.py
          echo "st = os.environ.get('test_status', 'unknown')" >> /tmp/dump_metrics.py
          echo "tp = '${{ inputs.test_type }}'" >> /tmp/dump_metrics.py
          echo "metrics = {}" >> /tmp/dump_metrics.py
          echo "with open('/tmp/test_output.log') as f:" >> /tmp/dump_metrics.py
          echo "    for line in f:" >> /tmp/dump_metrics.py
          echo "        m = re.match(r'\[METRIC\] (\S+)=(\S+)', line)" >> /tmp/dump_metrics.py
          echo "        if m:" >> /tmp/dump_metrics.py
          echo "            v = m.group(2)" >> /tmp/dump_metrics.py
          echo "            try:" >> /tmp/dump_metrics.py
          echo "                v = float(v)" >> /tmp/dump_metrics.py
          echo "            except ValueError:" >> /tmp/dump_metrics.py
          echo "                pass" >> /tmp/dump_metrics.py
          echo "            metrics[m.group(1)] = v" >> /tmp/dump_metrics.py
          echo "baselines = {}" >> /tmp/dump_metrics.py
          echo "for k, v in list(metrics.items()):" >> /tmp/dump_metrics.py
          echo "    if k.endswith('_baseline'):" >> /tmp/dump_metrics.py
          echo "        baselines[k[:-9]] = v" >> /tmp/dump_metrics.py
          echo "        del metrics[k]" >> /tmp/dump_metrics.py
          echo "with open('/tmp/metrics.json', 'w') as f:" >> /tmp/dump_metrics.py
          echo "    json.dump({'test_case': tc, 'test_type': tp, 'status': st, 'metrics': metrics, 'baselines': baselines}, f)" >> /tmp/dump_metrics.py
          python3 /tmp/dump_metrics.py
          exit ${test_exit_code}

      - name: Upload metrics
        if: always()
        uses: actions/upload-artifact@v4
        with:
          name: metrics-${{ inputs.test_config_name }}
          path: /tmp/metrics.json
          retention-days: 7

      - name: Backup plog
        if: always()
        shell: bash
        run: |
          plog_path="/root/ascend/log/debug/plog"
          if [ -d "$plog_path" ];then
            echo "Plog files found. Begin to backup them."
            tc_name=${{ inputs.test_case }}
            tc_name=${tc_name##*/}
            tc_name=${tc_name%.*}
            target_plog_path="/root/.cache/tests/logs/plog/${tc_name}/${HOSTNAME}"
            echo "Save path: ${target_plog_path}"
            rm -rf ${target_plog_path}
            mkdir -p ${target_plog_path}
            cp ${plog_path}/* ${target_plog_path}
          fi