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Team termination condition sets in the constructor (#4042) 

* Termination condition as part of constructor

* Update doc

* Update notebooks
This commit is contained in:
Eric Zhu 2024-11-01 15:49:37 -07:00 committed by GitHub
parent 7d1857dae6
commit 4fec22ddc5
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13 changed files with 134 additions and 97 deletions
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2
python/packages/autogen-agentchat/src/autogen_agentchat/base/_task.py
View File

@ -33,5 +33,5 @@ class TaskRunner(Protocol):
cancellation_token: CancellationToken | None = None,
) -> AsyncGenerator[InnerMessage | ChatMessage | TaskResult, None]:
"""Run the task and produces a stream of messages and the final result
as the last item in the stream."""
:class:`TaskResult` as the last item in the stream."""
...

11
python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_base_group_chat.py
View File

@ -33,6 +33,7 @@ class BaseGroupChat(Team, ABC):
self,
participants: List[ChatAgent],
group_chat_manager_class: type[BaseGroupChatManager],
termination_condition: TerminationCondition | None = None,
):
if len(participants) == 0:
raise ValueError("At least one participant is required.")
@ -41,6 +42,7 @@ class BaseGroupChat(Team, ABC):
self._participants = participants
self._team_id = str(uuid.uuid4())
self._base_group_chat_manager_class = group_chat_manager_class
self._termination_condition = termination_condition
@abstractmethod
def _create_group_chat_manager_factory(
@ -72,12 +74,12 @@ class BaseGroupChat(Team, ABC):
task: str,
*,
cancellation_token: CancellationToken | None = None,
termination_condition: TerminationCondition | None = None,
) -> TaskResult:
"""Run the team and return the result. The base implementation uses
:meth:`run_stream` to run the team and then returns the final result."""
async for message in self.run_stream(
task, cancellation_token=cancellation_token, termination_condition=termination_condition
task,
cancellation_token=cancellation_token,
):
if isinstance(message, TaskResult):
return message
@ -88,10 +90,9 @@ class BaseGroupChat(Team, ABC):
task: str,
*,
cancellation_token: CancellationToken | None = None,
termination_condition: TerminationCondition | None = None,
) -> AsyncGenerator[InnerMessage | ChatMessage | TaskResult, None]:
"""Run the team and produces a stream of messages and the final result
as the last item in the stream."""
of the type :class:`TaskResult` as the last item in the stream."""
# Create the runtime.
runtime = SingleThreadedAgentRuntime()
@ -131,7 +132,7 @@ class BaseGroupChat(Team, ABC):
group_topic_type=group_topic_type,
participant_topic_types=participant_topic_types,
participant_descriptions=participant_descriptions,
termination_condition=termination_condition,
termination_condition=self._termination_condition,
),
)
# Add subscriptions for the group chat manager.

22
python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_round_robin_group_chat.py
View File

@ -50,7 +50,8 @@ class RoundRobinGroupChat(BaseGroupChat):
Args:
participants (List[BaseChatAgent]): The participants in the group chat.
tools (List[Tool], optional): The tools to use in the group chat. Defaults to None.
termination_condition (TerminationCondition, optional): The termination condition for the group chat. Defaults to None.
Without a termination condition, the group chat will run indefinitely.
Raises:
ValueError: If no participants are provided or if participant names are not unique.
@ -65,7 +66,7 @@ class RoundRobinGroupChat(BaseGroupChat):
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.task import StopMessageTermination
from autogen_agentchat.task import TextMentionTermination
async def main() -> None:
@ -79,8 +80,9 @@ class RoundRobinGroupChat(BaseGroupChat):
model_client=model_client,
tools=[get_weather],
)
team = RoundRobinGroupChat([assistant])
stream = team.run_stream("What's the weather in New York?", termination_condition=StopMessageTermination())
termination = TextMentionTermination("TERMINATE")
team = RoundRobinGroupChat([assistant], termination_condition=termination)
stream = team.run_stream("What's the weather in New York?")
async for message in stream:
print(message)
@ -95,7 +97,7 @@ class RoundRobinGroupChat(BaseGroupChat):
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.task import StopMessageTermination
from autogen_agentchat.task import TextMentionTermination
async def main() -> None:
@ -103,8 +105,9 @@ class RoundRobinGroupChat(BaseGroupChat):
agent1 = AssistantAgent("Assistant1", model_client=model_client)
agent2 = AssistantAgent("Assistant2", model_client=model_client)
team = RoundRobinGroupChat([agent1, agent2])
stream = team.run_stream("Tell me some jokes.", termination_condition=StopMessageTermination())
termination = TextMentionTermination("TERMINATE")
team = RoundRobinGroupChat([agent1, agent2], termination_condition=termination)
stream = team.run_stream("Tell me some jokes.")
async for message in stream:
print(message)
@ -112,10 +115,13 @@ class RoundRobinGroupChat(BaseGroupChat):
asyncio.run(main())
"""
def __init__(self, participants: List[ChatAgent]):
def __init__(
self, participants: List[ChatAgent], termination_condition: TerminationCondition | None = None
) -> None:
super().__init__(
participants,
group_chat_manager_class=RoundRobinGroupChatManager,
termination_condition=termination_condition,
)
def _create_group_chat_manager_factory(

