mirror of
https://github.com/microsoft/autogen.git
synced 2025-10-31 09:50:11 +00:00
979d8ab4f1
* initial pass on making group chats declarative * update group chat tests * update impl to include participant serialization for all teams * v1 making soc declarative * update memory test * update chatagent and team base classes * update serialization doc notebook * fomating updates
1280 lines
52 KiB
Python
1280 lines
52 KiB
Python
import asyncio
|
|
import json
|
|
import logging
|
|
import tempfile
|
|
from typing import Any, AsyncGenerator, List, Sequence
|
|
|
|
import pytest
|
|
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
|
|
from autogen_core import AgentId, CancellationToken, FunctionCall
|
|
from autogen_core.models import (
|
|
AssistantMessage,
|
|
FunctionExecutionResult,
|
|
FunctionExecutionResultMessage,
|
|
LLMMessage,
|
|
UserMessage,
|
|
)
|
|
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 openai.resources.chat.completions import AsyncCompletions
|
|
from openai.types.chat.chat_completion import ChatCompletion, Choice
|
|
from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
|
|
from openai.types.chat.chat_completion_message import ChatCompletionMessage
|
|
from openai.types.chat.chat_completion_message_tool_call import ChatCompletionMessageToolCall, Function
|
|
from openai.types.completion_usage import CompletionUsage
|
|
from utils import FileLogHandler
|
|
|
|
logger = logging.getLogger(EVENT_LOGGER_NAME)
|
|
logger.setLevel(logging.DEBUG)
|
|
logger.addHandler(FileLogHandler("test_group_chat.log"))
|
|
|
|
|
|
class _MockChatCompletion:
|
|
def __init__(self, chat_completions: List[ChatCompletion]) -> None:
|
|
self._saved_chat_completions = chat_completions
|
|
self._curr_index = 0
|
|
|
|
async def mock_create(
|
|
self, *args: Any, **kwargs: Any
|
|
) -> ChatCompletion | AsyncGenerator[ChatCompletionChunk, None]:
|
|
await asyncio.sleep(0.1)
|
|
completion = self._saved_chat_completions[self._curr_index]
|
|
self._curr_index += 1
|
|
return completion
|
|
|
|
def reset(self) -> None:
|
|
self._curr_index = 0
|
|
|
|
|
|
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))
|
|
|
|
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"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_round_robin_group_chat(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id1",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="stop",
|
|
index=0,
|
|
message=ChatCompletionMessage(
|
|
content="""Here is the program\n ```python\nprint("Hello, world!")\n```""",
|
|
role="assistant",
|
|
),
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="stop",
|
|
index=0,
|
|
message=ChatCompletionMessage(content="TERMINATE", role="assistant"),
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
with tempfile.TemporaryDirectory() as temp_dir:
|
|
code_executor_agent = CodeExecutorAgent(
|
|
"code_executor", code_executor=LocalCommandLineCodeExecutor(work_dir=temp_dir)
|
|
)
|
|
coding_assistant_agent = AssistantAgent(
|
|
"coding_assistant", model_client=OpenAIChatCompletionClient(model=model, api_key="")
|
|
)
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = RoundRobinGroupChat(
|
|
participants=[coding_assistant_agent, code_executor_agent], termination_condition=termination
|
|
)
|
|
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"
|
|
|
|
# Test streaming.
|
|
mock.reset()
|
|
index = 0
|
|
await team.reset()
|
|
async for message in team.run_stream(
|
|
task="Write a program that prints 'Hello, world!'",
|
|
):
|
|
if isinstance(message, TaskResult):
|
|
assert message == result
|
|
else:
|
|
assert message == result.messages[index]
|
|
index += 1
|
|
|
|
# Test message input.
|
|
# Text message.
|
|
mock.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.
