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import asyncio
import json
import logging
import tempfile
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
from typing import AsyncGenerator, List, Sequence
import pytest
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
import pytest_asyncio
from autogen_agentchat import EVENT_LOGGER_NAME
from autogen_agentchat.agents import (
AssistantAgent,
BaseChatAgent,
CodeExecutorAgent,
)
from autogen_agentchat.base import Handoff, Response, TaskResult
from autogen_agentchat.conditions import HandoffTermination, MaxMessageTermination, TextMentionTermination
from autogen_agentchat.messages import (
AgentEvent,
ChatMessage,
HandoffMessage,
MultiModalMessage,
StopMessage,
TextMessage,
ToolCallExecutionEvent,
ToolCallRequestEvent,
ToolCallSummaryMessage,
)
from autogen_agentchat.teams import MagenticOneGroupChat, RoundRobinGroupChat, SelectorGroupChat, Swarm
from autogen_agentchat.teams._group_chat._round_robin_group_chat import RoundRobinGroupChatManager
from autogen_agentchat.teams._group_chat._selector_group_chat import SelectorGroupChatManager
from autogen_agentchat.teams._group_chat._swarm_group_chat import SwarmGroupChatManager
from autogen_agentchat.ui import Console
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
from autogen_core import AgentId, AgentRuntime, CancellationToken, FunctionCall, SingleThreadedAgentRuntime
from autogen_core.models import (
AssistantMessage,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
CreateResult,
FunctionExecutionResult,
FunctionExecutionResultMessage,
LLMMessage,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
RequestUsage,
UserMessage,
)
2024-12-09 21:39:07 -05:00
from autogen_core.tools import FunctionTool
from autogen_ext.code_executors.local import LocalCommandLineCodeExecutor
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.models.replay import ReplayChatCompletionClient
from utils import FileLogHandler
logger = logging.getLogger(EVENT_LOGGER_NAME)
logger.setLevel(logging.DEBUG)
logger.addHandler(FileLogHandler("test_group_chat.log"))
class _EchoAgent(BaseChatAgent):
def __init__(self, name: str, description: str) -> None:
super().__init__(name, description)
self._last_message: str | None = None
self._total_messages = 0
@property
def produced_message_types(self) -> Sequence[type[ChatMessage]]:
return (TextMessage,)
@property
def total_messages(self) -> int:
return self._total_messages
async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
if len(messages) > 0:
assert isinstance(messages[0], TextMessage)
self._last_message = messages[0].content
self._total_messages += 1
return Response(chat_message=TextMessage(content=messages[0].content, source=self.name))
else:
assert self._last_message is not None
self._total_messages += 1
return Response(chat_message=TextMessage(content=self._last_message, source=self.name))
2024-11-10 18:28:20 -08:00
async def on_reset(self, cancellation_token: CancellationToken) -> None:
self._last_message = None
class _FlakyAgent(BaseChatAgent):
def __init__(self, name: str, description: str) -> None:
super().__init__(name, description)
self._last_message: str | None = None
self._total_messages = 0
@property
def produced_message_types(self) -> Sequence[type[ChatMessage]]:
return (TextMessage,)
@property
def total_messages(self) -> int:
return self._total_messages
async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
raise ValueError("I am a flaky agent...")
async def on_reset(self, cancellation_token: CancellationToken) -> None:
self._last_message = None
class _StopAgent(_EchoAgent):
def __init__(self, name: str, description: str, *, stop_at: int = 1) -> None:
super().__init__(name, description)
self._count = 0
self._stop_at = stop_at
@property
def produced_message_types(self) -> Sequence[type[ChatMessage]]:
return (TextMessage, StopMessage)
async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
self._count += 1
if self._count < self._stop_at:
return await super().on_messages(messages, cancellation_token)
return Response(chat_message=StopMessage(content="TERMINATE", source=self.name))
def _pass_function(input: str) -> str:
return "pass"
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
@pytest_asyncio.fixture(params=["single_threaded", "embedded"]) # type: ignore
async def runtime(request: pytest.FixtureRequest) -> AsyncGenerator[AgentRuntime | None, None]:
if request.param == "single_threaded":
runtime = SingleThreadedAgentRuntime()
runtime.start()
yield runtime
await runtime.stop()
elif request.param == "embedded":
yield None
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
[
'Here is the program\n ```python\nprint("Hello, world!")\n```',
"TERMINATE",
],
)
with tempfile.TemporaryDirectory() as temp_dir:
code_executor_agent = CodeExecutorAgent(
"code_executor", code_executor=LocalCommandLineCodeExecutor(work_dir=temp_dir)
)
coding_assistant_agent = AssistantAgent(
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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"coding_assistant",
model_client=model_client,
)
termination = TextMentionTermination("TERMINATE")
team = RoundRobinGroupChat(
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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participants=[coding_assistant_agent, code_executor_agent],
termination_condition=termination,
runtime=runtime,
)
result = await team.run(
task="Write a program that prints 'Hello, world!'",
)
expected_messages = [
"Write a program that prints 'Hello, world!'",
'Here is the program\n ```python\nprint("Hello, world!")\n```',
"Hello, world!",
"TERMINATE",
]