34
python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_selector_group_chat.py
View File

@ -169,6 +169,8 @@ class SelectorGroupChat(BaseGroupChat):
must have unique names and at least two participants.
model_client (ChatCompletionClient): The ChatCompletion model client used
to select the next speaker.
termination_condition (TerminationCondition, optional): The termination condition for the group chat. Defaults to None.
Without a termination condition, the group chat will run indefinitely.
selector_prompt (str, optional): The prompt template to use for selecting the next speaker.
Must contain '{roles}', '{participants}', and '{history}' to be filled in.
allow_repeated_speaker (bool, optional): Whether to allow the same speaker to be selected
@ -187,10 +189,11 @@ class SelectorGroupChat(BaseGroupChat):
.. code-block:: python
import asyncio
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import SelectorGroupChat
from autogen_agentchat.task import StopMessageTermination
from autogen_agentchat.task import TextMentionTermination
async def main() -> None:
@ -223,20 +226,24 @@ class SelectorGroupChat(BaseGroupChat):
tools=[lookup_flight],
description="Helps with flight booking.",
)
team = SelectorGroupChat([travel_advisor, hotel_agent, flight_agent], model_client=model_client)
stream = team.run_stream("Book a 3-day trip to new york.", termination_condition=StopMessageTermination())
termination = TextMentionTermination("TERMINATE")
team = SelectorGroupChat(
[travel_advisor, hotel_agent, flight_agent],
model_client=model_client,
termination_condition=termination,
)
stream = team.run_stream("Book a 3-day trip to new york.")
async for message in stream:
print(message)
import asyncio
asyncio.run(main())
A team with a custom selector function:
.. code-block:: python
import asyncio
from autogen_ext.models import OpenAIChatCompletionClient
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.teams import SelectorGroupChat
@ -273,15 +280,19 @@ class SelectorGroupChat(BaseGroupChat):
return "Agent2"
return None
team = SelectorGroupChat([agent1, agent2], model_client=model_client, selector_func=selector_func)
termination = TextMentionTermination("Correct!")
team = SelectorGroupChat(
[agent1, agent2],
model_client=model_client,
selector_func=selector_func,
termination_condition=termination,
)
stream = team.run_stream("What is 1 + 1?", termination_condition=TextMentionTermination("Correct!"))
stream = team.run_stream("What is 1 + 1?")
async for message in stream:
print(message)
import asyncio
asyncio.run(main())
"""
@ -290,6 +301,7 @@ class SelectorGroupChat(BaseGroupChat):
participants: List[ChatAgent],
model_client: ChatCompletionClient,
*,
termination_condition: TerminationCondition | None = None,
selector_prompt: str = """You are in a role play game. The following roles are available:
{roles}.
Read the following conversation. Then select the next role from {participants} to play. Only return the role.
@ -301,7 +313,9 @@ Read the above conversation. Then select the next role from {participants} to pl
allow_repeated_speaker: bool = False,
selector_func: Callable[[Sequence[ChatMessage]], str | None] | None = None,
):
super().__init__(participants, group_chat_manager_class=SelectorGroupChatManager)
super().__init__(
participants, group_chat_manager_class=SelectorGroupChatManager, termination_condition=termination_condition
)
# Validate the participants.
if len(participants) < 2:
raise ValueError("At least two participants are required for SelectorGroupChat.")

