wehub-resource-sync
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66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
import asyncio
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import json
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from pathlib import Path
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from aggregation import aggregate
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from eval_runner import EvalRunner
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from workflow import EvalInput, create_workflow
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async def test_correct():
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wf = create_workflow()
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result = await wf.run(EvalInput(groundtruth="APP", prediction="APP"))
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assert result.get_outputs()[0] == "Correct"
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print("PASS: test_correct")
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async def test_incorrect():
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wf = create_workflow()
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result = await wf.run(EvalInput(groundtruth="APP", prediction="WEB"))
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assert result.get_outputs()[0] == "Incorrect"
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print("PASS: test_incorrect")
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async def test_batch():
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dataset = [
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EvalInput(groundtruth="APP", prediction="APP"),
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EvalInput(groundtruth="Channel", prediction="Channel"),
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EvalInput(groundtruth="Academic", prediction="Finance"),
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]
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runner = EvalRunner(
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workflow_factory=create_workflow,
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aggregate_fn=aggregate,
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concurrency=5,
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input_mapping={"values": "grades"},
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)
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result = await runner.run(dataset)
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assert result.metrics["accuracy"] == 0.67
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print("PASS: test_batch")
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async def test_data_jsonl():
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"""Run eval on every row in data.jsonl"""
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data_path = Path(__file__).parent / "data.jsonl"
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rows = [json.loads(line) for line in data_path.read_text(encoding="utf-8").splitlines() if line.strip()]
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wf = create_workflow()
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for i, row in enumerate(rows):
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result = await wf.run(EvalInput(
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groundtruth=row["groundtruth"],
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prediction=row["prediction"],
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))
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grade = result.get_outputs()[0]
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assert grade in ("Correct", "Incorrect"), f"Row {i}: unexpected grade '{grade}'"
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print(f" Row {i}: grade={grade}")
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print(f"PASS: test_data_jsonl ({len(rows)} rows)")
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async def main():
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await test_correct()
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await test_incorrect()
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await test_batch()
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await test_data_jsonl()
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print("\nAll tests passed!")
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if __name__ == "__main__":
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asyncio.run(main())
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