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from __future__ import annotations
import argparse
import asyncio
import json
import os
from collections import Counter
from collections.abc import Sequence
from pathlib import Path
from typing import Any
from autocad_bench.bundle import export_bundle, validate_bundle
from autocad_bench.common.paths import BENCHMARK_ROOT
from autocad_bench.common.runtime_contract import DEFAULT_EVALUATOR_VERSION
from autocad_bench.tasks.audit import load_gold_audit
from autocad_bench.tasks.manifest import SplitSelector, load_manifest, load_public_tasks
from autocad_bench.evaluation.scoring.evaluator import HttpDWGEvaluator
from autocad_bench.evaluation.scoring.gold_cache import (
DEFAULT_GOLD_CACHE_ROOT,
GoldCacheStore,
build_gold_cache,
)
from autocad_bench.evaluation.scoring.models import sha256_bytes
from autocad_bench.evaluation.scoring.vision_judge import (
DEFAULT_VISION_JUDGE_MODEL,
DEFAULT_VISION_JUDGE_REASONING,
OpenAIVisionJudge,
build_vision_evidence,
load_evaluated_drawing,
write_vision_judge_artifacts,
)
def _validate() -> int:
entries = load_manifest()
summary = {
"tasks": len(entries),
"enabled": sum(entry.enabled for entry in entries),
"dev": sum(entry.enabled and entry.split == "dev" for entry in entries),
"eval": sum(entry.enabled and entry.split == "eval" for entry in entries),
"levels": dict(Counter(entry.level for entry in entries)),
"drawing_types": dict(Counter(entry.drawing_type for entry in entries)),
"dwg_signature": "AC1032",
"status": "ok",
}
print(json.dumps(summary, indent=2, sort_keys=True))
return 0
def _list_tasks(split: SplitSelector) -> int:
tasks = load_public_tasks(split)
print(json.dumps([task.model_dump(mode="json") for task in tasks], indent=2))
return 0
def _validate_audit() -> int:
entries = load_gold_audit()
summary = {
"tasks": len(entries),
"machine_checks_passed": sum(entry.machine_checks == "passed" for entry in entries),
"reference_reviews_pending": sum(
entry.reference_review == "pending" for entry in entries
),
"autocad_reviews_pending": sum(entry.autocad_review == "pending" for entry in entries),
"development_tasks": [
entry.task_id for entry in entries if entry.selected_for_dev
],
"status": "ok",
}
print(json.dumps(summary, indent=2, sort_keys=True))
return 0
def _export_bundle(args: argparse.Namespace) -> int:
if args.source_only and args.evaluator_version:
raise SystemExit(
"--source-only cannot be combined with --evaluator-version"
)
evaluator_versions = (
()
if args.source_only
else tuple(args.evaluator_version or [DEFAULT_EVALUATOR_VERSION])
)
bundle = export_bundle(
args.output,
source_root=args.source_root,
evaluator_versions=evaluator_versions,
)
print(
json.dumps(
{
"bundle_root": str(Path(args.output).expanduser().resolve()),
"bundle_version": bundle.bundle_version,
"tasks": bundle.task_count,
"evaluator_versions": list(bundle.evaluator_versions),
"files": len(bundle.files),
"bytes": sum(entry.bytes for entry in bundle.files),
"status": "ok",
},
indent=2,
sort_keys=True,
)
)
return 0
def _validate_bundle(args: argparse.Namespace) -> int:
bundle = validate_bundle(args.root)
print(
json.dumps(
{
"bundle_root": str(Path(args.root).expanduser().resolve()),
"bundle_version": bundle.bundle_version,
"tasks": bundle.task_count,
"evaluator_versions": list(bundle.evaluator_versions),
"files": len(bundle.files),
"bytes": sum(entry.bytes for entry in bundle.files),
"status": "ok",
},
indent=2,
sort_keys=True,
)
)
return 0
def _build_gold_cache(args: argparse.Namespace) -> int:
token = os.environ.get(args.token_env)
if not token:
raise SystemExit(f"required evaluator token is not set: {args.token_env}")
evaluator = HttpDWGEvaluator(
args.evaluator_url,
token=token,
evaluator_version=args.evaluator_version,
timeout_s=args.timeout_s,
)
store = GoldCacheStore(
evaluator_version=args.evaluator_version,
root=Path(args.root),
)
async def run() -> tuple[str, ...]:
await evaluator.health()
return await build_gold_cache(evaluator, store, split=args.split)
built = asyncio.run(run())
print(
json.dumps(
{
"evaluator_version": args.evaluator_version,
