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import hashlib
import json
import httpx
import pytest
from jev_adapter.benchmarks.compare import collect
from jev_adapter.benchmarks.data import normalize_record
from jev_adapter.benchmarks.metrics import metrics, prediction_rows, summarize
from jev_adapter.benchmarks.run import evaluate, load_data, validate_launch
def item(record_id="one", variant="clean", source="policy"):
return normalize_record(
{
"state": "The transaction is refundable.",
"questions": {
"route": {
"type": "choice",
"instructions": "Choose a team.",
"criteria": {"billing": None, "support": "Technical support"},
"label": "billing",
"src": "route",
},
"refund": {
"type": "noul",
"instructions": "Refundable?",
"label": True,
"src": "refund",
},
"priority": {
"type": "score",
"instructions": "How urgent?",
"criteria": ["low", "mid", "high"],
"label": 2,
"src": "priority",
},
},
"_meta": {
"id": record_id,
"source": source,
"variant": variant,
"group_id": record_id,
},
},
"fixture",
"development",
)
def response():
return {
"model": "decision-model",
"answers": {
"route": {
"type": "choice",
"probabilities": {"billing": 0.8, "support": 0.2},
},
"refund": {"type": "noul", "noul": 0.9},
"priority": {
"type": "score",
"probabilities": {"0": 0.1, "1": 0.2, "2": 0.7},
},
},
"usage": {"input_tokens": 100, "output_tokens": 0},
"metadata": {"adapter_elapsed_ms": 2.0, "evaluations": 3},
}
def test_metrics_boolean_order_score_and_calibration():
rows = prediction_rows(item(), response())
assert rows[1]["keys"] == ["false", "true"]
assert rows[1]["p"] == pytest.approx([0.1, 0.9])
result = metrics(rows)
assert result["n"] == 3
assert result["acc"] == 1
assert result["ece"] == pytest.approx(0.2)
assert result["brier"] == pytest.approx((0.08 + 0.02 + 0.14) / 3)
assert result["score_mae"] == pytest.approx(0.4)
assert result["ranked_probability_score"] == pytest.approx(0.05)
def test_jevbench_probability_reference_and_native_tie_break():
example = item()
example["metadata"]["gold_policy"] = {"argmax_tie_break": "lexicographic_label"}
example["expected"]["route"].update(
labels=["support", "billing"],
label=1,
target=[0, 1],
reference_probs=[0.5, 0.5],
)
body = response()
body["answers"]["route"]["probabilities"] = {"support": 0.5, "billing": 0.5}
rows = prediction_rows(example, body)
assert metrics(rows)["acc"] == 1
report = summarize(rows)
assert report["reference_distribution"]["n"] == 1
assert report["reference_distribution"]["squared_l2"] == 0
assert report["reference_distribution"]["total_variation"] == 0
assert report["reference_distribution"]["kl_reference_to_model"] == 0
def test_unknown_excluded_and_permutation_aligned():
original = item()
permuted = item("two", "permuted")
permuted["metadata"]["group_id"] = "one"
permuted["expected"]["route"].update(
labels=["support", "billing"], label=1, target=[0, 1]
)
unknown = item("three", source="unknowable")
rows = [
row
for i in [original, permuted, unknown]
for row in prediction_rows(i, response())
]
report = summarize(rows)
assert report["clean"]["n"] == 3
assert report["unknowable"]["n"] == 3
assert report["permutation"]["n"] == 1
assert report["permutation"]["flip_rate"] == 0
assert "unknowable" not in report["sources"]
@pytest.mark.parametrize("change", ["missing", "nan", "output", "type"])
def test_invalid_predictions_rejected(change):
body = response()
if change == "missing":
del body["answers"]["route"]["probabilities"]["support"]
elif change == "nan":
body["answers"]["refund"]["noul"] = float("nan")
elif change == "type":
body["answers"]["refund"]["type"] = "choice"
else:
body["answers"]["route"]["probabilities"] = {"billing": 0.9, "support": 0.9}
with pytest.raises(ValueError):
prediction_rows(item(), body)
def arguments(tmp_path, records=None):
data = tmp_path / "data.jsonl"
records = records or [item(), item("two")]
data.write_text("".join(json.dumps(i) + "\n" for i in records))
return argparse.Namespace(
data=[data],
model="decision-model",
allow_test=False,
limit=None,
output=tmp_path / "result",
