name: XPU CI Job Monitor

on:
  schedule:
    - cron: '0 0 * * *'  # Daily at midnight UTC
  pull_request:
    paths:
      - '.github/workflows/xpu-ci-job-monitor.yml'
      - 'scripts/ci/utils/xpu_job_monitor.py'
  workflow_dispatch:
    inputs:
      hours:
        description: 'Time window in hours'
        required: false
        default: '24'
        type: string
      job_filter:
        description: 'Job name filter (leave empty for all XPU jobs)'
        required: false
        type: string

# Bound the API cost when the same ref pushes repeatedly. See note in
# runner-utilization.yml for the original incident this guards against.
concurrency:
  group: xpu-ci-job-monitor-${{ github.ref }}
  cancel-in-progress: true

jobs:
  fetch-actions-data:
    name: Fetch Actions Snapshot
    # Skip fork PRs entirely, and require the `run-ci` label on same-repo PRs.
    # schedule and workflow_dispatch always run.
    if: >-
      github.event_name != 'pull_request' ||
      (github.event.pull_request.head.repo.full_name == github.repository &&
       contains(github.event.pull_request.labels.*.name, 'run-ci'))
    runs-on: ubuntu-latest
    env:
      GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: pip install tabulate

      - name: Select workflows for snapshot
        id: select-workflows
        run: |
          if [[ -n "${{ inputs.job_filter }}" ]]; then
            echo "workflows=pr-test-xpu.yml" >> "$GITHUB_OUTPUT"
          else
            echo "workflows=pr-test-xpu.yml,nightly-test-intel.yml" >> "$GITHUB_OUTPUT"
          fi

      - name: Fetch Actions data snapshot
        timeout-minutes: 30
        run: |
          # PR-trigger is just a script smoke check; scan a 20-minute window
          # (0.34h) to bound API cost. schedule / dispatch run the full report.
          python scripts/ci/utils/xpu_job_monitor.py \
            --repo ${{ github.repository }} \
            --workflow "${{ steps.select-workflows.outputs.workflows }}" \
            --hours ${{ (github.event_name == 'pull_request' && '0.34') || inputs.hours || '24' }} \
            --dump-data-file actions-job-snapshot.json

      - name: Upload Actions data snapshot
        uses: actions/upload-artifact@v4
        with:
          name: actions-job-snapshot
          path: actions-job-snapshot.json
          if-no-files-found: error

  # Single job filter mode
  custom-report:
    name: Custom Job Report
    if: ${{ inputs.job_filter }}
    needs: fetch-actions-data
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: pip install tabulate

      - name: Download Actions data snapshot
        uses: actions/download-artifact@v4
        with:
          name: actions-job-snapshot
          path: ci-data

      - name: Generate Custom Job Report
        timeout-minutes: 30
        run: |
          python scripts/ci/utils/xpu_job_monitor.py \
            --repo ${{ github.repository }} \
            --job "${{ inputs.job_filter }}" \
            --workflow "pr-test-xpu.yml" \
            --hours ${{ inputs.hours || '24' }} \
            --input-data-file ci-data/actions-job-snapshot.json \
            --summary

  # Parse workflow files to get job names dynamically
  parse-workflows:
    name: Parse Workflow Jobs
    if: ${{ !inputs.job_filter }}
    runs-on: ubuntu-latest
    outputs:
      pr_jobs: ${{ steps.parse.outputs.pr_jobs }}
      nightly_jobs: ${{ steps.parse.outputs.nightly_jobs }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Parse workflow files
        id: parse
        run: |
          # Parse pr-test-xpu.yml and extract job names (exclude utility jobs)
          # Excluded: check-changes, pr-gate, finish
          pr_jobs=$(yq -r '.jobs | keys | .[]' .github/workflows/pr-test-xpu.yml | \
            grep -v -E '^(check-changes|pr-gate|finish)$' | \
            jq -R -s -c 'split("\n") | map(select(length > 0))')
          echo "pr_jobs=$pr_jobs" >> $GITHUB_OUTPUT
          echo "PR jobs: $pr_jobs"

          # Parse nightly-test-intel.yml and extract job names (exclude utility jobs)
          # Excluded: check-all-jobs
          nightly_jobs=$(yq -r '.jobs | keys | .[]' .github/workflows/nightly-test-intel.yml | \
            grep -v -E '^(check-all-jobs)$' | \
            jq -R -s -c 'split("\n") | map(select(length > 0))')
          echo "nightly_jobs=$nightly_jobs" >> $GITHUB_OUTPUT
          echo "Nightly jobs: $nightly_jobs"

