chore: vendor sglang v0.5.10 snapshot

third_party/sglang/sgl-model-gateway/e2e_test/benchmarks/summarize.py

@@ -0,0 +1,119 @@
+"""Generate benchmark summary for GitHub Actions."""
+
+from __future__ import annotations
+
+import os
+import sys
+from pathlib import Path
+
+from results import BenchmarkResult, GPUUtilization
+
+
+def discover_benchmarks(base_dir: Path) -> list[tuple[Path, str]]:
+    """Auto-discover benchmark folders and their result JSON files.
+
+    Returns list of (json_path, label) tuples sorted by folder name.
+    """
+    results = []
+    for folder in base_dir.rglob("benchmark_*"):
+        if not folder.is_dir():
+            continue
+        # Find result JSON (exclude metadata and gpu files)
+        for json_file in folder.glob("*.json"):
+            if (
+                "experiment_metadata" not in json_file.name
+                and "gpu_utilization" not in json_file.name
+            ):
+                # Generate label from folder name: benchmark_cache_aware_pd_grpc -> cache_aware pd grpc
+                label = folder.name.replace("benchmark_", "").replace("_", " ")
+                results.append((json_file, label))
+                break  # One JSON per folder
+    return sorted(results, key=lambda x: x[0].parent.name)
+
+
+def find_gpu_utilization(result_path: Path) -> Path | None:
+    """Find GPU utilization JSON in same folder as result."""
+    gpu_json = result_path.parent / "gpu_utilization.json"
+    return gpu_json if gpu_json.exists() else None
+
+
+def generate_summary(base_dir: Path) -> str:
+    """Generate markdown summary."""
+    benchmarks = discover_benchmarks(base_dir)
+
+    if not benchmarks:
+        return (
+            "## Gateway E2E Genai-Bench Results Summary\n\nNo benchmark results found."
+        )
+
+    lines = [
+        "## Gateway E2E Genai-Bench Results Summary",
+        "",
+        "| Scenario | Status | TTFT (s) | E2E Latency (s) | Input Throughput (tok/s) | Output Throughput (tok/s) |",
+        "|----------|--------|----------|-----------------|--------------------------|---------------------------|",
+    ]
+
+    gpu_sections = []
+
+    for result_path, label in benchmarks:
+        try:
+            result = BenchmarkResult.from_json(result_path)
+        except Exception as e:
+            print(f"Warning: Failed to parse {result_path}: {e}", file=sys.stderr)
+            lines.append(f"| {label} | ❌ Failed | - | - | - | - |")
+            continue
+
+        lines.append(
+            f"| {label} | ✅ Success | "
+            f"{result.ttft_mean:.2f} | "
+            f"{result.e2e_latency_mean:.2f} | "
+            f"{result.input_throughput_mean:.0f} | "
+            f"{result.output_throughput_mean:.0f} |"
+        )
+
+        # GPU utilization
+        gpu_path = find_gpu_utilization(result_path)
+        if gpu_path:
+            gpu = GPUUtilization.from_json(gpu_path)
+            if gpu and gpu.per_gpu:
+                gpu_lines = [
+                    f"### GPU Utilization — {label}",
+                    "",
+                    f"Overall mean: {gpu.overall_mean:.2f}%",
+                    "",
+                    "| GPU | Mean (%) | p5 | p10 | p25 | p50 | p75 | p90 | p95 |",
+                    "|-----|----------|----|-----|-----|-----|-----|-----|-----|",
+                ]
+                for gpu_id, stats in sorted(
+                    gpu.per_gpu.items(), key=lambda x: int(x[0])
+                ):
+                    gpu_lines.append(
+                        f"| {gpu_id} | {stats.get('mean', 0):.2f} | "
+                        f"{stats.get('p5', 0):.2f} | {stats.get('p10', 0):.2f} | "
+                        f"{stats.get('p25', 0):.2f} | {stats.get('p50', 0):.2f} | "
+                        f"{stats.get('p75', 0):.2f} | {stats.get('p90', 0):.2f} | "
+                        f"{stats.get('p95', 0):.2f} |"
+                    )
+                gpu_sections.append("\n".join(gpu_lines))
+
+    return "\n".join(lines) + "\n" + "\n\n".join(gpu_sections)
+
+
+def main() -> None:
+    """Main entry point."""
+    base_dir = Path(sys.argv[1]) if len(sys.argv) > 1 else Path.cwd()
+    summary = generate_summary(base_dir)
+
+    # Write to GITHUB_STEP_SUMMARY if available
+    summary_file = os.environ.get("GITHUB_STEP_SUMMARY")
+    if summary_file:
+        with open(summary_file, "a") as f:
+            f.write(summary)
+            f.write("\n")
+        print(f"Summary written to {summary_file}")
+    else:
+        print(summary)
+
+
+if __name__ == "__main__":
+    main()