concurrency=2,
repeats=2,
warmup=2,
seed=42,
cache_mode="full-prefill",
timeout=10,
engine_url="http://engine",
base_url="http://adapter",
engine_manifest=None,
assistant_prefix=None,
)
@pytest.mark.asyncio
async def test_runner_outputs_and_excludes_warmup_repeat_quality(tmp_path):
args = arguments(tmp_path)
seen = []
def transport(request):
if request.url.path == "/model_info":
return httpx.Response(200, json={"served_model_name": "decision-model"})
if request.url.path == "/server_info":
return httpx.Response(
200,
json={
"disable_radix_cache": True,
"mm_preprocess_cache_size_mb": 0,
"api_key": "secret",
},
)
payload = json.loads(request.content)
seen.append(payload)
assert "expected" not in payload and "metadata" not in payload
assert all(
"label" not in q and "src" not in q for q in payload["questions"].values()
)
return httpx.Response(200, json=response())
async with httpx.AsyncClient(transport=httpx.MockTransport(transport)) as client:
result = await evaluate(args, client)
assert len(seen) == 6
assert result["status"] == "complete"
assert result["successful_requests"] == 4
assert result["suites"]["fixture/development"]["clean"]["n"] == 6
assert result["latency_ms"]["n"] == 4
assert "secret" not in (args.output / "manifest.json").read_text()
assert len((args.output / "predictions.jsonl").read_text().splitlines()) == 4
comparison = collect(args.output)
assert len(comparison) == 1 and comparison[0]["clean_questions"] == 6
assert comparison[0]["partial_dataset"] is True
with pytest.raises(FileExistsError):
await evaluate(args)
(args.output / "invalidated.json").write_text(
json.dumps({"reason": "Tokenization failed an independent canonical check"})
)
assert collect(args.output) == []
@pytest.mark.asyncio
async def test_runner_errors_do_not_produce_headline_or_retry(tmp_path):
args = arguments(tmp_path)
args.warmup = 0
calls = 0
def transport(request):
nonlocal calls
if request.url.path == "/model_info":
return httpx.Response(200, json={"served_model_name": "decision-model"})
if request.url.path == "/server_info":
return httpx.Response(
200,
json={"disable_radix_cache": True, "mm_preprocess_cache_size_mb": 0},
)
calls += 1
body = response()
body["usage"]["output_tokens"] = 1
return httpx.Response(200, json=body)
async with httpx.AsyncClient(transport=httpx.MockTransport(transport)) as client:
result = await evaluate(args, client)
assert result["status"] == "failed"
assert result["suites"] == {}
assert result["errors"] == 4 and calls == 4
assert (args.output / "failures.json").exists()
assert collect(args.output) == []
def test_locked_split_and_data_integrity(tmp_path):
locked = item()
locked["split"] = "test"
args = arguments(tmp_path, [locked])
with pytest.raises(ValueError, match="allow-test"):
load_data(args.data, args.model)
assert len(load_data(args.data, args.model, allow_test=True)[0]) == 1
args.data[0].with_suffix(".manifest.json").write_text(
json.dumps({"data_sha256": "bad"})
)
with pytest.raises(ValueError, match="checksum"):
load_data(args.data, args.model, allow_test=True)
def test_prepared_subset_metadata_is_retained(tmp_path):
args = arguments(tmp_path)
raw = args.data[0].read_bytes()
args.data[0].with_suffix(".manifest.json").write_text(
json.dumps(
{
"data_sha256": hashlib.sha256(raw).hexdigest(),
"selected": {"records": 2},
"selection": {"is_full_partition": False},
}
)
)
_, sources = load_data(args.data, args.model)
assert sources[0]["prepared_manifest"]["selection"]["is_full_partition"] is False
def test_launch_cannot_label_another_checkpoint():
launch = {
"model": {
"repo_id": "Qwen/one",
"revision": "abc",
"dtype": "bfloat16",
"quantization": None,
},
"profile": "one",
"engine": {"revision": "def"},
}
snapshot = {
"server_info": {
"model_path": "Qwen/one",
"revision": "abc",
"dtype": "bfloat16",
"quantization": None,
},
"model_info": {"model_path": "Qwen/one"},
}
validate_launch(snapshot, launch)
snapshot["server_info"]["revision"] = "changed"
with pytest.raises(ValueError, match="revision"):
validate_launch(snapshot, launch)
|