15
python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_swarm_group_chat.py
View File

@ -56,6 +56,8 @@ class Swarm(BaseGroupChat):
Args:
participants (List[ChatAgent]): The agents participating in the group chat. The first agent in the list is the initial speaker.
termination_condition (TerminationCondition, optional): The termination condition for the group chat. Defaults to None.
Without a termination condition, the group chat will run indefinitely.
Examples:
@ -81,9 +83,10 @@ class Swarm(BaseGroupChat):
"Bob", model_client=model_client, system_message="You are Bob and your birthday is on 1st January."
)
team = Swarm([agent1, agent2])
termination = MaxMessageTermination(3)
team = Swarm([agent1, agent2], termination_condition=termination)
stream = team.run_stream("What is bob's birthday?", termination_condition=MaxMessageTermination(3))
stream = team.run_stream("What is bob's birthday?")
async for message in stream:
print(message)
@ -91,8 +94,12 @@ class Swarm(BaseGroupChat):
asyncio.run(main())
"""
def __init__(self, participants: List[ChatAgent]):
super().__init__(participants, group_chat_manager_class=SwarmGroupChatManager)
def __init__(
self, participants: List[ChatAgent], termination_condition: TerminationCondition | None = None
) -> None:
super().__init__(
participants, group_chat_manager_class=SwarmGroupChatManager, termination_condition=termination_condition
)
# The first participant must be able to produce handoff messages.
first_participant = self._participants[0]
if HandoffMessage not in first_participant.produced_message_types:

