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