chore: import upstream snapshot with attribution

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

@@ -0,0 +1,56 @@
+"""
+Per-row MAF workflow for eval-basic.
+
+Converts the `line_process` node from the original PromptFlow evaluation flow.
+Each workflow invocation processes a single (groundtruth, prediction) pair and
+yields "Correct" or "Incorrect".
+
+Original flow graph (per-row nodes only):
+    [inputs: groundtruth, prediction] → [line_process] → output
+"""
+
+import asyncio
+from dataclasses import dataclass
+
+from typing_extensions import Never
+
+from agent_framework import Executor, WorkflowBuilder, WorkflowContext, handler
+
+
+@dataclass
+class EvalInput:
+    groundtruth: str
+    prediction: str
+
+
+class LineProcessExecutor(Executor):
+    """Replaces the `line_process` Python node.
+
+    Compares groundtruth and prediction (case-insensitive) and yields the result.
+    """
+
+    @handler
+    async def process(self, input: EvalInput, ctx: WorkflowContext[Never, str]) -> None:
+        result = "Correct" if input.groundtruth.lower() == input.prediction.lower() else "Incorrect"
+        await ctx.yield_output(result)
+
+
+def create_workflow():
+    """Create a fresh workflow instance.
+
+    MAF workflows do not support concurrent execution, so each batch row
+    needs its own workflow instance.
+    """
+    _line_process = LineProcessExecutor(id="line_process")
+    return WorkflowBuilder(name="EvalBasicRow", start_executor=_line_process).build()
+
+
+async def main():
+    """Quick smoke test with a single row."""
+    wf = create_workflow()
+    result = await wf.run(EvalInput(groundtruth="sunny", prediction="Sunny"))
+    print(result.get_outputs()[0])  # → "Correct"
+
+
+if __name__ == "__main__":
+    asyncio.run(main())