Skip to content

Python: Fix group chat docstring examples #9752

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
Naveen Chatlapalli (1aifanatic) wants to merge 2 commits into
base: main
Choose a base branch
from
Draft

Python: Fix group chat docstring examples #9752

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
e72f5df
Python: fix group chat docstring examples
1aifanatic Oct 27, 2026
7b21052
Show the public GroupChatBuilder route in the orchestrator example
1aifanatic Oct 27, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
25 changes: 15 additions & 10 deletions python/packages/orchestrations/agent_framework_orchestrations/_group_chat.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -147,21 +147,26 @@ def __init__(
Example:
.. code-block:: python

from agent_framework_orchestrations import GroupChatOrchestrator
from agent_framework import Agent
from agent_framework_orchestrations import GroupChatBuilder, GroupChatState


async def round_robin_selector(state: GroupChatState) -> str:
def round_robin_selector(state: GroupChatState) -> str:
# Simple round-robin selection among participants
return state.participants[state.current_round % len(state.participants)]
names = list(state.participants)
return names[state.current_round % len(names)]


orchestrator = GroupChatOrchestrator(
id="group_chat_orchestrator_1",
# GroupChatBuilder creates a GroupChatOrchestrator when given a selection_func.
workflow = GroupChatBuilder(
participants=[
Agent(client=client, name="researcher"),
Agent(client=client, name="writer"),
],
selection_func=round_robin_selector,
participants=["researcher", "writer"],
name="Coordinator",
orchestrator_name="Coordinator",
max_rounds=10,
)
).build()
"""
super().__init__(
id,
Expand Down Expand Up @@ -895,10 +900,10 @@ def with_checkpointing(self, checkpoint_storage: CheckpointStorage) -> GroupChat

.. code-block:: python

from agent_framework import MemoryCheckpointStorage
from agent_framework import InMemoryCheckpointStorage
from agent_framework_orchestrations import GroupChatBuilder

storage = MemoryCheckpointStorage()
storage = InMemoryCheckpointStorage()
workflow = (
GroupChatBuilder(
participants=[agent1, agent2],
Expand Down
Loading