Files
autocad-mcp-pro/benchmarks/render_chart.py
T
Umutcan EdizsalanandCursor bae0750d4c docs(bench): dark leaderboard styling for all benchmark charts
Leaderboard restyled to the LLM-benchmark look: dark background, rank-numbered labels, per-rank color palette, 'NN / 100 - grade' annotations. The live-run, task-matrix and performance charts share the same dark theme for a consistent README identity. Charts regenerated deterministically from their data files.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-23 16:14:04 +03:00

172 lines
5.7 KiB
Python

"""Render the source-reviewed AutoCAD MCP benchmark as a deterministic SVG."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
from typing import Any
ROOT = Path(__file__).resolve().parents[1]
DEFAULT_INPUT = ROOT / "benchmarks" / "source_review.json"
DEFAULT_OUTPUT = ROOT / "docs" / "assets" / "autocad-mcp-benchmark.svg"
REQUIRED_PROJECT_KEYS = {
"repository",
"url",
"reviewed_version",
"score",
"evidence_grade",
"note",
}
def load_benchmark(path: Path) -> dict[str, Any]:
"""Load and validate the benchmark snapshot used by docs and tests."""
data = json.loads(path.read_text(encoding="utf-8"))
if data.get("schema_version") != "1.0":
raise ValueError("unsupported benchmark schema_version")
if data.get("evidence_boundary") != "source_review_not_shared_live_run":
raise ValueError("benchmark evidence boundary must be explicit")
rubric = data.get("rubric")
if not isinstance(rubric, list) or sum(item.get("weight", 0) for item in rubric) != 100:
raise ValueError("benchmark rubric weights must total 100")
projects = data.get("projects")
if not isinstance(projects, list) or not projects:
raise ValueError("benchmark must contain projects")
seen: set[str] = set()
for project in projects:
missing = REQUIRED_PROJECT_KEYS - project.keys()
if missing:
raise ValueError(f"project is missing keys: {sorted(missing)}")
repository = project["repository"]
if repository in seen:
raise ValueError(f"duplicate repository: {repository}")
seen.add(repository)
if not 0 <= project["score"] <= 100:
raise ValueError(f"score outside 0..100: {repository}")
if project["evidence_grade"] not in {"A", "B", "C"}:
raise ValueError(f"invalid evidence grade: {repository}")
return data
def render_chart(data: dict[str, Any], output: Path) -> None:
"""Render a GitHub-readable fixed-background horizontal bar chart."""
try:
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
except ImportError as exc:
raise SystemExit(
'Matplotlib is required. Install it with: pip install -e ".[pdf]"'
) from exc
matplotlib.rcParams["svg.hashsalt"] = "autocad-mcp-source-review-v1"
projects = sorted(data["projects"], key=lambda item: item["score"])
total = len(projects)
# rank 1 = highest score (drawn topmost by barh with ascending sort)
labels = [
f"{total - index}. {item['repository']}" for index, item in enumerate(projects)
]
scores = [item["score"] for item in projects]
grades = [item["evidence_grade"] for item in projects]
# leaderboard palette by rank (rank 1 first), canvas/LLM-benchmark style
rank_palette = [
"#3fb950", # 1 green
"#58a6ff", # 2 sky
"#6e7ce0", # 3 indigo
"#d29922", # 4 amber
"#c4622d", # 5 rust
"#e3b341", # 6 yellow
"#bf4b8a", # 7 magenta
"#f0876e", # 8 salmon
"#8957e5", # 9 purple
]
colors = [
rank_palette[(total - 1 - index) % len(rank_palette)]
for index in range(total)
]
fig, ax = plt.subplots(figsize=(12, 0.62 * total + 2.4), constrained_layout=True)
fig.patch.set_facecolor("#0d1117")
ax.set_facecolor("#0d1117")
bars = ax.barh(labels, scores, color=colors, height=0.62)
ax.set_xlim(0, 100)
ax.set_xlabel("Weighted capability score / 100", color="#e6edf3", labelpad=10)
ax.set_title(
"Public AutoCAD MCP leaderboard — Source-reviewed capability benchmark",
loc="left",
fontsize=17,
fontweight="bold",
color="#e6edf3",
pad=28,
)
ax.text(
0,
1.02,
f"Fixed rubric · reviewed {data['reviewed_at']} · evidence grade shown per project",
transform=ax.transAxes,
color="#8b949e",
fontsize=10,
)
for bar, score, grade in zip(bars, scores, grades, strict=True):
ax.text(
min(score + 1.2, 88),
bar.get_y() + bar.get_height() / 2,
f"{score} / 100 · {grade}",
va="center",
color="#e6edf3",
fontweight="bold",
)
ax.text(
0,
-0.17,
"Shared live-run results are not implied. Scores reflect public-source and recorded test evidence.",
transform=ax.transAxes,
color="#8b949e",
fontsize=9,
)
ax.grid(axis="x", color="#30363d", linewidth=0.8, alpha=0.9)
ax.set_axisbelow(True)
ax.tick_params(axis="x", colors="#8b949e")
ax.tick_params(axis="y", colors="#e6edf3", length=0, pad=8)
for spine in ax.spines.values():
spine.set_visible(False)
output.parent.mkdir(parents=True, exist_ok=True)
fig.savefig(
output,
format="svg",
facecolor=fig.get_facecolor(),
metadata={"Creator": "AutoCAD MCP Pro benchmark renderer", "Date": None},
)
plt.close(fig)
svg = output.read_text(encoding="utf-8")
normalized = "\n".join(line.rstrip() for line in svg.splitlines()) + "\n"
output.write_text(normalized, encoding="utf-8", newline="\n")
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--input", type=Path, default=DEFAULT_INPUT)
parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
return parser
def main() -> int:
args = build_parser().parse_args()
render_chart(load_benchmark(args.input), args.output)
print(f"Rendered benchmark chart: {args.output}")
return 0
if __name__ == "__main__":
raise SystemExit(main())