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chore: import upstream snapshot with attribution
2026-07-13 13:39:52 +08:00

61 lines
1.8 KiB
Python

import asyncio
import json
from pathlib import Path
from aggregation import aggregate
from eval_runner import EvalRunner
from workflow import EvalInput, create_workflow
async def test_exact_match():
wf = create_workflow()
result = await wf.run(EvalInput(
entities=["software engineer", "CEO"],
ground_truth='"CEO, Software Engineer, Finance Manager"'
))
output = result.get_outputs()[0]
assert output["exact_match"] == 0
assert output["partial_match"] == 1
print("PASS: test_exact_match")
async def test_batch():
dataset = [
EvalInput(entities=["CEO"], ground_truth="CEO, Engineer"),
EvalInput(entities=["CEO", "Engineer"], ground_truth="CEO, Engineer"),
]
runner = EvalRunner(
workflow_factory=create_workflow,
aggregate_fn=aggregate,
concurrency=5,
)
result = await runner.run(dataset)
assert result.metrics["partial_match_rate"] == 1.0
print("PASS: test_batch")
async def test_data_jsonl():
"""Run eval on every row in data.jsonl"""
data_path = Path(__file__).parent / "data.jsonl"
rows = [json.loads(line) for line in data_path.read_text(encoding="utf-8").splitlines() if line.strip()]
wf = create_workflow()
for i, row in enumerate(rows):
result = await wf.run(EvalInput(
entities=row["entities"],
ground_truth=row["ground_truth"],
))
output = result.get_outputs()[0]
assert isinstance(output, dict), f"Row {i}: expected dict, got {type(output)}"
print(f" Row {i}: output={output}")
print(f"PASS: test_data_jsonl ({len(rows)} rows)")
async def main():
await test_exact_match()
await test_batch()
await test_data_jsonl()
print("\nAll tests passed!")
if __name__ == "__main__":
asyncio.run(main())