  # PR CI reports using dynamic matrix
  pr-ci-reports:
    name: PR - ${{ matrix.job_name }}
    needs: [parse-workflows, fetch-actions-data]
    if: ${{ !inputs.job_filter }}
    runs-on: ubuntu-latest
    strategy:
      fail-fast: false
      matrix:
        job_name: ${{ fromJson(needs.parse-workflows.outputs.pr_jobs) }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: pip install tabulate

      - name: Download Actions data snapshot
        uses: actions/download-artifact@v4
        with:
          name: actions-job-snapshot
          path: ci-data

      - name: Generate Report
        timeout-minutes: 15
        run: |
          python scripts/ci/utils/xpu_job_monitor.py \
            --repo ${{ github.repository }} \
            --job "${{ matrix.job_name }}" \
            --workflow "pr-test-xpu.yml" \
            --hours ${{ inputs.hours || '24' }} \
            --input-data-file ci-data/actions-job-snapshot.json \
            --summary

  # Nightly XPU test reports using dynamic matrix
  nightly-reports:
    name: Nightly - ${{ matrix.job_name }}
    needs: [parse-workflows, fetch-actions-data]
    if: ${{ !inputs.job_filter }}
    runs-on: ubuntu-latest
    strategy:
      fail-fast: false
      matrix:
        job_name: ${{ fromJson(needs.parse-workflows.outputs.nightly_jobs) }}
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: pip install tabulate

      - name: Download Actions data snapshot
        uses: actions/download-artifact@v4
        with:
          name: actions-job-snapshot
          path: ci-data

      - name: Generate Nightly Report
        timeout-minutes: 15
        run: |
          python scripts/ci/utils/xpu_job_monitor.py \
            --repo ${{ github.repository }} \
            --job "${{ matrix.job_name }}" \
            --workflow "nightly-test-intel.yml" \
            --hours ${{ inputs.hours || '24' }} \
            --input-data-file ci-data/actions-job-snapshot.json \
            --summary

  # Runner fleet report - cross-workflow runner analytics in a single pass
  runner-fleet-report:
    name: Runner Fleet Report
    if: ${{ !inputs.job_filter }}
    needs: fetch-actions-data
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: pip install tabulate

      - name: Download Actions data snapshot
        uses: actions/download-artifact@v4
        with:
          name: actions-job-snapshot
          path: ci-data

      - name: Generate Runner Fleet Report
        timeout-minutes: 30
        run: |
          python scripts/ci/utils/xpu_job_monitor.py \
            --repo ${{ github.repository }} \
            --runner-report \
            --workflow "pr-test-xpu.yml,nightly-test-intel.yml" \
            --hours ${{ inputs.hours || '24' }} \
            --input-data-file ci-data/actions-job-snapshot.json \
            --summary

  # Colorful nightly XPU status dashboard, rendered into the workflow summary.
  # Success-rate thresholds: >=90% healthy, >=70% degraded, else critical.
  nightly-xpu-status-dashboard:
    name: Nightly XPU Status Dashboard
    if: ${{ !inputs.job_filter }}
    needs: [fetch-actions-data, nightly-reports]
    runs-on: ubuntu-latest
    env:
      HEALTHY_THRESHOLD: '90'
      DEGRADED_THRESHOLD: '70'
      WINDOW_HOURS: ${{ inputs.hours || '24' }}
    steps:
      - name: Download Actions data snapshot
        uses: actions/download-artifact@v4
        with:
          name: actions-job-snapshot
          path: ci-data

      - name: Render colorful nightly status dashboard
        run: |
          python - <<'PY'
          import json, os, sys
          from datetime import datetime, timezone

          snap_path = "ci-data/actions-job-snapshot.json"
          out = os.environ.get("GITHUB_STEP_SUMMARY", "/dev/stdout")
          healthy = float(os.environ["HEALTHY_THRESHOLD"])
          degraded = float(os.environ["DEGRADED_THRESHOLD"])
          window_hours = os.environ.get("WINDOW_HOURS", "24")

          with open(snap_path) as f:
              snapshot = json.load(f)

