Datasets:
Tasks:
Document Question Answering
Size:
n<1K
Tags:
benchmark
document-ai
information-extraction
structured-extraction
key-information-extraction
ocr
License:
| 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) | |