"split": args.split,
"built": list(built),
"count": len(built),
"status": "ok",
},
indent=2,
sort_keys=True,
)
)
return 0
def _verify_gold_cache(args: argparse.Namespace) -> int:
selected = tuple(
entry
for entry in load_manifest()
if entry.enabled and (args.split == "all" or entry.split == args.split)
)
task_ids = tuple(entry.task_id for entry in selected)
expected_checksums = {
entry.task_id: sha256_bytes(entry.resolve_gold_path().read_bytes())
for entry in selected
}
store = GoldCacheStore(
evaluator_version=args.evaluator_version,
root=Path(args.root),
)
verified = store.verify(
task_ids,
expected_source_sha256=expected_checksums,
)
print(
json.dumps(
{
"evaluator_version": args.evaluator_version,
"split": args.split,
"verified": list(verified),
"count": len(verified),
"status": "ok",
},
indent=2,
sort_keys=True,
)
)
return 0
def _vision_judge(args: argparse.Namespace) -> int:
api_key = os.environ.get(args.api_key_env)
if not api_key:
raise SystemExit(f"required OpenAI credential is not set: {args.api_key_env}")
rollout_dir = Path(args.rollout_dir).expanduser().resolve()
candidate_dwg_path = rollout_dir / "attempt.dwg"
candidate_metadata_path = rollout_dir / "evaluation" / "metadata.json"
candidate_render_path = rollout_dir / "evaluation" / "render.png"
required = (
candidate_dwg_path,
candidate_metadata_path,
candidate_render_path,
)
missing = [str(path) for path in required if not path.is_file()]
if missing:
raise SystemExit("missing rollout evaluation artifacts: " + ", ".join(missing))
entries = {entry.task_id: entry for entry in load_manifest()}
try:
entry = entries[args.task_id]
except KeyError as exc:
raise SystemExit(f"unknown task_id: {args.task_id}") from exc
candidate = load_evaluated_drawing(
candidate_metadata_path, candidate_render_path
)
store = GoldCacheStore(
evaluator_version=candidate.metadata.evaluator_version,
root=Path(args.gold_cache_root),
)
gold = store.load(args.task_id)
candidate_dwg = candidate_dwg_path.read_bytes()
gold_dwg_path = entry.resolve_gold_path()
gold_dwg = gold_dwg_path.read_bytes()
reference_path = entry.resolve_image_path()
reference_png = reference_path.read_bytes()
evidence = build_vision_evidence(
task_id=args.task_id,
units=entry.units,
drawing_type=entry.drawing_type,
candidate_dwg=candidate_dwg,
gold_dwg=gold_dwg,
reference_png=reference_png,
candidate=candidate,
gold=gold,
)
image_artifacts = (
{
"role": "reference_image",
"artifact_path": str(reference_path),
"sha256": sha256_bytes(reference_png),
},
{
"role": "gold_dwg_render",
"artifact_path": str(
Path(args.gold_cache_root)
/ candidate.metadata.evaluator_version
/ args.task_id
/ "render.png"
),
"sha256": sha256_bytes(gold.render_png),
},
{
"role": "candidate_dwg_render",
"artifact_path": str(candidate_render_path),
"sha256": sha256_bytes(candidate.render_png),
},
{
"role": "candidate_dwg_binary_not_sent",
"artifact_path": str(candidate_dwg_path),
"sha256": sha256_bytes(candidate_dwg),
},
{
"role": "gold_dwg_binary_not_sent",
"artifact_path": str(gold_dwg_path),
"sha256": sha256_bytes(gold_dwg),
},
)
judge = OpenAIVisionJudge(
api_key=api_key,
model_id=args.model,
reasoning_effort=args.reasoning_effort,
max_output_tokens=args.max_output_tokens,
timeout_s=args.timeout_s,
max_request_attempts=args.max_request_attempts,
)
async def run() -> Any:
return await judge.judge(
task_id=args.task_id,
candidate_dwg_sha256=sha256_bytes(candidate_dwg),
gold_dwg_sha256=sha256_bytes(gold_dwg),
evidence=evidence,
reference_png=reference_png,
gold_render_png=gold.render_png,
candidate_render_png=candidate.render_png,
sample_count=args.samples,
image_artifacts=image_artifacts,
)
judged = asyncio.run(run())
output_dir = (
Path(args.output_dir).expanduser().resolve()
if args.output_dir
else rollout_dir / "evaluation" / "vision-judge"
)
score_path = write_vision_judge_artifacts(output_dir, judged)
print(
json.dumps(
{
"task_id": args.task_id,
"model": args.model,
"samples": args.samples,
"overall_score": judged.result.overall_score,
"verdict": judged.result.verdict,
"target_acquired": judged.result.target_acquired,
"confidence": judged.result.confidence,