# Normalize the messages to remove \r\n and any leading/trailing whitespace.
normalized_messages = [
msg.content.replace("\r\n", "\n").rstrip("\n") if isinstance(msg.content, str) else msg.content
for msg in result.messages
]
# Assert that all expected messages are in the collected messages
assert normalized_messages == expected_messages
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
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# Test streaming.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client.reset()
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index = 0
await team.reset()
2024-11-01 04:12:43 -07:00
async for message in team.run_stream(
task="Write a program that prints 'Hello, world!'",
2024-11-01 04:12:43 -07:00
):
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test message input.
# Text message.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client.reset()
index = 0
await team.reset()
result_2 = await team.run(
task=TextMessage(content="Write a program that prints 'Hello, world!'", source="user")
)
assert result == result_2
# Test multi-modal message.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client.reset()
index = 0
await team.reset()
result_2 = await team.run(
task=MultiModalMessage(content=["Write a program that prints 'Hello, world!'"], source="user")
)
assert result.messages[0].content == result_2.messages[0].content[0]
assert result.messages[1:] == result_2.messages[1:]
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat_state(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
["No facts", "No plan", "print('Hello, world!')", "TERMINATE"],
)
agent1 = AssistantAgent("agent1", model_client=model_client)
agent2 = AssistantAgent("agent2", model_client=model_client)
termination = TextMentionTermination("TERMINATE")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team1 = RoundRobinGroupChat(participants=[agent1, agent2], termination_condition=termination, runtime=runtime)
await team1.run(task="Write a program that prints 'Hello, world!'")
state = await team1.save_state()
agent3 = AssistantAgent("agent1", model_client=model_client)
agent4 = AssistantAgent("agent2", model_client=model_client)
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team2 = RoundRobinGroupChat(participants=[agent3, agent4], termination_condition=termination, runtime=runtime)
await team2.load_state(state)
state2 = await team2.save_state()
assert state == state2
agent1_model_ctx_messages = await agent1._model_context.get_messages() # pyright: ignore
agent2_model_ctx_messages = await agent2._model_context.get_messages() # pyright: ignore
agent3_model_ctx_messages = await agent3._model_context.get_messages() # pyright: ignore
agent4_model_ctx_messages = await agent4._model_context.get_messages() # pyright: ignore
assert agent3_model_ctx_messages == agent1_model_ctx_messages
assert agent4_model_ctx_messages == agent2_model_ctx_messages
manager_1 = await team1._runtime.try_get_underlying_agent_instance( # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
AgentId(f"{team1._group_chat_manager_name}_{team1._team_id}", team1._team_id), # pyright: ignore
RoundRobinGroupChatManager, # pyright: ignore
) # pyright: ignore
manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
AgentId(f"{team2._group_chat_manager_name}_{team2._team_id}", team2._team_id), # pyright: ignore
RoundRobinGroupChatManager, # pyright: ignore
) # pyright: ignore
assert manager_1._current_turn == manager_2._current_turn # pyright: ignore
assert manager_1._message_thread == manager_2._message_thread # pyright: ignore
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat_with_tools(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
chat_completions=[
CreateResult(
finish_reason="function_calls",
content=[FunctionCall(id="1", name="pass", arguments=json.dumps({"input": "pass"}))],
usage=RequestUsage(prompt_tokens=0, completion_tokens=0),
cached=False,
),
"Hello",
"TERMINATE",
],
model_info={"family": "gpt-4o", "function_calling": True, "json_output": True, "vision": True},
)
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
tool = FunctionTool(_pass_function, name="pass", description="pass function")
tool_use_agent = AssistantAgent("tool_use_agent", model_client=model_client, tools=[tool])
echo_agent = _EchoAgent("echo_agent", description="echo agent")
termination = TextMentionTermination("TERMINATE")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = RoundRobinGroupChat(
participants=[tool_use_agent, echo_agent], termination_condition=termination, runtime=runtime
)
result = await team.run(
task="Write a program that prints 'Hello, world!'",
)
assert len(result.messages) == 8
assert isinstance(result.messages[0], TextMessage) # task
assert isinstance(result.messages[1], ToolCallRequestEvent) # tool call
assert isinstance(result.messages[2], ToolCallExecutionEvent) # tool call result
assert isinstance(result.messages[3], ToolCallSummaryMessage) # tool use agent response
assert result.messages[3].content == "pass" # ensure the tool call was executed
assert isinstance(result.messages[4], TextMessage) # echo agent response
assert isinstance(result.messages[5], TextMessage) # tool use agent response
assert isinstance(result.messages[6], TextMessage) # echo agent response
assert isinstance(result.messages[7], TextMessage) # tool use agent response, that has TERMINATE
assert result.messages[7].content == "TERMINATE"
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
2024-11-01 04:12:43 -07:00
# Test streaming.
await tool_use_agent._model_context.clear() # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client.reset()
2024-11-01 04:12:43 -07:00
index = 0
await team.reset()
2024-11-01 04:12:43 -07:00
async for message in team.run_stream(
task="Write a program that prints 'Hello, world!'",
2024-11-01 04:12:43 -07:00
):
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test Console.
