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Python: Clean left-over WorkflowCompletedEvent (#884)

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* Clean left-over WorkflowCompletedEvent

* Improve comments

* Fix type check error
This commit is contained in:
Tao Chen
2025-09-23 17:52:51 -07:00
committed by GitHub
Unverified
parent 06827e9f1a
commit 36933de345
7 changed files with 18 additions and 19 deletions
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python/samples/getting_started/workflow/parallelism/aggregate_results_of_different_types.py
+11 -10
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@@ -3,7 +3,8 @@
import asyncio
import random
from agent_framework import Executor, WorkflowBuilder, WorkflowCompletedEvent, WorkflowContext, handler
from agent_framework import Executor, WorkflowBuilder, WorkflowContext, WorkflowOutputEvent, handler
from typing_extensions import Never
"""
Sample: Concurrent fan out and fan in with two different tasks that output results of different types.
@@ -52,10 +53,10 @@ class Sum(Executor):
class Aggregator(Executor):
"""Aggregate the results from the different tasks and emit the `WorkflowCompletedEvent`."""
"""Aggregate the results from the different tasks and yield the final output."""
@handler
async def handle(self, results: list[int | float], ctx: WorkflowContext[None]):
async def handle(self, results: list[int | float], ctx: WorkflowContext[Never, list[int | float]]):
"""Receive the results from the source executors.
The framework will automatically collect messages from the source executors
@@ -65,9 +66,9 @@ class Aggregator(Executor):
results (list[int | float]): execution results from upstream executors.
The type annotation must be a list of union types that the upstream
executors will produce.
cts (WorkflowContext[None]): A workflow context.
ctx (WorkflowContext[Never, list[int | float]]): A workflow context that can yield the final output.
"""
await ctx.add_event(WorkflowCompletedEvent(data=results))
await ctx.yield_output(results)
async def main() -> None:
@@ -87,13 +88,13 @@ async def main() -> None:
)
# 3) Run the workflow
completion: WorkflowCompletedEvent | None = None
output: list[int | float] | None = None
async for event in workflow.run_stream([random.randint(1, 100) for _ in range(10)]):
if isinstance(event, WorkflowCompletedEvent):
completion = event
if isinstance(event, WorkflowOutputEvent):
output = event.data
if completion is not None:
print(completion.data)
if output is not None:
print(output)
if __name__ == "__main__":