管理状态#
到目前为止，我们已经讨论了如何在多代理应用程序中构建组件 - 代理、团队、终止条件。在许多情况下，将这些组件的状态保存到磁盘并在以后加载它们非常有用。这在 Web 应用程序中尤其有用，在这种应用程序中，无状态端点响应请求并需要从持久存储加载应用程序的状态。
在本笔记本中，我们将讨论如何保存和加载代理、团队和终止条件的状态。
保存和加载代理#
我们可以通过调用 save_state() 方法来获取 AssistantAgent 的状态。
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import MaxMessageTermination
from autogen_agentchat.messages import TextMessage
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.ui import Console
from autogen_core import CancellationToken
from autogen_ext.models.openai import OpenAIChatCompletionClient
model_client = OpenAIChatCompletionClient(model="gpt-4o-2024-08-06")
assistant_agent = AssistantAgent(
name="assistant_agent",
system_message="You are a helpful assistant",
model_client=model_client,
)
# Use asyncio.run(...) when running in a script.
response = await assistant_agent.on_messages(
[TextMessage(content="Write a 3 line poem on lake tangayika", source="user")], CancellationToken()
)
print(response.chat_message)
await model_client.close()
In Tanganyika's embrace so wide and deep,
Ancient waters cradle secrets they keep,
Echoes of time where horizons sleep.
agent_state = await assistant_agent.save_state()
print(agent_state)
{'type': 'AssistantAgentState', 'version': '1.0.0', 'llm_messages': [{'content': 'Write a 3 line poem on lake tangayika', 'source': 'user', 'type': 'UserMessage'}, {'content': "In Tanganyika's embrace so wide and deep, \nAncient waters cradle secrets they keep, \nEchoes of time where horizons sleep. ", 'source': 'assistant_agent', 'type': 'AssistantMessage'}]}
model_client = OpenAIChatCompletionClient(model="gpt-4o-2024-08-06")
new_assistant_agent = AssistantAgent(
name="assistant_agent",
system_message="You are a helpful assistant",
model_client=model_client,
)
await new_assistant_agent.load_state(agent_state)
# Use asyncio.run(...) when running in a script.
response = await new_assistant_agent.on_messages(
[TextMessage(content="What was the last line of the previous poem you wrote", source="user")], CancellationToken()
)
print(response.chat_message)
await model_client.close()
The last line of the poem was: "Echoes of time where horizons sleep."
注意
对于 AssistantAgent，它的状态包括 model_context。如果编写自己的自定义代理，请考虑覆盖 save_state() 和 load_state() 方法来自定义行为。默认实现保存和加载空状态。
保存和加载团队#
我们可以通过调用团队上的 save_state 方法来获取团队的状态，并通过调用团队上的 load_state 方法将其加载回来。
当我们在团队上调用 save_state 时，它会保存团队中所有代理的状态。
我们将首先创建一个带有单个代理的简单 RoundRobinGroupChat 团队，并要求它写一首诗。
model_client = OpenAIChatCompletionClient(model="gpt-4o-2024-08-06")
# Define a team.
assistant_agent = AssistantAgent(
name="assistant_agent",
system_message="You are a helpful assistant",
model_client=model_client,
)
agent_team = RoundRobinGroupChat([assistant_agent], termination_condition=MaxMessageTermination(max_messages=2))
# Run the team and stream messages to the console.
stream = agent_team.run_stream(task="Write a beautiful poem 3-line about lake tangayika")
# Use asyncio.run(...) when running in a script.
await Console(stream)
# Save the state of the agent team.
team_state = await agent_team.save_state()
---------- user ----------
Write a beautiful poem 3-line about lake tangayika
---------- assistant_agent ----------
In Tanganyika's gleam, beneath the azure skies,
Whispers of ancient waters, in tranquil guise,
Nature's mirror, where dreams and serenity lie.
[Prompt tokens: 29, Completion tokens: 34]
---------- Summary ----------
Number of messages: 2
Finish reason: Maximum number of messages 2 reached, current message count: 2
Total prompt tokens: 29
Total completion tokens: 34
Duration: 0.71 seconds
如果我们重置团队（模拟团队的实例化），并提出问题 What was the last line of the poem you wrote?，我们看到团队无法完成此任务，因为没有对先前运行的引用。
await agent_team.reset()
stream = agent_team.run_stream(task="What was the last line of the poem you wrote?")
await Console(stream)
---------- user ----------
What was the last line of the poem you wrote?
---------- assistant_agent ----------
I'm sorry, but I am unable to recall or access previous interactions, including any specific poem I may have composed in our past conversations. If you like, I can write a new poem for you.