await tool_use_agent._model_context.clear() # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client.reset()
index = 0
await team.reset()
result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
assert result2 == result
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat_with_resume_and_reset(runtime: AgentRuntime | None) -> None:
agent_1 = _EchoAgent("agent_1", description="echo agent 1")
agent_2 = _EchoAgent("agent_2", description="echo agent 2")
agent_3 = _EchoAgent("agent_3", description="echo agent 3")
agent_4 = _EchoAgent("agent_4", description="echo agent 4")
termination = MaxMessageTermination(3)
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = RoundRobinGroupChat(
participants=[agent_1, agent_2, agent_3, agent_4], termination_condition=termination, runtime=runtime
)
result = await team.run(
task="Write a program that prints 'Hello, world!'",
)
assert len(result.messages) == 3
assert result.messages[1].source == "agent_1"
assert result.messages[2].source == "agent_2"
assert result.stop_reason is not None
# Resume.
result = await team.run()
assert len(result.messages) == 3
assert result.messages[0].source == "agent_3"
assert result.messages[1].source == "agent_4"
assert result.messages[2].source == "agent_1"
assert result.stop_reason is not None
# Reset.
await team.reset()
result = await team.run(task="Write a program that prints 'Hello, world!'")
assert len(result.messages) == 3
assert result.messages[1].source == "agent_1"
assert result.messages[2].source == "agent_2"
assert result.stop_reason is not None
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
# TODO: add runtime fixture for testing with custom runtime once the issue regarding
# hanging on exception is resolved.
@pytest.mark.asyncio
async def test_round_robin_group_chat_with_exception_raised() -> None:
agent_1 = _EchoAgent("agent_1", description="echo agent 1")
agent_2 = _FlakyAgent("agent_2", description="echo agent 2")
agent_3 = _EchoAgent("agent_3", description="echo agent 3")
termination = MaxMessageTermination(3)
team = RoundRobinGroupChat(
participants=[agent_1, agent_2, agent_3],
termination_condition=termination,
)
with pytest.raises(ValueError, match="I am a flaky agent..."):
await team.run(
task="Write a program that prints 'Hello, world!'",
)
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat_max_turn(runtime: AgentRuntime | None) -> None:
agent_1 = _EchoAgent("agent_1", description="echo agent 1")
agent_2 = _EchoAgent("agent_2", description="echo agent 2")
agent_3 = _EchoAgent("agent_3", description="echo agent 3")
agent_4 = _EchoAgent("agent_4", description="echo agent 4")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], max_turns=3, runtime=runtime)
result = await team.run(
task="Write a program that prints 'Hello, world!'",
)
assert len(result.messages) == 4
assert result.messages[1].source == "agent_1"
assert result.messages[2].source == "agent_2"
assert result.messages[3].source == "agent_3"
assert result.stop_reason is not None
# Resume.
result = await team.run()
assert len(result.messages) == 3
assert result.messages[0].source == "agent_4"
assert result.messages[1].source == "agent_1"
assert result.messages[2].source == "agent_2"
assert result.stop_reason is not None
# Reset.
await team.reset()
result = await team.run(task="Write a program that prints 'Hello, world!'")
assert len(result.messages) == 4
assert result.messages[1].source == "agent_1"
assert result.messages[2].source == "agent_2"
assert result.messages[3].source == "agent_3"
assert result.stop_reason is not None
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat_cancellation(runtime: AgentRuntime | None) -> None:
agent_1 = _EchoAgent("agent_1", description="echo agent 1")
agent_2 = _EchoAgent("agent_2", description="echo agent 2")
agent_3 = _EchoAgent("agent_3", description="echo agent 3")
agent_4 = _EchoAgent("agent_4", description="echo agent 4")
# Set max_turns to a large number to avoid stopping due to max_turns before cancellation.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], max_turns=1000, runtime=runtime)
cancellation_token = CancellationToken()
run_task = asyncio.create_task(
team.run(
task="Write a program that prints 'Hello, world!'",
cancellation_token=cancellation_token,
)
)
await asyncio.sleep(0.1)
# Cancel the task.
cancellation_token.cancel()
with pytest.raises(asyncio.CancelledError):
await run_task
# Still can run again and finish the task.
result = await team.run()
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
assert result.stop_reason is not None and result.stop_reason == "Maximum number of turns 1000 reached."