61
python/packages/autogen-agentchat/tests/test_group_chat.py
View File

@ -148,10 +148,12 @@ async def test_round_robin_group_chat(monkeypatch: pytest.MonkeyPatch) -> None:
coding_assistant_agent = AssistantAgent(
"coding_assistant", model_client=OpenAIChatCompletionClient(model=model, api_key="")
)
team = RoundRobinGroupChat(participants=[coding_assistant_agent, code_executor_agent])
termination = TextMentionTermination("TERMINATE")
team = RoundRobinGroupChat(
participants=[coding_assistant_agent, code_executor_agent], termination_condition=termination
)
result = await team.run(
"Write a program that prints 'Hello, world!'",
termination_condition=TextMentionTermination("TERMINATE"),
)
expected_messages = [
"Write a program that prints 'Hello, world!'",
@ -171,8 +173,9 @@ async def test_round_robin_group_chat(monkeypatch: pytest.MonkeyPatch) -> None:
# Test streaming.
mock.reset()
index = 0
await termination.reset()
async for message in team.run_stream(
"Write a program that prints 'Hello, world!'", termination_condition=TextMentionTermination("TERMINATE")
"Write a program that prints 'Hello, world!'",
):
if isinstance(message, TaskResult):
assert message == result
@ -244,10 +247,10 @@ async def test_round_robin_group_chat_with_tools(monkeypatch: pytest.MonkeyPatch
tools=[tool],
)
echo_agent = _EchoAgent("echo_agent", description="echo agent")
team = RoundRobinGroupChat(participants=[tool_use_agent, echo_agent])
termination = TextMentionTermination("TERMINATE")
team = RoundRobinGroupChat(participants=[tool_use_agent, echo_agent], termination_condition=termination)
result = await team.run(
"Write a program that prints 'Hello, world!'",
termination_condition=TextMentionTermination("TERMINATE"),
)
assert len(result.messages) == 6
@ -274,8 +277,9 @@ async def test_round_robin_group_chat_with_tools(monkeypatch: pytest.MonkeyPatch
tool_use_agent._model_context.clear() # pyright: ignore
mock.reset()
index = 0
await termination.reset()
async for message in team.run_stream(
"Write a program that prints 'Hello, world!'", termination_condition=TextMentionTermination("TERMINATE")
"Write a program that prints 'Hello, world!'",
):
if isinstance(message, TaskResult):
assert message == result
@ -345,13 +349,14 @@ async def test_selector_group_chat(monkeypatch: pytest.MonkeyPatch) -> None:
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=2)
agent2 = _EchoAgent("agent2", description="echo agent 2")
agent3 = _EchoAgent("agent3", description="echo agent 3")
termination = TextMentionTermination("TERMINATE")
team = SelectorGroupChat(
participants=[agent1, agent2, agent3],
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
termination_condition=termination,
)
result = await team.run(
"Write a program that prints 'Hello, world!'",
termination_condition=TextMentionTermination("TERMINATE"),
)
assert len(result.messages) == 6
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
@ -365,8 +370,9 @@ async def test_selector_group_chat(monkeypatch: pytest.MonkeyPatch) -> None:
mock.reset()
agent1._count = 0 # pyright: ignore
index = 0
await termination.reset()
async for message in team.run_stream(
"Write a program that prints 'Hello, world!'", termination_condition=TextMentionTermination("TERMINATE")
"Write a program that prints 'Hello, world!'",
):
if isinstance(message, TaskResult):
assert message == result
@ -395,13 +401,14 @@ async def test_selector_group_chat_two_speakers(monkeypatch: pytest.MonkeyPatch)
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=2)
agent2 = _EchoAgent("agent2", description="echo agent 2")
termination = TextMentionTermination("TERMINATE")
team = SelectorGroupChat(
participants=[agent1, agent2],
termination_condition=termination,
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
)
result = await team.run(
"Write a program that prints 'Hello, world!'",
termination_condition=TextMentionTermination("TERMINATE"),
)
assert len(result.messages) == 5
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
@ -416,9 +423,8 @@ async def test_selector_group_chat_two_speakers(monkeypatch: pytest.MonkeyPatch)
mock.reset()
agent1._count = 0 # pyright: ignore
index = 0
async for message in team.run_stream(
"Write a program that prints 'Hello, world!'", termination_condition=TextMentionTermination("TERMINATE")
):
await termination.reset()
async for message in team.run_stream("Write a program that prints 'Hello, world!'"):
if isinstance(message, TaskResult):
assert message == result
else:
@ -466,14 +472,14 @@ async def test_selector_group_chat_two_speakers_allow_repeated(monkeypatch: pyte
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
agent2 = _EchoAgent("agent2", description="echo agent 2")
termination = TextMentionTermination("TERMINATE")
team = SelectorGroupChat(
participants=[agent1, agent2],
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
termination_condition=termination,
allow_repeated_speaker=True,
)
result = await team.run(
"Write a program that prints 'Hello, world!'", termination_condition=TextMentionTermination("TERMINATE")
)
result = await team.run("Write a program that prints 'Hello, world!'")
assert len(result.messages) == 4
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
assert result.messages[1].source == "agent2"
@ -483,9 +489,8 @@ async def test_selector_group_chat_two_speakers_allow_repeated(monkeypatch: pyte
# Test streaming.
mock.reset()
index = 0
async for message in team.run_stream(
"Write a program that prints 'Hello, world!'", termination_condition=TextMentionTermination("TERMINATE")
):
await termination.reset()
async for message in team.run_stream("Write a program that prints 'Hello, world!'"):
if isinstance(message, TaskResult):
assert message == result
else:
@ -527,12 +532,14 @@ async def test_selector_group_chat_custom_selector(monkeypatch: pytest.MonkeyPat
else:
return "agent1"
termination = MaxMessageTermination(6)
team = SelectorGroupChat(
participants=[agent1, agent2, agent3, agent4],
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
selector_func=_select_agent,
termination_condition=termination,
)
result = await team.run("task", termination_condition=MaxMessageTermination(6))
result = await team.run("task")
assert len(result.messages) == 6
assert result.messages[1].source == "agent1"
assert result.messages[2].source == "agent2"
@ -564,8 +571,9 @@ async def test_swarm_handoff() -> None:
second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
team = Swarm([second_agent, first_agent, third_agent])
result = await team.run("task", termination_condition=MaxMessageTermination(6))
termination = MaxMessageTermination(6)
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination)
result = await team.run("task")
assert len(result.messages) == 6
assert result.messages[0].content == "task"
assert result.messages[1].content == "Transferred to third_agent."
@ -576,7 +584,8 @@ async def test_swarm_handoff() -> None:
# Test streaming.
index = 0
stream = team.run_stream("task", termination_condition=MaxMessageTermination(6))
await termination.reset()
stream = team.run_stream("task")
async for message in stream:
if isinstance(message, TaskResult):
assert message == result
@ -648,8 +657,9 @@ async def test_swarm_handoff_using_tool_calls(monkeypatch: pytest.MonkeyPatch) -
handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
)
agent2 = _HandOffAgent("agent2", description="agent 2", next_agent="agent1")
team = Swarm([agent1, agent2])
result = await team.run("task", termination_condition=TextMentionTermination("TERMINATE"))
termination = TextMentionTermination("TERMINATE")
team = Swarm([agent1, agent2], termination_condition=termination)
result = await team.run("task")
assert len(result.messages) == 7
assert result.messages[0].content == "task"
assert isinstance(result.messages[1], ToolCallMessage)
@ -663,7 +673,8 @@ async def test_swarm_handoff_using_tool_calls(monkeypatch: pytest.MonkeyPatch) -
agent1._model_context.clear() # pyright: ignore
mock.reset()
index = 0
stream = team.run_stream("task", termination_condition=TextMentionTermination("TERMINATE"))
await termination.reset()
stream = team.run_stream("task")
async for message in stream:
if isinstance(message, TaskResult):
assert message == result