"needs_human_review": judged.result.needs_human_review,
"score_path": str(score_path),
},
indent=2,
sort_keys=True,
)
)
return 0
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(prog="autocad-bench")
subparsers = parser.add_subparsers(dest="command", required=True)
subparsers.add_parser("validate", help="validate the complete source manifest")
list_parser = subparsers.add_parser(
"list", help="print model-safe public task rows"
)
list_parser.add_argument("--split", choices=("dev", "eval", "all"), default="all")
subparsers.add_parser(
"validate-audit", help="validate the machine-level gold audit inventory"
)
export_parser = subparsers.add_parser(
"bundle-export",
help="export a portable, checksum-bound benchmark data directory",
)
export_parser.add_argument("--output", type=Path, required=True)
export_parser.add_argument(
"--source-root",
type=Path,
default=BENCHMARK_ROOT,
help="checkout or bundle containing tasks/ and artifacts/",
)
export_parser.add_argument(
"--evaluator-version",
action="append",
help=(
"gold-cache version to include; repeat as needed "
f"(default: {DEFAULT_EVALUATOR_VERSION})"
),
)
export_parser.add_argument(
"--source-only",
action="store_true",
help="omit generated gold-cache entries",
)
validate_bundle_parser = subparsers.add_parser(
"bundle-validate",
help="verify a portable benchmark bundle and all file checksums",
)
validate_bundle_parser.add_argument("--root", type=Path, required=True)
build_cache_parser = subparsers.add_parser(
"build-gold-cache", help="build trusted gold renders using the Windows evaluator"
)
build_cache_parser.add_argument("--evaluator-url", required=True)
build_cache_parser.add_argument("--evaluator-version", required=True)
build_cache_parser.add_argument("--root", default=str(DEFAULT_GOLD_CACHE_ROOT))
build_cache_parser.add_argument("--split", choices=("dev", "eval", "all"), default="dev")
build_cache_parser.add_argument(
"--token-env", default="AUTOCAD_EVALUATOR_TOKEN"
)
build_cache_parser.add_argument("--timeout-s", type=float, default=120.0)
verify_cache_parser = subparsers.add_parser(
"verify-gold-cache", help="verify gold cache completeness and checksums"
)
verify_cache_parser.add_argument("--evaluator-version", required=True)
verify_cache_parser.add_argument("--root", default=str(DEFAULT_GOLD_CACHE_ROOT))
verify_cache_parser.add_argument(
"--split", choices=("dev", "eval", "all"), default="dev"
)
vision_parser = subparsers.add_parser(
"vision-judge",
help="judge one evaluated rollout with GPT-5.6 Sol vision",
)
vision_parser.add_argument("--task-id", required=True)
vision_parser.add_argument("--rollout-dir", required=True)
vision_parser.add_argument("--gold-cache-root", default=str(DEFAULT_GOLD_CACHE_ROOT))
vision_parser.add_argument("--output-dir")
vision_parser.add_argument("--api-key-env", default="OPENAI_API_KEY")
vision_parser.add_argument("--model", default=DEFAULT_VISION_JUDGE_MODEL)
vision_parser.add_argument(
"--reasoning-effort",
choices=("none", "low", "medium", "high", "xhigh", "max"),
default=DEFAULT_VISION_JUDGE_REASONING,
)
vision_parser.add_argument("--samples", type=int, choices=range(1, 6), default=1)
vision_parser.add_argument("--max-output-tokens", type=int, default=32768)
vision_parser.add_argument("--timeout-s", type=float, default=600.0)
vision_parser.add_argument("--max-request-attempts", type=int, default=3)
return parser
def main(argv: Sequence[str] | None = None) -> int:
args = build_parser().parse_args(argv)
if args.command == "validate":
return _validate()
if args.command == "list":
return _list_tasks(args.split)
if args.command == "validate-audit":
return _validate_audit()
if args.command == "bundle-export":
return _export_bundle(args)
if args.command == "bundle-validate":
return _validate_bundle(args)
if args.command == "build-gold-cache":
return _build_gold_cache(args)
if args.command == "verify-gold-cache":
return _verify_gold_cache(args)
if args.command == "vision-judge":
return _vision_judge(args)
raise AssertionError(f"unhandled command: {args.command}")
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