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_selector_group_chat(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
chat_completions=[
"agent3",
"agent2",
"agent1",
"agent2",
"agent1",
]
)
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],
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client=model_client,
termination_condition=termination,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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runtime=runtime,
)
result = await team.run(
task="Write a program that prints 'Hello, world!'",
)
assert len(result.messages) == 6
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
assert result.messages[1].source == "agent3"
assert result.messages[2].source == "agent2"
assert result.messages[3].source == "agent1"
assert result.messages[4].source == "agent2"
assert result.messages[5].source == "agent1"
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
2024-11-01 04:12:43 -07:00
# Test streaming.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
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agent1._count = 0 # pyright: ignore
index = 0
await team.reset()
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async for message in team.run_stream(
task="Write a program that prints 'Hello, world!'",
2024-11-01 04:12:43 -07:00
):
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test Console.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
agent1._count = 0 # pyright: ignore
index = 0
await team.reset()
result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
assert result2 == result
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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async def test_selector_group_chat_state(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
["agent1", "No facts", "agent2", "No plan", "agent1", "print('Hello, world!')", "agent2", "TERMINATE"],
)
agent1 = AssistantAgent("agent1", model_client=model_client)
agent2 = AssistantAgent("agent2", model_client=model_client)
termination = TextMentionTermination("TERMINATE")
team1 = SelectorGroupChat(
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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participants=[agent1, agent2],
termination_condition=termination,
model_client=model_client,
runtime=runtime,
)
await team1.run(task="Write a program that prints 'Hello, world!'")
state = await team1.save_state()
agent3 = AssistantAgent("agent1", model_client=model_client)
agent4 = AssistantAgent("agent2", model_client=model_client)
team2 = SelectorGroupChat(
participants=[agent3, agent4], termination_condition=termination, model_client=model_client
)
await team2.load_state(state)
state2 = await team2.save_state()
assert state == state2
agent1_model_ctx_messages = await agent1._model_context.get_messages() # pyright: ignore
agent2_model_ctx_messages = await agent2._model_context.get_messages() # pyright: ignore
agent3_model_ctx_messages = await agent3._model_context.get_messages() # pyright: ignore
agent4_model_ctx_messages = await agent4._model_context.get_messages() # pyright: ignore
assert agent3_model_ctx_messages == agent1_model_ctx_messages
assert agent4_model_ctx_messages == agent2_model_ctx_messages
manager_1 = await team1._runtime.try_get_underlying_agent_instance( # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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AgentId(f"{team1._group_chat_manager_name}_{team1._team_id}", team1._team_id), # pyright: ignore
SelectorGroupChatManager, # pyright: ignore
) # pyright: ignore
manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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AgentId(f"{team2._group_chat_manager_name}_{team2._team_id}", team2._team_id), # pyright: ignore
SelectorGroupChatManager, # pyright: ignore
) # pyright: ignore
assert manager_1._message_thread == manager_2._message_thread # pyright: ignore
assert manager_1._previous_speaker == manager_2._previous_speaker # pyright: ignore
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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async def test_selector_group_chat_two_speakers(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(["agent2"])
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,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client=model_client,
runtime=runtime,
)
result = await team.run(
task="Write a program that prints 'Hello, world!'",
)
assert len(result.messages) == 5
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
assert result.messages[1].source == "agent2"
assert result.messages[2].source == "agent1"
assert result.messages[3].source == "agent2"
assert result.messages[4].source == "agent1"
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
2024-11-01 04:12:43 -07:00
# Test streaming.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
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agent1._count = 0 # pyright: ignore
index = 0
await team.reset()
async for message in team.run_stream(task="Write a program that prints 'Hello, world!'"):
2024-11-01 04:12:43 -07:00
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test Console.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
agent1._count = 0 # pyright: ignore
index = 0
await team.reset()
result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
assert result2 == result
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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async def test_selector_group_chat_two_speakers_allow_repeated(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
[
"agent2",
"agent2",
"agent1",
]
)
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],
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client=model_client,
termination_condition=termination,
allow_repeated_speaker=True,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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runtime=runtime,
)
result = await team.run(task="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"
assert result.messages[2].source == "agent2"
assert result.messages[3].source == "agent1"
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
2024-11-01 04:12:43 -07:00
# Test streaming.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
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index = 0
await team.reset()
async for message in team.run_stream(task="Write a program that prints 'Hello, world!'"):
2024-11-01 04:12:43 -07:00
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test Console.
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
index = 0
await team.reset()
result2 = await Console(team.run_stream(task="Write a program that prints 'Hello, world!'"))
assert result2 == result
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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async def test_selector_group_chat_succcess_after_2_attempts(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
["agent2, agent3", "agent2"],
)
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
agent2 = _EchoAgent("agent2", description="echo agent 2")
agent3 = _EchoAgent("agent3", description="echo agent 3")
team = SelectorGroupChat(
participants=[agent1, agent2, agent3],
model_client=model_client,
max_turns=1,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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runtime=runtime,
)
result = await team.run(task="Write a program that prints 'Hello, world!'")
