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[BREAKING] Python: Fix workflow as agent streaming output (#3649)

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* WIP: with_output_from

* Add with_output_from to other modules; next: workflow as agent

* WIP: remove agent run events

* orchestrations

* WIP: update samples; next start at guessing_game_With_human_input.py

* Update all samples

* WIP: consolidate workflow as agent streaming vs non-streaming

* Consolidate workflow as agent streaming vs non-streaming

* Move request info event processing to a share method

* Final pass on the samples

* Fix mypy

* Fix mypy

* Comments

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
This commit is contained in:
Tao Chen
2026-02-04 16:16:45 -08:00
committed by GitHub
Unverified
parent 907654a489
commit a971d24f1e
68 changed files with 2652 additions and 2247 deletions
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python/samples/getting_started/workflows/parallelism/aggregate_results_of_different_types.py
-1
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@@ -13,7 +13,6 @@ Purpose:
Show how to construct a parallel branch pattern in workflows. Demonstrate:
- Fan out by targeting multiple executors from one dispatcher.
- Fan in by collecting a list of results from the executors.
- Simple tracing using AgentRunEvent to observe execution order and progress.
Prerequisites:
- Familiarity with WorkflowBuilder, executors, edges, events, and streaming runs.
python/samples/getting_started/workflows/parallelism/fan_out_fan_in_edges.py
+1 -2
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@@ -15,7 +15,7 @@ from agent_framework import ( # Core chat primitives to build LLM requests
WorkflowContext, # Per run context and event bus
WorkflowOutputEvent, # Event emitted when workflow yields output
handler, # Decorator to mark an Executor method as invokable
)
)
from agent_framework.azure import AzureOpenAIChatClient
from azure.identity import AzureCliCredential # Uses your az CLI login for credentials
from typing_extensions import Never
@@ -30,7 +30,6 @@ Purpose:
Show how to construct a parallel branch pattern in workflows. Demonstrate:
- Fan out by targeting multiple AgentExecutor nodes from one dispatcher.
- Fan in by collecting a list of AgentExecutorResponse objects and reducing them to a single result.
- Simple tracing using AgentRunEvent to observe execution order and progress.
Prerequisites:
- Familiarity with WorkflowBuilder, executors, edges, events, and streaming runs.
python/samples/getting_started/workflows/parallelism/map_reduce_and_visualization.py
+3 -2
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@@ -14,7 +14,7 @@ from agent_framework import (
WorkflowOutputEvent, # Event emitted when workflow yields output
WorkflowViz, # Utility to visualize a workflow graph
handler, # Decorator to expose an Executor method as a step
)
)
from typing_extensions import Never
"""
@@ -286,7 +286,8 @@ async def main():
# Step 2: Build the workflow graph using fan out and fan in edges.
workflow = (
workflow_builder.set_start_executor("split_data_executor")
workflow_builder
.set_start_executor("split_data_executor")
.add_fan_out_edges(
"split_data_executor",
["map_executor_0", "map_executor_1", "map_executor_2"],