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Evaluation Suite: - Tiered eval framework (Tier 1 ~$3/15min, Tier 2/3 for extended coverage) - 16 benchmarks across 3 tiers: GSM8K, TruthfulQA, MMLU, ARC, HumanEval, SQuAD v2, BFCL, Tool Outputs, CCR needle retention, HotpotQA, and more - Before/After runner with full proxy support (compression + CCR retrieval) - LLM-as-judge for ground-truth comparison (BFCL function calling) - Zero-cost compression-only runner (CCR needle retention, info retention) - Cost tracker with per-model pricing and budget enforcement - Report card generator (Markdown, JSON, HTML) - Suite CLI: python -m headroom.evals suite --tier 1 - Fix BFCL dataset loader for current HuggingFace schema - CI workflow: PR smoke test + weekly full Tier 1 Results: SQuAD 97%, BFCL 97%, Tool Outputs 100%, CCR 100% SmartCrusher: - Universal JSON crush for heterogeneous arrays - Fix mypy redefinition warning in _crush_string_array Other: - Latency benchmark suite with docs - Known limitations doc - Prompt comparison evaluator - Config updates for new features
374 lines
11 KiB
Python
374 lines
11 KiB
Python
#!/usr/bin/env python3
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"""CLI runner for Headroom benchmark suite.
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This script provides a convenient interface for running benchmarks and
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generating reports. It wraps pytest-benchmark with Headroom-specific
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options and markdown report generation.
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Usage:
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# Run all benchmarks
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python benchmarks/run_benchmarks.py
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# Run specific suite
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python benchmarks/run_benchmarks.py --suite transforms
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# Generate markdown report
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python benchmarks/run_benchmarks.py --output report.md
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# Compare against baseline
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python benchmarks/run_benchmarks.py --compare baseline.json
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# Save results as new baseline
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python benchmarks/run_benchmarks.py --save-baseline baseline.json
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Available Suites:
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all - Run all benchmark suites (transforms + relevance)
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latency - Compression overhead & cost-benefit analysis (standalone)
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transforms - SmartCrusher, CacheAligner, RollingWindow
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relevance - BM25Scorer, HybridScorer
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crusher - SmartCrusher only
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window - RollingWindow only
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pipeline - Full transform pipeline
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"""
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from __future__ import annotations
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import argparse
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import json
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import subprocess
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import sys
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from datetime import datetime
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from pathlib import Path
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from typing import Any
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# Benchmark suite definitions
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BENCHMARK_SUITES = {
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"all": [
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"benchmarks/bench_transforms.py",
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"benchmarks/bench_relevance.py",
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],
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"latency": [], # Standalone script: python benchmarks/bench_latency.py
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"transforms": [
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"benchmarks/bench_transforms.py",
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],
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"relevance": [
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"benchmarks/bench_relevance.py",
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],
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"crusher": [
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"benchmarks/bench_transforms.py::TestSmartCrusherBenchmarks",
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],
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"aligner": [
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"benchmarks/bench_transforms.py::TestCacheAlignerBenchmarks",
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],
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"window": [
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"benchmarks/bench_transforms.py::TestRollingWindowBenchmarks",
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],
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"pipeline": [
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"benchmarks/bench_transforms.py::TestTransformPipelineBenchmarks",
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],
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"bm25": [
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"benchmarks/bench_relevance.py::TestBM25Benchmarks",
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],
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"hybrid": [
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"benchmarks/bench_relevance.py::TestHybridBenchmarks",
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],
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}
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# Performance targets (mean time in microseconds)
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PERFORMANCE_TARGETS = {
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"test_compress_100_items": 2000, # 2ms
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"test_compress_1000_items": 10000, # 10ms
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"test_compress_10000_items": 100000, # 100ms
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"test_date_extraction": 1000, # 1ms
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"test_hash_computation": 500, # 0.5ms
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"test_window_50_turns": 5000, # 5ms
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"test_window_200_turns": 20000, # 20ms
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"test_single_item": 100, # 0.1ms
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"test_batch_100": 1000, # 1ms
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"test_batch_1000": 10000, # 10ms
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"test_pipeline_simple": 5000, # 5ms
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"test_pipeline_agentic": 30000, # 30ms
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"test_pipeline_rag": 50000, # 50ms
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}
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def run_benchmarks(
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suite: str,
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output_json: str | None = None,
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compare: str | None = None,
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verbose: bool = False,
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extra_args: list[str] | None = None,
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) -> tuple[int, dict[str, Any] | None]:
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"""Run benchmark suite via pytest.