assert len(result.messages) == 2
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
assert result.messages[1].source == "agent2"
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_selector_group_chat_fall_back_to_first_after_3_attempts(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
[
"agent2, agent3", # Multiple speakers
"agent5", # Non-existent speaker
"agent3, agent1", # Multiple speakers
]
)
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
agent2 = _EchoAgent("agent2", description="echo agent 2")
agent3 = _EchoAgent("agent3", description="echo agent 3")
team = SelectorGroupChat(
participants=[agent1, agent2, agent3],
model_client=model_client,
max_turns=1,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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runtime=runtime,
)
result = await team.run(task="Write a program that prints 'Hello, world!'")
assert len(result.messages) == 2
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
assert result.messages[1].source == "agent1"
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_selector_group_chat_fall_back_to_previous_after_3_attempts(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
["agent2", "agent2", "agent2", "agent2"],
)
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
agent2 = _EchoAgent("agent2", description="echo agent 2")
agent3 = _EchoAgent("agent3", description="echo agent 3")
team = SelectorGroupChat(
participants=[agent1, agent2, agent3],
model_client=model_client,
max_turns=2,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
runtime=runtime,
)
result = await team.run(task="Write a program that prints 'Hello, world!'")
assert len(result.messages) == 3
assert result.messages[0].content == "Write a program that prints 'Hello, world!'"
assert result.messages[1].source == "agent2"
assert result.messages[2].source == "agent2"
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_selector_group_chat_custom_selector(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(["agent3"])
agent1 = _EchoAgent("agent1", description="echo agent 1")
agent2 = _EchoAgent("agent2", description="echo agent 2")
agent3 = _EchoAgent("agent3", description="echo agent 3")
agent4 = _EchoAgent("agent4", description="echo agent 4")
def _select_agent(messages: Sequence[AgentEvent | ChatMessage]) -> str | None:
if len(messages) == 0:
return "agent1"
elif messages[-1].source == "agent1":
return "agent2"
elif messages[-1].source == "agent2":
return None
elif messages[-1].source == "agent3":
return "agent4"
else:
return "agent1"
termination = MaxMessageTermination(6)
team = SelectorGroupChat(
participants=[agent1, agent2, agent3, agent4],
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client=model_client,
selector_func=_select_agent,
termination_condition=termination,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
runtime=runtime,
)
result = await team.run(task="task")
assert len(result.messages) == 6
assert result.messages[1].source == "agent1"
assert result.messages[2].source == "agent2"
assert result.messages[3].source == "agent3"
assert result.messages[4].source == "agent4"
assert result.messages[5].source == "agent1"
assert (
result.stop_reason is not None
and result.stop_reason == "Maximum number of messages 6 reached, current message count: 6"
)
class _HandOffAgent(BaseChatAgent):
def __init__(self, name: str, description: str, next_agent: str) -> None:
super().__init__(name, description)
self._next_agent = next_agent
@property
def produced_message_types(self) -> Sequence[type[ChatMessage]]:
return (HandoffMessage,)
async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
return Response(
chat_message=HandoffMessage(
content=f"Transferred to {self._next_agent}.", target=self._next_agent, source=self.name
)
)
2024-11-10 18:28:20 -08:00
async def on_reset(self, cancellation_token: CancellationToken) -> None:
pass
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_swarm_handoff(runtime: AgentRuntime | None) -> None:
first_agent = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
termination = MaxMessageTermination(6)
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination, runtime=runtime)
result = await team.run(task="task")
assert len(result.messages) == 6
assert result.messages[0].content == "task"
assert result.messages[1].content == "Transferred to third_agent."
assert result.messages[2].content == "Transferred to first_agent."
assert result.messages[3].content == "Transferred to second_agent."
assert result.messages[4].content == "Transferred to third_agent."
assert result.messages[5].content == "Transferred to first_agent."
assert (
result.stop_reason is not None
and result.stop_reason == "Maximum number of messages 6 reached, current message count: 6"
)
2024-11-01 04:12:43 -07:00
# Test streaming.
index = 0
await team.reset()
stream = team.run_stream(task="task")
2024-11-01 04:12:43 -07:00
async for message in stream:
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test save and load.