9
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/examples/company-research.ipynb
View File

@ -260,7 +260,8 @@
" system_message=\"You are a helpful assistant that can generate a comprehensive report on a given topic based on search and stock analysis. When you done with generating the report, reply with TERMINATE.\",\n",
")\n",
"\n",
"team = RoundRobinGroupChat([search_agent, stock_analysis_agent, report_agent])"
"termination = TextMentionTermination(\"TERMINATE\")\n",
"team = RoundRobinGroupChat([search_agent, stock_analysis_agent, report_agent], termination_condition=termination)"
]
},
{
@ -400,9 +401,7 @@
}
],
"source": [
"result = await team.run(\n",
" \"Write a financial report on American airlines\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
")\n",
"result = await team.run(\"Write a financial report on American airlines\")\n",
"print(result)"
]
}
@ -423,7 +422,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.6"
"version": "3.11.5"
}
},
"nbformat": 4,

8
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/examples/literature-review.ipynb
View File

@ -328,11 +328,13 @@
" system_message=\"You are a helpful assistant. Your task is to synthesize data extracted into a high quality literature review including CORRECT references. You MUST write a final report that is formatted as a literature review with CORRECT references. Your response should end with the word 'TERMINATE'\",\n",
")\n",
"\n",
"team = RoundRobinGroupChat(participants=[google_search_agent, arxiv_search_agent, report_agent])\n",
"termination = TextMentionTermination(\"TERMINATE\")\n",
"team = RoundRobinGroupChat(\n",
" participants=[google_search_agent, arxiv_search_agent, report_agent], termination_condition=termination\n",
")\n",
"\n",
"result = await team.run(\n",
" task=\"Write a literature review on no code tools for building multi agent ai systems\",\n",
" termination_condition=TextMentionTermination(\"TERMINATE\"),\n",
")"
]
}
@ -353,7 +355,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.6"
"version": "3.11.5"
}
},
"nbformat": 4,

7
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/examples/travel-planning.ipynb
View File

@ -194,10 +194,11 @@
}
],
"source": [
"group_chat = RoundRobinGroupChat([planner_agent, local_agent, language_agent, travel_summary_agent])\n",
"result = await group_chat.run(\n",
" task=\"Plan a 3 day trip to Nepal.\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
"termination = TextMentionTermination(\"TERMINATE\")\n",
"group_chat = RoundRobinGroupChat(\n",
" [planner_agent, local_agent, language_agent, travel_summary_agent], termination_condition=termination\n",
")\n",
"result = await group_chat.run(task=\"Plan a 3 day trip to Nepal.\")\n",
"print(result)"
]
}

12
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/quickstart.ipynb
View File

@ -81,12 +81,10 @@
")\n",
"\n",
"# add the agent to a team\n",
"agent_team = RoundRobinGroupChat([weather_agent])\n",
"termination = MaxMessageTermination(max_messages=2)\n",
"agent_team = RoundRobinGroupChat([weather_agent], termination_condition=termination)\n",
"# Note: if running in a Python file directly you'll need to use asyncio.run(agent_team.run(...)) instead of await agent_team.run(...)\n",
"result = await agent_team.run(\n",
" task=\"What is the weather in New York?\",\n",
" termination_condition=MaxMessageTermination(max_messages=2),\n",
")\n",
"result = await agent_team.run(task=\"What is the weather in New York?\")\n",
"print(\"\\n\", result)"
]
},
@ -110,7 +108,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "agnext",
"display_name": ".venv",
"language": "python",
"name": "python3"
},
@ -124,7 +122,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
"version": "3.11.5"
}
},
"nbformat": 4,