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Args:
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suite: Name of benchmark suite to run.
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output_json: Path to save JSON results.
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compare: Path to baseline JSON for comparison.
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verbose: Enable verbose output.
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extra_args: Additional pytest arguments.
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Returns:
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Tuple of (exit_code, results_dict).
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"""
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if suite not in BENCHMARK_SUITES:
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print(f"Error: Unknown suite '{suite}'")
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print(f"Available suites: {', '.join(BENCHMARK_SUITES.keys())}")
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return 1, None
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# Build pytest command
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cmd = [
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sys.executable,
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"-m",
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"pytest",
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"--benchmark-only",
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"--benchmark-sort=name",
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]
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# Add test files/patterns
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cmd.extend(BENCHMARK_SUITES[suite])
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# Add output options
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if output_json:
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cmd.extend(["--benchmark-json", output_json])
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# Add comparison
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if compare:
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cmd.extend(["--benchmark-compare", compare])
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# Add verbosity
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if verbose:
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cmd.append("-v")
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else:
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cmd.append("-q")
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# Add extra args
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if extra_args:
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cmd.extend(extra_args)
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# Run benchmarks
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print(f"Running {suite} benchmarks...")
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print(f"Command: {' '.join(cmd)}")
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print("-" * 60)
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result = subprocess.run(cmd, capture_output=False)
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# Load results if saved
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results = None
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if output_json and Path(output_json).exists():
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with open(output_json) as f:
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results = json.load(f)
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return result.returncode, results
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def generate_markdown_report(
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results: dict[str, Any],
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output_path: str,
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include_targets: bool = True,
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) -> None:
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"""Generate markdown report from benchmark results.
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Args:
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results: Benchmark results dictionary (from pytest-benchmark JSON).
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output_path: Path to write markdown file.
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include_targets: Include performance target comparison.
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"""
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lines = []
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# Header
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lines.append("# Headroom SDK Benchmark Report")
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lines.append("")
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lines.append(f"Generated: {datetime.now().isoformat()}")
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lines.append("")
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# Machine info
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if "machine_info" in results:
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info = results["machine_info"]
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lines.append("## Environment")
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lines.append("")
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lines.append(f"- **Machine**: {info.get('machine', 'unknown')}")
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lines.append(f"- **Processor**: {info.get('processor', 'unknown')}")
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lines.append(f"- **Python**: {info.get('python_version', 'unknown')}")
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lines.append("")
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# Summary table
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lines.append("## Results Summary")
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lines.append("")
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lines.append("| Test | Mean | StdDev | Min | Max | Target | Status |")
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lines.append("|------|------|--------|-----|-----|--------|--------|")
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benchmarks = results.get("benchmarks", [])
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passed = 0
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failed = 0
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for bench in benchmarks:
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name = bench["name"]
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stats = bench["stats"]
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mean_us = stats["mean"] * 1_000_000 # Convert to microseconds
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stddev_us = stats["stddev"] * 1_000_000
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min_us = stats["min"] * 1_000_000
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max_us = stats["max"] * 1_000_000
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# Format times
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mean_str = _format_time(mean_us)
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stddev_str = _format_time(stddev_us)
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min_str = _format_time(min_us)
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max_str = _format_time(max_us)
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# Check target
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test_name = name.split("::")[-1]
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target = PERFORMANCE_TARGETS.get(test_name)
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if target:
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target_str = _format_time(target)
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if mean_us <= target:
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status = "PASS"
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passed += 1
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else:
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status = "FAIL"
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failed += 1
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else:
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target_str = "-"
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status = "-"
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lines.append(
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f"| `{test_name}` | {mean_str} | {stddev_str} | {min_str} | {max_str} | {target_str} | {status} |"
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)
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lines.append("")