state = await team.save_state()
first_agent2 = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
second_agent2 = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
third_agent2 = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team2 = Swarm([second_agent2, first_agent2, third_agent2], termination_condition=termination, runtime=runtime)
await team2.load_state(state)
state2 = await team2.save_state()
assert state == state2
manager_1 = await team._runtime.try_get_underlying_agent_instance( # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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AgentId(f"{team._group_chat_manager_name}_{team._team_id}", team._team_id), # pyright: ignore
SwarmGroupChatManager, # pyright: ignore
) # pyright: ignore
manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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AgentId(f"{team2._group_chat_manager_name}_{team2._team_id}", team2._team_id), # pyright: ignore
SwarmGroupChatManager, # pyright: ignore
) # pyright: ignore
assert manager_1._message_thread == manager_2._message_thread # pyright: ignore
assert manager_1._current_speaker == manager_2._current_speaker # pyright: ignore
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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async def test_swarm_handoff_using_tool_calls(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
chat_completions=[
CreateResult(
finish_reason="function_calls",
content=[FunctionCall(id="1", name="handoff_to_agent2", arguments=json.dumps({}))],
usage=RequestUsage(prompt_tokens=0, completion_tokens=0),
cached=False,
),
"Hello",
"TERMINATE",
],
model_info={"family": "gpt-4o", "function_calling": True, "json_output": True, "vision": True},
)
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agent1 = AssistantAgent(
"agent1",
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client=model_client,
handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
)
agent2 = _HandOffAgent("agent2", description="agent 2", next_agent="agent1")
termination = TextMentionTermination("TERMINATE")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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team = Swarm([agent1, agent2], termination_condition=termination, runtime=runtime)
result = await team.run(task="task")
assert len(result.messages) == 7
assert result.messages[0].content == "task"
assert isinstance(result.messages[1], ToolCallRequestEvent)
assert isinstance(result.messages[2], ToolCallExecutionEvent)
assert result.messages[3].content == "handoff to agent2"
assert result.messages[4].content == "Transferred to agent1."
assert result.messages[5].content == "Hello"
assert result.messages[6].content == "TERMINATE"
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
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# Test streaming.
await agent1._model_context.clear() # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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model_client.reset()
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index = 0
await team.reset()
stream = team.run_stream(task="task")
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async for message in stream:
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test Console
await agent1._model_context.clear() # pyright: ignore
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client.reset()
index = 0
await team.reset()
result2 = await Console(team.run_stream(task="task"))
assert result2 == result
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_swarm_pause_and_resume(runtime: AgentRuntime | None) -> None:
first_agent = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = Swarm([second_agent, first_agent, third_agent], max_turns=1, runtime=runtime)
result = await team.run(task="task")
assert len(result.messages) == 2
assert result.messages[0].content == "task"
assert result.messages[1].content == "Transferred to third_agent."
# Resume with a new task.
result = await team.run(task="new task")
assert len(result.messages) == 2
assert result.messages[0].content == "new task"
assert result.messages[1].content == "Transferred to first_agent."
# Resume with the same task.
result = await team.run()
assert len(result.messages) == 1
assert result.messages[0].content == "Transferred to second_agent."
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_swarm_with_parallel_tool_calls(runtime: AgentRuntime | None) -> None:
model_client = ReplayChatCompletionClient(
[
CreateResult(
finish_reason="function_calls",
content=[
FunctionCall(id="1", name="tool1", arguments="{}"),
FunctionCall(id="2", name="tool2", arguments="{}"),
FunctionCall(id="3", name="handoff_to_agent2", arguments=json.dumps({})),
],
usage=RequestUsage(prompt_tokens=0, completion_tokens=0),
cached=False,
),
"Hello",
"TERMINATE",
],
model_info={"family": "gpt-4o", "function_calling": True, "json_output": True, "vision": True},
)
expected_handoff_context: List[LLMMessage] = [
AssistantMessage(
source="agent1",
content=[
FunctionCall(id="1", name="tool1", arguments="{}"),
FunctionCall(id="2", name="tool2", arguments="{}"),
],
),
FunctionExecutionResultMessage(
content=[
fix: Update SKChatCompletionAdapter message conversion (#5749) <!-- Thank you for your contribution! Please review https://microsoft.github.io/autogen/docs/Contribute before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? <!-- Please give a short summary of the change and the problem this solves. --> The PR introduces two changes. The first change is adding a name attribute to `FunctionExecutionResult`. The motivation is that semantic kernel requires it for their function result interface and it seemed like a easy modification as `FunctionExecutionResult` is always created in the context of a `FunctionCall` which will contain the name. I'm unsure if there was a motivation to keep it out but this change makes it easier to trace which tool the result refers to and also increases api compatibility with SK. The second change is an update to how messages are mapped from autogen to semantic kernel, which includes an update/fix in the processing of function results. ## Related issue number <!-- For example: "Closes #1234" --> Related to #5675 but wont fix the underlying issue of anthropic requiring tools during AssistantAgent reflection. ## Checks - [ ] I've included any doc changes needed for <https://microsoft.github.io/autogen/>. See <https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to build and test documentation locally. - [ ] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [ ] I've made sure all auto checks have passed. --------- Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>
2025-03-04 09:05:54 +10:00
FunctionExecutionResult(content="tool1", call_id="1", is_error=False, name="tool1"),
FunctionExecutionResult(content="tool2", call_id="2", is_error=False, name="tool2"),
]
),
]
def tool1() -> str:
return "tool1"
def tool2() -> str:
return "tool2"
agent1 = AssistantAgent(
"agent1",
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client=model_client,
handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
tools=[tool1, tool2],
)
agent2 = AssistantAgent(
"agent2",
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
model_client=model_client,
)
termination = TextMentionTermination("TERMINATE")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = Swarm([agent1, agent2], termination_condition=termination, runtime=runtime)
result = await team.run(task="task")
assert len(result.messages) == 6
assert result.messages[0] == TextMessage(content="task", source="user")
assert isinstance(result.messages[1], ToolCallRequestEvent)
assert isinstance(result.messages[2], ToolCallExecutionEvent)
assert result.messages[3] == HandoffMessage(
content="handoff to agent2",
target="agent2",
source="agent1",
context=expected_handoff_context,
)
assert result.messages[4].content == "Hello"
assert result.messages[4].source == "agent2"
assert result.messages[5].content == "TERMINATE"
assert result.messages[5].source == "agent2"
