chore: import upstream snapshot with attribution

examples/flows/evaluation/eval-basic-maf/run_eval.py

@@ -0,0 +1,70 @@
+"""
+Entry point: run the eval-basic evaluation as a batch.
+
+Loads the test dataset, runs the per-row workflow for each row,
+then aggregates results.
+
+Usage:
+    python run_eval.py
+    python run_eval.py --data path/to/data.jsonl --concurrency 10
+"""
+
+import argparse
+import asyncio
+import json
+from pathlib import Path
+
+from aggregation import aggregate
+from eval_runner import EvalResult, EvalRunner
+from workflow import EvalInput, create_workflow
+
+DEFAULT_DATA = Path(__file__).parent / "data.jsonl"
+
+
+def load_dataset(path: Path) -> list[EvalInput]:
+    """Load a JSONL file into a list of EvalInput."""
+    rows = []
+    with open(path, encoding="utf-8") as f:
+        for line in f:
+            line = line.strip()
+            if line:
+                obj = json.loads(line)
+                rows.append(EvalInput(groundtruth=obj["groundtruth"], prediction=obj["prediction"]))
+    return rows
+
+
+async def main(data_path: Path, concurrency: int) -> EvalResult:
+    dataset = load_dataset(data_path)
+    print(f"Loaded {len(dataset)} rows from {data_path}")
+
+    runner = EvalRunner(
+        workflow_factory=create_workflow,
+        aggregate_fn=aggregate,
+        concurrency=concurrency,
+        input_mapping={"values": "processed_results"},
+    )
+
+    result = await runner.run(dataset)
+
+    print("\n--- Per-row outputs ---")
+    for i, output in enumerate(result.per_row_outputs):
+        print(f"  Row {i}: {output}")
+
+    print("\n--- Metrics ---")
+    for key, value in result.metrics.items():
+        print(f"  {key}: {value}")
+
+    if result.errors:
+        print(f"\n--- Errors ({len(result.errors)}) ---")
+        for idx, err in result.errors:
+            print(f"  Row {idx}: {err}")
+
+    return result
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Run eval-basic evaluation batch")
+    parser.add_argument("--data", type=Path, default=DEFAULT_DATA, help="Path to JSONL dataset")
+    parser.add_argument("--concurrency", type=int, default=5, help="Max concurrent workflow runs")
+    args = parser.parse_args()
+    asyncio.run(main(args.data, args.concurrency))