chore: import upstream snapshot with attribution

python/samples/03-workflows/observability/executor_io_observation.py

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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from typing import Any, cast
+
+from agent_framework import (
+    Executor,
+    WorkflowBuilder,
+    WorkflowContext,
+    handler,
+)
+from typing_extensions import Never
+
+"""
+Executor I/O Observation
+
+This sample demonstrates how to observe executor input and output data without modifying
+executor code. This is useful for debugging, logging, or building monitoring tools.
+
+What this example shows:
+- executor_invoked events (type='executor_invoked') contain the input message in event.data
+- executor_completed events (type='executor_completed') contain the messages sent via ctx.send_message() in event.data
+- How to generically observe all executor I/O through workflow streaming events
+
+Prerequisites:
+- No external services required.
+"""
+
+
+class UpperCaseExecutor(Executor):
+    """Convert input text to uppercase and forward to next executor."""
+
+    def __init__(self, id: str = "upper_case"):
+        super().__init__(id=id)
+
+    @handler
+    async def handle(self, text: str, ctx: WorkflowContext[str]) -> None:
+        result = text.upper()
+        await ctx.send_message(result)
+
+
+class ReverseTextExecutor(Executor):
+    """Reverse the input text and yield as workflow output."""
+
+    def __init__(self, id: str = "reverse_text"):
+        super().__init__(id=id)
+
+    @handler
+    async def handle(self, text: str, ctx: WorkflowContext[Never, str]) -> None:
+        result = text[::-1]
+        await ctx.yield_output(result)
+
+
+def format_io_data(data: Any) -> str:
+    """Format executor I/O data for display.
+
+    This helper formats common data types for readable output.
+    Customize based on the types used in your workflow.
+    """
+    type_name = type(data).__name__
+
+    if data is None:
+        return "None"
+    if isinstance(data, str):
+        preview = data[:80] + "..." if len(data) > 80 else data
+        return f"{type_name}: '{preview}'"
+    if isinstance(data, list):
+        data_list = cast(list[Any], data)
+        if len(data_list) == 0:
+            return f"{type_name}: []"
+        # For sent_messages, show each item with its type
+        if len(data_list) <= 3:
+            items = [format_io_data(item) for item in data_list]
+            return f"{type_name}: [{', '.join(items)}]"
+        return f"{type_name}: [{len(data_list)} items]"
+    return f"{type_name}: {repr(data)}"
+
+
+async def main() -> None:
+    """Build a workflow and observe executor I/O through streaming events."""
+    upper_case = UpperCaseExecutor()
+    reverse_text = ReverseTextExecutor()
+
+    workflow = WorkflowBuilder(start_executor=upper_case).add_edge(upper_case, reverse_text).build()
+
+    print("Running workflow with executor I/O observation...\n")
+
+    async for event in workflow.run("hello world", stream=True):
+        if event.type == "executor_invoked":
+            # The input message received by the executor is in event.data
+            print(f"[INVOKED] {event.executor_id}")
+            print(f"    Input: {format_io_data(event.data)}")
+
+        elif event.type == "executor_completed":
+            # Messages sent via ctx.send_message() are in event.data
+            print(f"[COMPLETED] {event.executor_id}")
+            if event.data:
+                print(f"    Output: {format_io_data(event.data)}")
+
+        elif event.type == "output":
+            print(f"[WORKFLOW OUTPUT] {format_io_data(event.data)}")
+
+    """
+    Sample Output:
+
+    Running workflow with executor I/O observation...
+
+    [INVOKED] upper_case
+        Input: str: 'hello world'
+    [COMPLETED] upper_case
+        Output: list: [str: 'HELLO WORLD']
+    [INVOKED] reverse_text
+        Input: str: 'HELLO WORLD'
+    [WORKFLOW OUTPUT] str: 'DLROW OLLEH'
+    [COMPLETED] reverse_text
+        Output: list: [str: 'DLROW OLLEH']
+    """
+
+
+if __name__ == "__main__":
+    asyncio.run(main())