# Verify the tool calls are in agent2's context.
agent2_model_ctx_messages = await agent2._model_context.get_messages() # pyright: ignore
assert agent2_model_ctx_messages[0] == UserMessage(content="task", source="user")
assert agent2_model_ctx_messages[1] == expected_handoff_context[0]
assert agent2_model_ctx_messages[2] == expected_handoff_context[1]
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_swarm_with_handoff_termination(runtime: AgentRuntime | None) -> None:
first_agent = _HandOffAgent("first_agent", description="first agent", next_agent="second_agent")
second_agent = _HandOffAgent("second_agent", description="second agent", next_agent="third_agent")
third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="first_agent")
# Handoff to an existing agent.
termination = HandoffTermination(target="third_agent")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination, runtime=runtime)
# Start
result = await team.run(task="task")
assert len(result.messages) == 2
assert result.messages[0].content == "task"
assert result.messages[1].content == "Transferred to third_agent."
# Resume existing.
result = await team.run()
assert len(result.messages) == 3
assert result.messages[0].content == "Transferred to first_agent."
assert result.messages[1].content == "Transferred to second_agent."
assert result.messages[2].content == "Transferred to third_agent."
# Resume new task.
result = await team.run(task="new task")
assert len(result.messages) == 4
assert result.messages[0].content == "new task"
assert result.messages[1].content == "Transferred to first_agent."
assert result.messages[2].content == "Transferred to second_agent."
assert result.messages[3].content == "Transferred to third_agent."
# Handoff to a non-existing agent.
third_agent = _HandOffAgent("third_agent", description="third agent", next_agent="non_existing_agent")
termination = HandoffTermination(target="non_existing_agent")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination, runtime=runtime)
# Start
result = await team.run(task="task")
assert len(result.messages) == 3
assert result.messages[0].content == "task"
assert result.messages[1].content == "Transferred to third_agent."
assert result.messages[2].content == "Transferred to non_existing_agent."
# Attempt to resume.
with pytest.raises(ValueError):
await team.run()
# Attempt to resume with a new task.
with pytest.raises(ValueError):
await team.run(task="new task")
# Resume with a HandoffMessage
result = await team.run(task=HandoffMessage(content="Handoff to first_agent.", target="first_agent", source="user"))
assert len(result.messages) == 4
assert result.messages[0].content == "Handoff to first_agent."
assert result.messages[1].content == "Transferred to second_agent."
assert result.messages[2].content == "Transferred to third_agent."
assert result.messages[3].content == "Transferred to non_existing_agent."
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
2025-03-06 10:32:52 -08:00
async def test_round_robin_group_chat_with_message_list(runtime: AgentRuntime | None) -> None:
# Create a simple team with echo agents
agent1 = _EchoAgent("Agent1", "First agent")
agent2 = _EchoAgent("Agent2", "Second agent")
termination = MaxMessageTermination(4) # Stop after 4 messages
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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team = RoundRobinGroupChat([agent1, agent2], termination_condition=termination, runtime=runtime)
# Create a list of messages
messages: List[ChatMessage] = [
TextMessage(content="Message 1", source="user"),
TextMessage(content="Message 2", source="user"),
TextMessage(content="Message 3", source="user"),
]
# Run the team with the message list
result = await team.run(task=messages)
# Verify the messages were processed in order
assert len(result.messages) == 4 # Initial messages + echo until termination
assert result.messages[0].content == "Message 1" # First message
assert result.messages[1].content == "Message 2" # Second message
assert result.messages[2].content == "Message 3" # Third message
assert result.messages[3].content == "Message 1" # Echo from first agent
assert result.stop_reason == "Maximum number of messages 4 reached, current message count: 4"
# Test with streaming
await team.reset()
index = 0
async for message in team.run_stream(task=messages):
if isinstance(message, TaskResult):
assert message == result
else:
assert message == result.messages[index]
index += 1
# Test with invalid message list
with pytest.raises(ValueError, match="All messages in task list must be valid ChatMessage types"):
await team.run(task=["not a message"]) # type: ignore[list-item, arg-type] # intentionally testing invalid input
# Test with empty message list
with pytest.raises(ValueError, match="Task list cannot be empty"):
await team.run(task=[])
@pytest.mark.asyncio
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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async def test_declarative_groupchats_with_config(runtime: AgentRuntime | None) -> None:
# Create basic agents and components for testing
agent1 = AssistantAgent(
"agent_1",
model_client=OpenAIChatCompletionClient(model="gpt-4o-2024-05-13", api_key=""),
handoffs=["agent_2"],
)
agent2 = AssistantAgent("agent_2", model_client=OpenAIChatCompletionClient(model="gpt-4o-2024-05-13", api_key=""))