[Prompt tokens: 28, Completion tokens: 40]
---------- Summary ----------
Number of messages: 2
Finish reason: Maximum number of messages 2 reached, current message count: 2
Total prompt tokens: 28
Total completion tokens: 40
Duration: 0.70 seconds
TaskResult(messages=[TextMessage(source='user', models_usage=None, content='What was the last line of the poem you wrote?', type='TextMessage'), TextMessage(source='assistant_agent', models_usage=RequestUsage(prompt_tokens=28, completion_tokens=40), content="I'm sorry, but I am unable to recall or access previous interactions, including any specific poem I may have composed in our past conversations. If you like, I can write a new poem for you.", type='TextMessage')], stop_reason='Maximum number of messages 2 reached, current message count: 2')
接下来，我们加载团队的状态并提出相同的问题。我们看到团队能够准确地返回它写的诗的最后一行。
print(team_state)
# Load team state.
await agent_team.load_state(team_state)
stream = agent_team.run_stream(task="What was the last line of the poem you wrote?")
await Console(stream)
{'type': 'TeamState', 'version': '1.0.0', 'agent_states': {'group_chat_manager/a55364ad-86fd-46ab-9449-dcb5260b1e06': {'type': 'RoundRobinManagerState', 'version': '1.0.0', 'message_thread': [{'source': 'user', 'models_usage': None, 'content': 'Write a beautiful poem 3-line about lake tangayika', 'type': 'TextMessage'}, {'source': 'assistant_agent', 'models_usage': {'prompt_tokens': 29, 'completion_tokens': 34}, 'content': "In Tanganyika's gleam, beneath the azure skies, \nWhispers of ancient waters, in tranquil guise, \nNature's mirror, where dreams and serenity lie.", 'type': 'TextMessage'}], 'current_turn': 0, 'next_speaker_index': 0}, 'collect_output_messages/a55364ad-86fd-46ab-9449-dcb5260b1e06': {}, 'assistant_agent/a55364ad-86fd-46ab-9449-dcb5260b1e06': {'type': 'ChatAgentContainerState', 'version': '1.0.0', 'agent_state': {'type': 'AssistantAgentState', 'version': '1.0.0', 'llm_messages': [{'content': 'Write a beautiful poem 3-line about lake tangayika', 'source': 'user', 'type': 'UserMessage'}, {'content': "In Tanganyika's gleam, beneath the azure skies, \nWhispers of ancient waters, in tranquil guise, \nNature's mirror, where dreams and serenity lie.", 'source': 'assistant_agent', 'type': 'AssistantMessage'}]}, 'message_buffer': []}}, 'team_id': 'a55364ad-86fd-46ab-9449-dcb5260b1e06'}
---------- user ----------
What was the last line of the poem you wrote?
---------- assistant_agent ----------
The last line of the poem I wrote is:
"Nature's mirror, where dreams and serenity lie."
[Prompt tokens: 86, Completion tokens: 22]
---------- Summary ----------
Number of messages: 2
Finish reason: Maximum number of messages 2 reached, current message count: 2
Total prompt tokens: 86
Total completion tokens: 22
Duration: 0.96 seconds
TaskResult(messages=[TextMessage(source='user', models_usage=None, content='What was the last line of the poem you wrote?', type='TextMessage'), TextMessage(source='assistant_agent', models_usage=RequestUsage(prompt_tokens=86, completion_tokens=22), content='The last line of the poem I wrote is: \n"Nature\'s mirror, where dreams and serenity lie."', type='TextMessage')], stop_reason='Maximum number of messages 2 reached, current message count: 2')
持久化状态（文件或数据库）#
在许多情况下，我们可能希望将团队的状态持久化到磁盘（或数据库），并在以后加载它。状态是一个可以序列化为文件或写入数据库的字典。
import json
## save state to disk
with open("coding/team_state.json", "w") as f:
json.dump(team_state, f)
## load state from disk
with open("coding/team_state.json", "r") as f:
team_state = json.load(f)
new_agent_team = RoundRobinGroupChat([assistant_agent], termination_condition=MaxMessageTermination(max_messages=2))
await new_agent_team.load_state(team_state)
stream = new_agent_team.run_stream(task="What was the last line of the poem you wrote?")
await Console(stream)
await model_client.close()
---------- user ----------
What was the last line of the poem you wrote?
---------- assistant_agent ----------
The last line of the poem I wrote is:
"Nature's mirror, where dreams and serenity lie."
[Prompt tokens: 86, Completion tokens: 22]
---------- Summary ----------
Number of messages: 2
Finish reason: Maximum number of messages 2 reached, current message count: 2
Total prompt tokens: 86
Total completion tokens: 22
Duration: 0.72 seconds
TaskResult(messages=[TextMessage(source='user', models_usage=None, content='What was the last line of the poem you wrote?', type='TextMessage'), TextMessage(source='assistant_agent', models_usage=RequestUsage(prompt_tokens=86, completion_tokens=22), content='The last line of the poem I wrote is: \n"Nature\'s mirror, where dreams and serenity lie."', type='TextMessage')], stop_reason='Maximum number of messages 2 reached, current message count: 2')