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# Summary stats
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total = passed + failed
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if total > 0:
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lines.append("## Summary")
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lines.append("")
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lines.append(f"- **Passed**: {passed}/{total} ({100 * passed / total:.0f}%)")
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lines.append(f"- **Failed**: {failed}/{total} ({100 * failed / total:.0f}%)")
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lines.append("")
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# Performance notes
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lines.append("## Performance Targets")
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lines.append("")
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lines.append("| Component | Target | Notes |")
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lines.append("|-----------|--------|-------|")
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lines.append("| SmartCrusher (100 items) | < 2ms | Typical API response |")
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lines.append("| SmartCrusher (1000 items) | < 10ms | Large tool output |")
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lines.append("| SmartCrusher (10000 items) | < 100ms | Stress test |")
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lines.append("| CacheAligner | < 1ms | Date extraction + hash |")
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lines.append("| RollingWindow (50 turns) | < 5ms | Long conversation |")
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lines.append("| RollingWindow (200 turns) | < 20ms | Stress test |")
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lines.append("| BM25Scorer (batch 100) | < 1ms | Zero dependencies |")
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lines.append("| HybridScorer (batch 100) | < 50ms | With embeddings |")
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lines.append("")
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# Write file
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with open(output_path, "w") as f:
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f.write("\n".join(lines))
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print(f"Report written to: {output_path}")
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def _format_time(microseconds: float) -> str:
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"""Format time value with appropriate unit."""
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if microseconds < 1000:
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return f"{microseconds:.1f}us"
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elif microseconds < 1_000_000:
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return f"{microseconds / 1000:.2f}ms"
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else:
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return f"{microseconds / 1_000_000:.2f}s"
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def main() -> int:
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"""Main entry point."""
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parser = argparse.ArgumentParser(
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description="Run Headroom SDK benchmarks",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog=__doc__,
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)
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parser.add_argument(
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"--suite",
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"-s",
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choices=list(BENCHMARK_SUITES.keys()),
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default="all",
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help="Benchmark suite to run (default: all)",
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)
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parser.add_argument(
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"--output",
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"-o",
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help="Output markdown report path",
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)
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parser.add_argument(
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"--json",
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"-j",
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help="Save raw JSON results to path",
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)
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parser.add_argument(
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"--compare",
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"-c",
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help="Compare against baseline JSON",
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)
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parser.add_argument(
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"--save-baseline",
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help="Save results as baseline (alias for --json)",
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)
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parser.add_argument(
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"--verbose",
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"-v",
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action="store_true",
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help="Verbose output",
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)
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parser.add_argument(
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"pytest_args",
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nargs="*",
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help="Additional pytest arguments",
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)
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args = parser.parse_args()
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# Handle save-baseline as alias
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json_output = args.json or args.save_baseline
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# Latency suite is a standalone script, not pytest-benchmark
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if args.suite == "latency":
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cmd = [sys.executable, "benchmarks/bench_latency.py"]
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if args.output:
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cmd.extend(["--output", args.output])
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if json_output:
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cmd.extend(["--json", json_output])
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if args.verbose:
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cmd.append("-v")
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print("Delegating to latency benchmark script...")
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return subprocess.run(cmd).returncode
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# Run benchmarks
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exit_code, results = run_benchmarks(
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suite=args.suite,
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output_json=json_output,
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compare=args.compare,
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verbose=args.verbose,
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extra_args=args.pytest_args,
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)
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# Generate markdown report if requested
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if args.output and results:
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generate_markdown_report(results, args.output)
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elif args.output and json_output:
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# Load results from saved JSON
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with open(json_output) as f:
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results = json.load(f)
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generate_markdown_report(results, args.output)
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return exit_code
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if __name__ == "__main__":
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sys.exit(main())
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