chore: import upstream snapshot with attribution

examples/flows/evaluation/eval-accuracy-maths-to-code-maf/test_eval.py

@@ -0,0 +1,75 @@
+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_single_correct():
+    wf = create_workflow()
+    result = await wf.run(EvalInput(groundtruth="1.0", prediction="1"))
+    assert result.get_outputs()[0] == 1
+    print("PASS: test_single_correct")
+
+
+async def test_single_incorrect():
+    wf = create_workflow()
+    result = await wf.run(EvalInput(groundtruth="2.1", prediction="2.0"))
+    assert result.get_outputs()[0] == 0
+    print("PASS: test_single_incorrect")
+
+
+async def test_json_error():
+    wf = create_workflow()
+    result = await wf.run(EvalInput(groundtruth="1.0", prediction="JSONDecodeError"))
+    assert result.get_outputs()[0] == -1
+    print("PASS: test_json_error")
+
+
+async def test_batch():
+    dataset = [
+        EvalInput(groundtruth="1.0", prediction="1"),
+        EvalInput(groundtruth="3.14", prediction="3.1415926"),
+        EvalInput(groundtruth="1.0", prediction="JSONDecodeError"),
+    ]
+    runner = EvalRunner(
+        workflow_factory=create_workflow,
+        aggregate_fn=aggregate,
+        concurrency=5,
+        input_mapping={"values": "processed_results"},
+    )
+    result = await runner.run(dataset)
+    assert result.metrics["num_total"] == 3
+    assert result.metrics["num_correct"] == 2
+    assert result.metrics["num_exception"] == 1
+    print("PASS: test_batch")
+
+
+async def test_data_jsonl():
+    """Run eval on every row in test_data.jsonl"""
+    data_path = Path(__file__).parent / "test_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(
+            groundtruth=row["groundtruth"],
+            prediction=row["answer"],
+        ))
+        score = result.get_outputs()[0]
+        assert isinstance(score, int), f"Row {i}: expected int, got {type(score)}"
+        print(f"  Row {i}: score={score}")
+    print(f"PASS: test_data_jsonl ({len(rows)} rows)")
+
+
+async def main():
+    await test_single_correct()
+    await test_single_incorrect()
+    await test_json_error()
+    await test_batch()
+    await test_data_jsonl()
+    print("\nAll tests passed!")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())