          # Snapshot writer emits `workflow` (filename), not `workflow_path`.
          nightly = [
              j for j in snapshot.get("jobs", [])
              if (j.get("workflow") or "").endswith("nightly-test-intel.yml")
          ]

          # status_summary style counts, per job name
          per_job = {}
          for j in nightly:
              name = j.get("job_name") or j.get("name", "unknown")
              d = per_job.setdefault(name, {"success": 0, "failure": 0, "cancelled": 0, "skipped": 0, "in_progress": 0, "other": 0})
              status = j.get("status", "")
              conclusion = j.get("conclusion", "")
              if status == "completed":
                  if conclusion == "success":
                      d["success"] += 1
                  elif conclusion == "failure":
                      d["failure"] += 1
                  elif conclusion == "skipped":
                      d["skipped"] += 1
                  elif conclusion == "cancelled":
                      d["cancelled"] += 1
                  else:
                      d["other"] += 1
              elif status in ("in_progress", "queued", "waiting"):
                  d["in_progress"] += 1
              else:
                  d["other"] += 1

          def badge(label, value, color):
              # shields.io renders inline in GitHub markdown summaries.
              label = label.replace("-", "--").replace(" ", "_")
              value = str(value).replace("-", "--").replace(" ", "_")
              return f"![{label}](https://img.shields.io/badge/{label}-{value}-{color})"

          def health(rate):
              if rate is None:
                  return ("gray", "UNKNOWN", "⚪")   # white circle
              if rate >= healthy:
                  return ("brightgreen", "HEALTHY", "\U0001F7E2")   # green circle
              if rate >= degraded:
                  return ("yellow", "DEGRADED", "\U0001F7E1")       # yellow circle
              return ("red", "CRITICAL", "\U0001F534")              # red circle

          totals = {"success": 0, "failure": 0, "cancelled": 0, "skipped": 0, "in_progress": 0, "other": 0}
          for counts in per_job.values():
              for k, v in counts.items():
                  totals[k] += v
          finished = totals["success"] + totals["failure"]
          overall_rate = (totals["success"] / finished * 100.0) if finished else None
          fleet_color, fleet_label, fleet_dot = health(overall_rate)

          now = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")
          lines = []
          lines.append("## Nightly XPU Status Dashboard")
          lines.append("")
          lines.append(f"_Window: last **{window_hours}h** · Snapshot rendered at **{now}**_")
          lines.append("")
          lines.append("### Fleet health")
          lines.append("")
          lines.append(
              " ".join([
                  badge("fleet", fleet_label, fleet_color),
                  badge("success_rate", f"{overall_rate:.1f}%25" if overall_rate is not None else "n%2Fa", fleet_color),
                  badge("healthy_threshold", f"{int(healthy)}%25", "brightgreen"),
                  badge("degraded_threshold", f"{int(degraded)}%25", "yellow"),
              ])
          )
          lines.append("")
          lines.append(
              f"**{fleet_dot} Overall:** "
              f"{totals['success']} passed · {totals['failure']} failed · "
              f"{totals['cancelled']} cancelled · {totals['skipped']} skipped · "
              f"{totals['in_progress']} in flight"
          )
          lines.append("")
          lines.append("### Per-model / per-job breakdown")
          lines.append("")
          lines.append("| Status | Job | Success rate | Passed | Failed | Skipped | Cancelled | In-flight |")
          lines.append("|:------:|:----|-------------:|-------:|-------:|--------:|----------:|----------:|")

          def sort_key(item):
              name, c = item
              finished = c["success"] + c["failure"]
              rate = (c["success"] / finished) if finished else 2.0  # untested last
              return (rate, name)

          for name, c in sorted(per_job.items(), key=sort_key):
              finished = c["success"] + c["failure"]
              rate = (c["success"] / finished * 100.0) if finished else None
              color, label, dot = health(rate)
              rate_txt = f"{rate:.1f}%" if rate is not None else "n/a"
              rate_badge = badge("rate", f"{rate:.1f}%25" if rate is not None else "n%2Fa", color)
              lines.append(
                  f"| {dot} `{label}` | `{name}` | {rate_badge} <sub>{rate_txt}</sub> | "
                  f"{c['success']} | {c['failure']} | {c['skipped']} | {c['cancelled']} | {c['in_progress']} |"
              )

          lines.append("")
          lines.append("<sub>Thresholds: "
                       f"\U0001F7E2 healthy ≥ {int(healthy)}% · "
                       f"\U0001F7E1 degraded ≥ {int(degraded)}% · "
                       f"\U0001F534 critical below</sub>")
          lines.append("")

          with open(out, "a") as f:
              f.write("\n".join(lines) + "\n")