|
|
mock.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
|
|
async def test_round_robin_group_chat_state() -> 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")
|
|
team1 = RoundRobinGroupChat(participants=[agent1, agent2], termination_condition=termination)
|
|
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 = RoundRobinGroupChat(participants=[agent3, agent4], termination_condition=termination)
|
|
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
|
|
AgentId("group_chat_manager", team1._team_id), # pyright: ignore
|
|
RoundRobinGroupChatManager, # pyright: ignore
|
|
) # pyright: ignore
|
|
manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
|
|
AgentId("group_chat_manager", 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
|
|
async def test_round_robin_group_chat_with_tools(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id1",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="tool_calls",
|
|
index=0,
|
|
message=ChatCompletionMessage(
|
|
content=None,
|
|
tool_calls=[
|
|
ChatCompletionMessageToolCall(
|
|
id="1",
|
|
type="function",
|
|
function=Function(
|
|
name="pass",
|
|
arguments=json.dumps({"input": "pass"}),
|
|
),
|
|
)
|
|
],
|
|
role="assistant",
|
|
),
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="Hello", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="stop", index=0, message=ChatCompletionMessage(content="TERMINATE", role="assistant")
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
# Test with repeat tool calls once
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
tool = FunctionTool(_pass_function, name="pass", description="pass function")
|
|
tool_use_agent = AssistantAgent(
|
|
"tool_use_agent",
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
tools=[tool],
|
|
)
|
|
echo_agent = _EchoAgent("echo_agent", description="echo agent")
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = RoundRobinGroupChat(participants=[tool_use_agent, echo_agent], termination_condition=termination)
|
|
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"
|
|
|
|
# Test streaming.
|
|
await tool_use_agent._model_context.clear() # pyright: ignore
|
|
mock.reset()
|
|
index = 0
|
|
await team.reset()
|
|
async for message in team.run_stream(
|
|
task="Write a program that prints 'Hello, world!'",
|
|
):
|
|
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
|
|
mock.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
|
|
async def test_round_robin_group_chat_with_resume_and_reset() -> 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)
|
|
team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], termination_condition=termination)
|
|
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
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_round_robin_group_chat_max_turn() -> 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")
|
|
team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], max_turns=3)
|
|
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
|
|
async def test_round_robin_group_chat_cancellation() -> 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.
|
|
team = RoundRobinGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], max_turns=1000)
|
|
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
|
|
|
|
# Total messages produced so far.
|
|
total_messages = agent_1.total_messages + agent_2.total_messages + agent_3.total_messages + agent_4.total_messages
|
|
|
|
# Still can run again and finish the task.
|
|
result = await team.run()
|
|
assert len(result.messages) + total_messages == 1000
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_selector_group_chat(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent3", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent2", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent1", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent2", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent1", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
|
|
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=2)
|
|
agent2 = _EchoAgent("agent2", description="echo agent 2")
|
|
agent3 = _EchoAgent("agent3", description="echo agent 3")
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = SelectorGroupChat(
|
|
participants=[agent1, agent2, agent3],
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
termination_condition=termination,
|
|
)
|
|
result = await team.run(
|
|
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"
|
|
|
|
# Test streaming.
|
|
mock.reset()
|
|
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!'",
|
|
):
|
|
if isinstance(message, TaskResult):
|
|
assert message == result
|
|
else:
|
|
assert message == result.messages[index]
|
|
index += 1
|
|
|
|
# Test Console.
|
|
mock.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
|
|
async def test_selector_group_chat_state() -> 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(
|
|
participants=[agent1, agent2], termination_condition=termination, model_client=model_client
|
|
)
|
|
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
|
|
AgentId("group_chat_manager", team1._team_id), # pyright: ignore
|
|
SelectorGroupChatManager, # pyright: ignore
|
|
) # pyright: ignore
|
|
manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
|
|
AgentId("group_chat_manager", 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
|
|
async def test_selector_group_chat_two_speakers(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent2", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
|
|
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=2)
|
|
agent2 = _EchoAgent("agent2", description="echo agent 2")
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = SelectorGroupChat(
|
|
participants=[agent1, agent2],
|
|
termination_condition=termination,
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
)
|
|
result = await team.run(
|
|
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"
|
|
# only one chat completion was called
|
|
assert mock._curr_index == 1 # pyright: ignore
|
|
assert result.stop_reason is not None and result.stop_reason == "Text 'TERMINATE' mentioned"
