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[BREAKING] Python: Refactor workflow events to unified discriminated union pattern (#3690)

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* Refactor events

* Merge main

* Fixes

* Cleanup

* Update samples and tests

* Remove unused imports

* PR feedback

* Merge main. Add properties for events to help typing

* Formatting

* Cleanup

* use builtins.type to avoid shadowing by WorkflowEvent.type attribute

* Final improvements
This commit is contained in:
Evan Mattson
2026-02-06 16:47:20 +09:00
committed by GitHub
Unverified
parent 09f59b21ad
commit 0f3f4dbcaf
127 changed files with 1646 additions and 1703 deletions
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python/samples/getting_started/orchestrations/magentic.py
+32 -30
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@@ -9,12 +9,11 @@ from agent_framework import (
AgentResponseUpdate,
ChatAgent,
ChatMessage,
GroupChatRequestSentEvent,
HostedCodeInterpreterTool,
WorkflowOutputEvent,
WorkflowEvent,
)
from agent_framework.openai import OpenAIChatClient, OpenAIResponsesClient
from agent_framework.orchestrations import MagenticBuilder, MagenticOrchestratorEvent, MagenticProgressLedger
from agent_framework.orchestrations import GroupChatRequestSentEvent, MagenticBuilder, MagenticProgressLedger
logging.basicConfig(level=logging.WARNING)
logger = logging.getLogger(__name__)
@@ -85,7 +84,7 @@ async def main() -> None:
max_reset_count=2,
)
# Enable intermediate outputs to observe the conversation as it unfolds
# Intermediate outputs will be emitted as WorkflowOutputEvent events
# Intermediate outputs will be emitted as WorkflowEvent events
.with_intermediate_outputs()
.build()
)
@@ -104,41 +103,44 @@ async def main() -> None:
# Keep track of the last executor to format output nicely in streaming mode
last_response_id: str | None = None
output_event: WorkflowEvent | None = None
async for event in workflow.run(task, stream=True):
if isinstance(event, MagenticOrchestratorEvent):
print(f"\n[Magentic Orchestrator Event] Type: {event.event_type.name}")
if isinstance(event.data, ChatMessage):
print(f"Please review the plan:\n{event.data.text}")
elif isinstance(event.data, MagenticProgressLedger):
print(f"Please review progress ledger:\n{json.dumps(event.data.to_dict(), indent=2)}")
if event.type == "output" and isinstance(event.data, AgentResponseUpdate):
response_id = event.data.response_id
if response_id != last_response_id:
if last_response_id is not None:
print("\n")
print(f"- {event.executor_id}:", end=" ", flush=True)
last_response_id = response_id
print(event.data, end="", flush=True)
elif event.type == "magentic_orchestrator":
print(f"\n[Magentic Orchestrator Event] Type: {event.data.event_type.name}")
if isinstance(event.data.content, ChatMessage):
print(f"Please review the plan:\n{event.data.content.text}")
elif isinstance(event.data.content, MagenticProgressLedger):
print(f"Please review progress ledger:\n{json.dumps(event.data.content.to_dict(), indent=2)}")
else:
print(f"Unknown data type in MagenticOrchestratorEvent: {type(event.data)}")
print(f"Unknown data type in MagenticOrchestratorEvent: {type(event.data.content)}")
# Block to allow user to read the plan/progress before continuing
# Note: this is for demonstration only and is not the recommended way to handle human interaction.
# Please refer to `with_plan_review` for proper human interaction during planning phases.
await asyncio.get_event_loop().run_in_executor(None, input, "Press Enter to continue...")
elif isinstance(event, GroupChatRequestSentEvent):
print(f"\n[REQUEST SENT ({event.round_index})] to agent: {event.participant_name}")
elif event.type == "group_chat" and isinstance(event.data, GroupChatRequestSentEvent):
print(f"\n[REQUEST SENT ({event.data.round_index})] to agent: {event.data.participant_name}")
elif isinstance(event, WorkflowOutputEvent):
data = event.data
if isinstance(data, AgentResponseUpdate):
response_id = data.response_id
if response_id != last_response_id:
if last_response_id is not None:
print("\n")
print(f"- {event.executor_id}:", end=" ", flush=True)
last_response_id = response_id
print(event.data, end="", flush=True)
else:
# The output of the magentic workflow is a collection of chat messages from all participants
outputs = cast(list[ChatMessage], event.data)
print("\n" + "=" * 80)
print("\nFinal Conversation Transcript:\n")
for message in outputs:
print(f"{message.author_name or message.role}: {message.text}\n")
elif event.type == "output":
output_event = event
if output_event:
# The output of the magentic workflow is a collection of chat messages from all participants
outputs = cast(list[ChatMessage], output_event.data)
print("\n" + "=" * 80)
print("\nFinal Conversation Transcript:\n")
for message in outputs:
print(f"{message.author_name or message.role}: {message.text}\n")
if __name__ == "__main__":