termination = MaxMessageTermination(4)
model_client = OpenAIChatCompletionClient(model="gpt-4o-2024-05-13", api_key="")
# Test round robin - verify config is preserved
round_robin = RoundRobinGroupChat(participants=[agent1, agent2], termination_condition=termination, max_turns=5)
config = round_robin.dump_component()
loaded = RoundRobinGroupChat.load_component(config)
assert loaded.dump_component() == config
# Test selector group chat - verify config is preserved
selector_prompt = "Custom selector prompt with {roles}, {participants}, {history}"
selector = SelectorGroupChat(
participants=[agent1, agent2],
model_client=model_client,
termination_condition=termination,
max_turns=10,
selector_prompt=selector_prompt,
allow_repeated_speaker=True,
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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runtime=runtime,
)
selector_config = selector.dump_component()
selector_loaded = SelectorGroupChat.load_component(selector_config)
assert selector_loaded.dump_component() == selector_config
# Test swarm with handoff termination
handoff_termination = HandoffTermination(target="Agent2")
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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swarm = Swarm(
participants=[agent1, agent2], termination_condition=handoff_termination, max_turns=5, runtime=runtime
)
swarm_config = swarm.dump_component()
swarm_loaded = Swarm.load_component(swarm_config)
assert swarm_loaded.dump_component() == swarm_config
# Test MagenticOne with custom parameters
magentic = MagenticOneGroupChat(
participants=[agent1],
model_client=model_client,
max_turns=15,
max_stalls=5,
final_answer_prompt="Custom prompt",
Support for external agent runtime in AgentChat (#5843) Resolves #4075 1. Introduce custom runtime parameter for all AgentChat teams (RoundRobinGroupChat, SelectorGroupChat, etc.). This is done by making sure each team's topics are isolated from other teams, and decoupling state from agent identities. Also, I removed the closure agent from the BaseGroupChat and use the group chat manager agent to relay messages to the output message queue. 2. Added unit tests to test scenarios with custom runtimes by using pytest fixture 3. Refactored existing unit tests to use ReplayChatCompletionClient with a few improvements to the client. 4. Fix a one-liner bug in AssistantAgent that caused deserialized agent to have handoffs. How to use it? ```python import asyncio from autogen_core import SingleThreadedAgentRuntime from autogen_agentchat.agents import AssistantAgent from autogen_agentchat.teams import RoundRobinGroupChat from autogen_agentchat.conditions import TextMentionTermination from autogen_ext.models.replay import ReplayChatCompletionClient async def main() -> None: # Create a runtime runtime = SingleThreadedAgentRuntime() runtime.start() # Create a model client. model_client = ReplayChatCompletionClient( ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], ) # Create agents agent1 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent2 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") # Create a termination condition termination_condition = TextMentionTermination("10", sources=["assistant1", "assistant2"]) # Create a team team = RoundRobinGroupChat([agent1, agent2], runtime=runtime, termination_condition=termination_condition) # Run the team stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Save the state. state = await team.save_state() # Load the state to an existing team. await team.load_state(state) # Run the team again model_client.reset() stream = team.run_stream(task="Count to 10.") async for message in stream: print(message) # Create a new team, with the same agent names. agent3 = AssistantAgent("assistant1", model_client=model_client, system_message="You are a helpful assistant.") agent4 = AssistantAgent("assistant2", model_client=model_client, system_message="You are a helpful assistant.") new_team = RoundRobinGroupChat([agent3, agent4], runtime=runtime, termination_condition=termination_condition) # Load the state to the new team. await new_team.load_state(state) # Run the new team model_client.reset() new_stream = new_team.run_stream(task="Count to 10.") async for message in new_stream: print(message) # Stop the runtime await runtime.stop() asyncio.run(main()) ``` TODOs as future PRs: 1. Documentation. 2. How to handle errors in custom runtime when the agent has exception? --------- Co-authored-by: Ryan Sweet <rysweet@microsoft.com>
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runtime=runtime,
)
magentic_config = magentic.dump_component()
magentic_loaded = MagenticOneGroupChat.load_component(magentic_config)
assert magentic_loaded.dump_component() == magentic_config
# Verify component types are correctly set for each
for team in [loaded, selector, swarm, magentic]:
assert team.component_type == "team"
# Verify provider strings are correctly set
assert round_robin.dump_component().provider == "autogen_agentchat.teams.RoundRobinGroupChat"
assert selector.dump_component().provider == "autogen_agentchat.teams.SelectorGroupChat"
assert swarm.dump_component().provider == "autogen_agentchat.teams.Swarm"
assert magentic.dump_component().provider == "autogen_agentchat.teams.MagenticOneGroupChat"