          # Fail the step if fleet is CRITICAL so oncall sees a red X on the run.
          if overall_rate is not None and overall_rate < degraded:
              print(f"::error::Nightly XPU fleet is CRITICAL: success rate {overall_rate:.1f}% < {int(degraded)}%")
              sys.exit(1)
          PY

  # -------------------------------------------------------------------
  # Intel(XPU) Nightly report — per-model 1x/2x/4x/8x tables.
  # Downloads the per-model metrics jsonl artifacts uploaded by
  # nightly-test-intel.yml (SGLANG_TEST_METRICS_FILE side-writer) and renders
  # one Markdown table per GPU-count suite. 8x is future-ready: it renders
  # "No metrics recorded" until an 8-GPU suite is enabled upstream.
  # -------------------------------------------------------------------
  nightly-xpu-per-model-report:
    name: Intel(XPU) Nightly report
    # Fork PRs don't get secrets and can't read cross-workflow artifacts;
    # rest is same gating as the fetch-actions-data job above.
    if: >-
      github.event_name != 'pull_request' ||
      (github.event.pull_request.head.repo.full_name == github.repository &&
       contains(github.event.pull_request.labels.*.name, 'run-ci'))
    runs-on: ubuntu-latest
    env:
      GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
    steps:
      - name: Resolve latest Nightly Test (Intel) run id
        id: source-run
        run: |
          # Pick the most recent completed run of nightly-test-intel.yml on the
          # default branch. workflow_dispatch reruns are included; skipped or
          # in-progress runs are not.
          RUN_ID=$(gh run list \
            --repo "${GITHUB_REPOSITORY}" \
            --workflow nightly-test-intel.yml \
            --branch main \
            --status completed \
            --limit 1 \
            --json databaseId --jq '.[0].databaseId // empty')
          if [ -z "$RUN_ID" ]; then
            echo "No completed Nightly Test (Intel) run found on main."
            echo "run_id=" >> "$GITHUB_OUTPUT"
          else
            echo "Latest completed nightly run: $RUN_ID"
            echo "run_id=$RUN_ID" >> "$GITHUB_OUTPUT"
          fi

      - name: Download per-model metrics artifacts
        if: steps.source-run.outputs.run_id != ''
        uses: actions/download-artifact@v4
        with:
          pattern: nightly-xpu-*-metrics
          path: metrics/
          run-id: ${{ steps.source-run.outputs.run_id }}
          github-token: ${{ secrets.GITHUB_TOKEN }}
          repository: ${{ github.repository }}
          # Keep artifact names as subdirs so we can split by GPU-count suite.
          merge-multiple: false
        continue-on-error: true

      - name: Render per-model 1x / 2x / 4x / 8x tables
        env:
          SOURCE_RUN_ID: ${{ steps.source-run.outputs.run_id }}
        run: |
          python - <<'PY'
          import glob
          import json
          import os

          SUITES = [
              ("1x", "nightly-xpu-1-gpu-metrics"),
              ("2x", "nightly-xpu-2-gpu-metrics"),
              ("4x", "nightly-xpu-4-gpu-metrics"),
              # 8x is here for future readiness. Until nightly-test-intel.yml
              # adds an 8-GPU suite + upload step, its artifact directory is
              # missing and the section renders "No metrics recorded".
              ("8x", "nightly-xpu-8-gpu-metrics"),
          ]

          def load(subdir: str):
              path = os.path.join("metrics", subdir)
              records = []
              for f in sorted(glob.glob(os.path.join(path, "*.jsonl"))):
                  with open(f) as fh:
                      for line in fh:
                          line = line.strip()
                          if not line:
                              continue
                          try:
                              records.append(json.loads(line))
                          except json.JSONDecodeError:
                              # Skip malformed rows so one bad line doesn't
                              # blank the whole table.
                              continue
              return records

          def fmt(value, precision: int = 2) -> str:
              if value is None or value == "" or value == "N/A":
                  return "N/A"
              try:
                  return f"{float(value):.{precision}f}"
              except (TypeError, ValueError):
                  return str(value)