10
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/selector-group-chat.ipynb
View File

@ -251,10 +251,14 @@
" model_client=OpenAIChatCompletionClient(model=\"gpt-4o-mini\"),\n",
" system_message=\"You are a travel assistant.\",\n",
")\n",
"\n",
"termination = TextMentionTermination(\"TERMINATE\")\n",
"team = SelectorGroupChat(\n",
" [user_proxy, flight_broker, travel_assistant], model_client=OpenAIChatCompletionClient(model=\"gpt-4o-mini\")\n",
" [user_proxy, flight_broker, travel_assistant],\n",
" model_client=OpenAIChatCompletionClient(model=\"gpt-4o-mini\"),\n",
" termination_condition=termination,\n",
")\n",
"await team.run(\"Help user plan a trip and book a flight.\", termination_condition=TextMentionTermination(\"TERMINATE\"))"
"await team.run(\"Help user plan a trip and book a flight.\")"
]
}
],
@ -274,7 +278,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.6"
"version": "3.11.5"
}
},
"nbformat": 4,

19
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/teams.ipynb
View File

@ -103,10 +103,9 @@
}
],
"source": [
"round_robin_team = RoundRobinGroupChat([tool_use_agent, writing_assistant_agent])\n",
"round_robin_team_result = await round_robin_team.run(\n",
" \"Write a Haiku about the weather in Paris\", termination_condition=MaxMessageTermination(max_messages=1)\n",
")"
"termination = MaxMessageTermination(max_messages=1)\n",
"round_robin_team = RoundRobinGroupChat([tool_use_agent, writing_assistant_agent], termination_condition=termination)\n",
"round_robin_team_result = await round_robin_team.run(\"Write a Haiku about the weather in Paris\")"
]
},
{
@ -173,12 +172,12 @@
}
],
"source": [
"llm_team = SelectorGroupChat([tool_use_agent, writing_assistant_agent], model_client=model_client)\n",
"termination = MaxMessageTermination(max_messages=2)\n",
"llm_team = SelectorGroupChat(\n",
" [tool_use_agent, writing_assistant_agent], model_client=model_client, termination_condition=termination\n",
")\n",
"\n",
"llm_team_result = await llm_team.run(\n",
" \"What is the weather in paris right now? Also write a haiku about it.\",\n",
" termination_condition=MaxMessageTermination(max_messages=2),\n",
")"
"llm_team_result = await llm_team.run(\"What is the weather in paris right now? Also write a haiku about it.\")"
]
},
{
@ -209,7 +208,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.6"
"version": "3.11.5"
}
},
"nbformat": 4,

21
python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
View File

@ -56,9 +56,7 @@
" name=\"writing_assistant_agent\",\n",
" system_message=\"You are a helpful assistant that solve tasks by generating text responses and code.\",\n",
" model_client=model_client,\n",
")\n",
"\n",
"round_robin_team = RoundRobinGroupChat([writing_assistant_agent])"
")"
]
},
{
@ -110,10 +108,9 @@
}
],
"source": [
"round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
"round_robin_team_result = await round_robin_team.run(\n",
" \"Write a unique, Haiku about the weather in Paris\", termination_condition=MaxMessageTermination(max_messages=3)\n",
")"
"max_msg_termination = MaxMessageTermination(max_messages=3)\n",
"round_robin_team = RoundRobinGroupChat([writing_assistant_agent], termination_condition=max_msg_termination)\n",
"round_robin_team_result = await round_robin_team.run(\"Write a unique, Haiku about the weather in Paris\")"
]
},
{
@ -174,12 +171,10 @@
" model_client=model_client,\n",
")\n",
"\n",
"text_termination = TextMentionTermination(\"TERMINATE\")\n",
"round_robin_team = RoundRobinGroupChat([writing_assistant_agent], termination_condition=text_termination)\n",
"\n",
"round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
"\n",
"round_robin_team_result = await round_robin_team.run(\n",
" \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
")"
"round_robin_team_result = await round_robin_team.run(\"Write a unique, Haiku about the weather in Paris\")"
]
}
],
@ -199,7 +194,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.6"
"version": "3.11.5"
}
},
"nbformat": 4,