Datasets:
Tasks:
Document Question Answering
Size:
n<1K
Tags:
benchmark
document-ai
information-extraction
structured-extraction
key-information-extraction
ocr
License:
File size: 1,792 Bytes
8143f06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | import importlib.util
import json
from pathlib import Path
import pytest
ROOT = Path(__file__).resolve().parent.parent
def load_module(name: str, relpath: str):
spec = importlib.util.spec_from_file_location(name, ROOT / relpath)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
build_data = load_module("build_data", "space/build_data.py")
def test_build_data_structure():
data = build_data.build()
summary = json.loads((ROOT / "results" / "summary.json").read_text())
engine_keys = [e["key"] for e in data["engines"]]
assert engine_keys == list(summary["aggregates"].keys())
assert len(data["documents"]) == summary["benchmark"]["doc_count"]
assert data["breakdowns"]["capability"], "expected at least one capability row"
for doc in data["documents"]:
assert set(doc["scores"].keys()) == set(engine_keys)
assert doc["name"] and doc["ftype"] and doc["lang"]
def test_committed_leaderboard_json_is_in_sync():
# the Space ships a committed copy; it must match a fresh build so it never goes stale
committed = json.loads((ROOT / "space" / "leaderboard.json").read_text())
assert committed == build_data.build(), "run `python3 space/build_data.py` to refresh space/leaderboard.json"
def test_app_tables():
pytest.importorskip("pandas")
pytest.importorskip("gradio")
app = load_module("space_app", "space/app.py")
leaderboard = app.leaderboard_df()
assert len(leaderboard) == len(app.ENGINES)
assert list(leaderboard["Rank"]) == sorted(leaderboard["Rank"])
all_docs = app.documents_df()
assert len(all_docs) == len(app.DATA["documents"])
rtl_docs = app.documents_df(capability="rtl")
assert 0 < len(rtl_docs) < len(all_docs)
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