          out = os.environ.get("GITHUB_STEP_SUMMARY", "/dev/stdout")
          source_run = os.environ.get("SOURCE_RUN_ID", "")
          repo = os.environ.get("GITHUB_REPOSITORY", "")

          lines = ["", "## Intel(XPU) Nightly report", ""]
          if source_run and repo:
              lines.append(
                  f"Source: [Intel(XPU) Nightly report - run #{source_run}]"
                  f"(https://github.com/{repo}/actions/runs/{source_run})"
              )
              lines.append("")
          elif not source_run:
              lines.append("_No completed Nightly Test (Intel) run found; nothing to render._")
              lines.append("")

          def rows_for(records):
              # Group records by test_file. Two record shapes:
              #   kind=="model": rich per-model row emitted by tests that call
              #                  write_results_to_github_step_summary.
              #   kind=="file":  file-level fallback emitted by run_unittest_files
              #                  for every test file in the suite.
              # If a test_file has any model rows, we show those and drop the
              # matching file row so a test does not double-count. Test files
              # that never emit a model row fall back to the file row - that
              # is what makes newly-added tests appear automatically.
              by_file_model = {}
              by_file_file = {}
              orphans_model = []
              for r in records:
                  kind = r.get("kind")
                  tf = r.get("test_file", "") or ""
                  if kind == "model":
                      if tf:
                          by_file_model.setdefault(tf, []).append(r)
                      else:
                          orphans_model.append(r)
                  else:
                      # "file" or legacy records without kind
                      if tf and "model" not in r:
                          by_file_file[tf] = r
                      else:
                          orphans_model.append(r)

              rendered = []
              for tf in sorted(set(by_file_model) | set(by_file_file)):
                  if tf in by_file_model:
                      for r in by_file_model[tf]:
                          rendered.append(("model", r))
                  else:
                      rendered.append(("file", by_file_file[tf]))
              for r in orphans_model:
                  rendered.append(("model", r))
              return rendered

          any_fail = 0
          for label, subdir in SUITES:
              records = load(subdir)
              lines.append(f"### {label} ({subdir[:-len('-metrics')]})")
              lines.append("")
              if not records:
                  lines.append("_No metrics recorded for this suite._")
                  lines.append("")
                  continue

              lines.append(
                  "| Model / Test file | Prompts | Ref accuracy | Actual accuracy "
                  "| Ref throughput | Actual throughput | Duration | Status |"
              )
              lines.append(
                  "|-------------------|--------:|-------------:|----------------:"
                  "|---------------:|------------------:|---------:|:------:|"
              )
              for row_kind, r in rows_for(records):
                  status = str(r.get("status", "")).lower()
                  is_pass = status == "pass"
                  if not is_pass:
                      any_fail += 1
                  status_cell = "PASS" if is_pass else (status.upper() or "N/A")
                  if row_kind == "model":
                      duration = r.get("latency")
                      lines.append(
                          f"| `{r.get('model','?')}` "
                          f"| {r.get('num_prompts','N/A')} "
                          f"| {fmt(r.get('accuracy_threshold'), 3)} "
                          f"| {fmt(r.get('accuracy'), 3)} "
                          f"| {fmt(r.get('output_throughput_threshold'), 2)} "
                          f"| {fmt(r.get('output_throughput'), 2)} "
                          f"| {fmt(duration, 2)} "
                          f"| {status_cell} |"
                      )
                  else:
                      tf = r.get("test_file", "?")
                      lines.append(
                          f"| {tf} "
                          f"| N/A | N/A | N/A | N/A | N/A "
                          f"| {fmt(r.get('duration'), 2)} "
                          f"| {status_cell} |"
                      )
              lines.append("")

          lines.append(
              "<sub>Rows with a model name are per-model records emitted by "
              "`write_results_to_github_step_summary`; rows with just a test "
              "file name are auto-recorded by `run_unittest_files`. Ref columns "
              "are the accuracy / throughput thresholds declared by each test; "
              "Actual is what nightly measured. Any new test added to "
              "run_suite.py shows up here on the next nightly.</sub>"
          )
          lines.append("")

          with open(out, "a") as f:
              f.write("\n".join(lines) + "\n")

          # Surface — but don't hard-fail — the report step: nightly-test-intel
          # already flags model failures. This job is a rendering step.
          if any_fail:
              print(f"::warning::{any_fail} nightly XPU model row(s) marked FAIL in the per-model tables")
          PY