|
|
|
|
# Test streaming.
|
|
mock.reset()
|
|
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!'"):
|
|
if isinstance(message, TaskResult):
|
|
assert message == result
|
|
else:
|
|
assert message == result.messages[index]
|
|
index += 1
|
|
|
|
# Test Console.
|
|
mock.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
|
|
async def test_selector_group_chat_two_speakers_allow_repeated(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent2", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent2", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent1", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
|
|
agent1 = _StopAgent("agent1", description="echo agent 1", stop_at=1)
|
|
agent2 = _EchoAgent("agent2", description="echo agent 2")
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = SelectorGroupChat(
|
|
participants=[agent1, agent2],
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
termination_condition=termination,
|
|
allow_repeated_speaker=True,
|
|
)
|
|
result = await team.run(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"
|
|
|
|
# Test streaming.
|
|
mock.reset()
|
|
index = 0
|
|
await team.reset()
|
|
async for message in team.run_stream(task="Write a program that prints 'Hello, world!'"):
|
|
if isinstance(message, TaskResult):
|
|
assert message == result
|
|
else:
|
|
assert message == result.messages[index]
|
|
index += 1
|
|
|
|
# Test Console.
|
|
mock.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
|
|
async def test_selector_group_chat_custom_selector(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="agent3", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
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],
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
selector_func=_select_agent,
|
|
termination_condition=termination,
|
|
)
|
|
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
|
|
)
|
|
)
|
|
|
|
async def on_reset(self, cancellation_token: CancellationToken) -> None:
|
|
pass
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_swarm_handoff() -> 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)
|
|
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination)
|
|
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"
|
|
)
|
|
|
|
# Test streaming.
|
|
index = 0
|
|
await team.reset()
|
|
stream = team.run_stream(task="task")
|
|
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")
|
|
team2 = Swarm([second_agent2, first_agent2, third_agent2], termination_condition=termination)
|
|
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
|
|
AgentId("group_chat_manager", team._team_id), # pyright: ignore
|
|
SwarmGroupChatManager, # pyright: ignore
|
|
) # pyright: ignore
|
|
manager_2 = await team2._runtime.try_get_underlying_agent_instance( # pyright: ignore
|
|
AgentId("group_chat_manager", 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
|
|
async def test_swarm_handoff_using_tool_calls(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id1",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="tool_calls",
|
|
index=0,
|
|
message=ChatCompletionMessage(
|
|
content=None,
|
|
tool_calls=[
|
|
ChatCompletionMessageToolCall(
|
|
id="1",
|
|
type="function",
|
|
function=Function(
|
|
name="handoff_to_agent2",
|
|
arguments=json.dumps({}),
|
|
),
|
|
)
|
|
],
|
|
role="assistant",
|
|
),
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="Hello", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="stop", index=0, message=ChatCompletionMessage(content="TERMINATE", role="assistant")
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
|
|
agent1 = AssistantAgent(
|
|
"agent1",
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
|
|
)
|
|
agent2 = _HandOffAgent("agent2", description="agent 2", next_agent="agent1")
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = Swarm([agent1, agent2], termination_condition=termination)
|
|
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"
