chore: import upstream snapshot with attribution

python/samples/03-workflows/functional/basic_pipeline.py

@@ -0,0 +1,58 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Basic sequential pipeline using the functional workflow API.
+
+The simplest possible workflow: plain async functions orchestrated by @workflow.
+No @step decorator needed — just write Python.
+"""
+
+import asyncio
+
+from agent_framework import workflow
+
+
+# These are plain async functions — no decorators needed.
+# They run normally inside the workflow, just like any other Python function.
+async def fetch_data(url: str) -> dict[str, str | int]:
+    """Simulate fetching data from a URL."""
+    return {"url": url, "content": f"Data from {url}", "status": 200}
+
+
+async def transform_data(data: dict[str, str | int]) -> str:
+    """Transform raw data into a summary string."""
+    return f"[{data['status']}] {data['content']}"
+
+
+# @workflow turns this async function into a FunctionalWorkflow object.
+# Without it, this is just a normal async function. With it, you get:
+#   - .run() that returns a WorkflowRunResult with events and outputs
+#   - .run(stream=True) for streaming events in real time
+#   - .as_agent() to use this workflow anywhere an agent is expected
+#
+# The function's first parameter receives the input from .run("...").
+# Add a `ctx: RunContext` parameter only if you need HITL, state, or custom events.
+@workflow
+async def data_pipeline(url: str) -> str:
+    """A simple sequential data pipeline."""
+    raw = await fetch_data(url)
+    summary = await transform_data(raw)
+
+    # This is just a function — plain Python works between calls.
+    # No need to wrap every operation in a separate async function.
+    is_valid = len(summary) > 0 and "[200]" in summary
+    tag = "VALID" if is_valid else "INVALID"
+
+    # Returning a value automatically emits it as an output.
+    # Callers retrieve it via result.get_outputs().
+    return f"[{tag}] {summary}"
+
+
+async def main():
+    # .run() is provided by @workflow — a plain async function wouldn't have it
+    result = await data_pipeline.run("https://example.com/api/data")
+    print("Output:", result.get_outputs()[0])
+    print("State:", result.get_final_state())
+
+
+if __name__ == "__main__":
+    asyncio.run(main())