|
|
|
|
# Test streaming.
|
|
await agent1._model_context.clear() # pyright: ignore
|
|
mock.reset()
|
|
index = 0
|
|
await team.reset()
|
|
stream = team.run_stream(task="task")
|
|
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
|
|
mock.reset()
|
|
index = 0
|
|
await team.reset()
|
|
result2 = await Console(team.run_stream(task="task"))
|
|
assert result2 == result
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_swarm_pause_and_resume() -> 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")
|
|
|
|
team = Swarm([second_agent, first_agent, third_agent], max_turns=1)
|
|
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
|
|
async def test_swarm_with_parallel_tool_calls(monkeypatch: pytest.MonkeyPatch) -> None:
|
|
model = "gpt-4o-2024-05-13"
|
|
chat_completions = [
|
|
ChatCompletion(
|
|
id="id1",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="tool_calls",
|
|
index=0,
|
|
message=ChatCompletionMessage(
|
|
content=None,
|
|
tool_calls=[
|
|
ChatCompletionMessageToolCall(
|
|
id="1",
|
|
type="function",
|
|
function=Function(
|
|
name="tool1",
|
|
arguments=json.dumps({}),
|
|
),
|
|
),
|
|
ChatCompletionMessageToolCall(
|
|
id="2",
|
|
type="function",
|
|
function=Function(
|
|
name="tool2",
|
|
arguments=json.dumps({}),
|
|
),
|
|
),
|
|
ChatCompletionMessageToolCall(
|
|
id="3",
|
|
type="function",
|
|
function=Function(
|
|
name="handoff_to_agent2",
|
|
arguments=json.dumps({}),
|
|
),
|
|
),
|
|
],
|
|
role="assistant",
|
|
),
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(finish_reason="stop", index=0, message=ChatCompletionMessage(content="Hello", role="assistant"))
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
ChatCompletion(
|
|
id="id2",
|
|
choices=[
|
|
Choice(
|
|
finish_reason="stop", index=0, message=ChatCompletionMessage(content="TERMINATE", role="assistant")
|
|
)
|
|
],
|
|
created=0,
|
|
model=model,
|
|
object="chat.completion",
|
|
usage=CompletionUsage(prompt_tokens=0, completion_tokens=0, total_tokens=0),
|
|
),
|
|
]
|
|
mock = _MockChatCompletion(chat_completions)
|
|
monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
|
|
|
|
expected_handoff_context: List[LLMMessage] = [
|
|
AssistantMessage(
|
|
source="agent1",
|
|
content=[
|
|
FunctionCall(id="1", name="tool1", arguments="{}"),
|
|
FunctionCall(id="2", name="tool2", arguments="{}"),
|
|
],
|
|
),
|
|
FunctionExecutionResultMessage(
|
|
content=[
|
|
FunctionExecutionResult(content="tool1", call_id="1"),
|
|
FunctionExecutionResult(content="tool2", call_id="2"),
|
|
]
|
|
),
|
|
]
|
|
|
|
def tool1() -> str:
|
|
return "tool1"
|
|
|
|
def tool2() -> str:
|
|
return "tool2"
|
|
|
|
agent1 = AssistantAgent(
|
|
"agent1",
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
handoffs=[Handoff(target="agent2", name="handoff_to_agent2", message="handoff to agent2")],
|
|
tools=[tool1, tool2],
|
|
)
|
|
agent2 = AssistantAgent(
|
|
"agent2",
|
|
model_client=OpenAIChatCompletionClient(model=model, api_key=""),
|
|
)
|
|
termination = TextMentionTermination("TERMINATE")
|
|
team = Swarm([agent1, agent2], termination_condition=termination)
|
|
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
|
|
async def test_swarm_with_handoff_termination() -> 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")
|
|
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination)
|
|
# 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")
|
|
team = Swarm([second_agent, first_agent, third_agent], termination_condition=termination)
|
|
# 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
|
|
async def test_round_robin_group_chat_with_message_list() -> 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
|
|
team = RoundRobinGroupChat([agent1, agent2], termination_condition=termination)
|
|
|
|
# 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
|
|
async def test_declarative_groupchats_with_config() -> 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,
|
|
)
|
|
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")
|
|
swarm = Swarm(participants=[agent1, agent2], termination_condition=handoff_termination, max_turns=5)
|
|
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",
|
|
)
|
|
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"
|