在NiceGUI中集成AutoGen并捕获Agent响应的教程

import autogen
from nicegui import ui, context
from uuid import uuid4

# 1. AutoGen 配置
config_list = [
    {
        'model': 'gpt-4',
        'api_key': 'YOUR_API_KEY' # 请替换为您的实际API密钥
    }
]
llm_config = {
    'seed': 42,
    'config_list': config_list,
    'temperature': 0.2
}

# 2. 初始化AutoGen Agent
assistant = autogen.AssistantAgent(name='Albert', llm_config=llm_config)
user_proxy = autogen.UserProxyAgent(
    name='user_proxy',
    human_input_mode="NEVER", # 在NiceGUI中，用户输入通过UI提供，Agent无需直接请求
    max_consecutive_auto_reply=10, # 允许更多轮次自动回复
    is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
    code_execution_config={"work_dir": "web"}, # 设定代码执行的工作目录
    llm_config=llm_config
)

# 3. NiceGUI 界面定义
@ui.page('/')
def main():
    # 存储聊天消息的列表，用于UI显示
    messages = []
    user_id = str(uuid4()) # 为每个用户会话生成唯一ID

    @ui.refreshable
    def chat_messages():
        """刷新聊天消息显示区域"""
        for name, text in messages:
            ui.chat_message(text=text, name=name, sent=name == 'You')
        if context.get_client().has_socket_connection:
            # 自动滚动到底部
            ui.run_javascript('setTimeout(() => window.scrollTo(0, document.body.scrollHeight), 0)')

    # ... (发送消息的逻辑将在后面修改)
    # ... (UI布局)

# 原始的尝试
response = await user_proxy.initiate_chat(assistant, message=user_message)
if response and 'content' in response[0]: # 这里的response[0]通常是最后一条消息
    assistant_response = response[0]['content']
    messages.append(('Albert', assistant_response))

agent.register_reply(
    trigger: Union[Type[Agent], Agent, List[Union[Type[Agent], Agent]], None],
    reply_func: Callable,
    config: Optional[Any] = None,
    reset_config: Optional[Callable] = None,
    position: Optional[int] = None
)

# 定义一个辅助函数来更新UI消息列表并刷新
def append_and_refresh_ui_messages(sender_name: str, content: str):
    """将消息添加到UI列表并刷新NiceGUI界面"""
    messages.append((sender_name, content))
    chat_messages.refresh()

# AutoGen回调函数
def autogen_reply_callback(recipient, current_messages, sender, config):
    """
    AutoGen Agent消息回调函数，用于捕获Agent的实时回复。
    """
    # current_messages 是一个列表，包含当前回合的所有消息。
    # 最后一条消息是刚刚发送或接收的消息。
    if current_messages:
        last_message = current_messages[-1]
        sender_name = last_message.get('name', sender.name) # 优先使用消息中的name，否则使用sender的name
        content = last_message.get('content', '')

        if content:
            # 使用NiceGUI的run_sync将UI更新操作调度到主线程
            ui.run_sync(lambda: append_and_refresh_ui_messages(sender_name, content))

    # 返回 False, None 表示Agent应继续其默认的回复生成逻辑
    return False, None

# 在 main() 函数内部，在 Agent 初始化之后，NiceGUI UI定义之前
# 注册回调函数
assistant.register_reply(
    [autogen.Agent, None], # 捕获assistant发送给任何Agent的消息
    reply_func=autogen_reply_callback,
    config={"callback": None},
)
user_proxy.register_reply(
    [autogen.Agent, None], # 捕获user_proxy发送给任何Agent的消息
    reply_func=autogen_reply_callback,
    config={"callback": None},
)

import autogen
from nicegui import ui, context
from uuid import uuid4

# AutoGen Configuration
config_list = [
    {
        'model': 'gpt-4',
        'api_key': 'YOUR_API_KEY' # 替换为您的实际API密钥
    }
]
llm_config = {
    'seed': 42,
    'config_list': config_list,
    'temperature': 0.2
}

# Initialize AutoGen Agents (在 main() 外部初始化，以便在回调中访问)
assistant = autogen.AssistantAgent(name='Albert', llm_config=llm_config)
user_proxy = autogen.UserProxyAgent(
    name='user_proxy',
    human_input_mode="NEVER",
    max_consecutive_auto_reply=10,
    is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
    code_execution_config={"work_dir": "web"},
    llm_config=llm_config
)

@ui.page('/')
def main():
    messages = [] # 存储聊天消息的列表
    user_id = str(uuid4())

    @ui.refreshable
    def chat_messages():
        for name, text in messages:
            ui.chat_message(text=text, name=name, sent=name == 'You')
        if context.get_client().has_socket_connection:
            ui.run_javascript('setTimeout(() => window.scrollTo(0, document.body.scrollHeight), 0)')

    # 定义辅助函数和回调函数，它们需要访问到 main() 作用域内的 messages 和 chat_messages
    def append_and_refresh_ui_messages(sender_name: str, content: str):
        messages.append((sender_name, content))
        chat_messages.refresh()

    def autogen_reply_callback(recipient, current_messages, sender, config):
        if current_messages:
            last_message = current_messages[-1]
            sender_name = last_message.get('name', sender.name)
            content = last_message.get('content', '')

            if content:
                ui.run_sync(lambda: append_and_refresh_ui_messages(sender_name, content))
        return False, None

    # 注册回调函数
    assistant.register_reply(
        [autogen.Agent, None],
        reply_func=autogen_reply_callback,
        config={"callback": None},
    )
    user_proxy.register_reply(
        [autogen.Agent, None],
        reply_func=autogen_reply_callback,
        config={"callback": None},
    )

    async def send():
        user_message = task_input.value
        if not user_message.strip():
            return # 防止发送空消息

        # 用户自己的消息直接添加到UI列表
        append_and_refresh_ui_messages('You', user_message)
        task_input.value = '' # 清空输入框

        try:
            # 启动AutoGen对话，Agent的回复将通过回调函数处理
            await user_proxy.initiate_chat(assistant, message=user_message)
        except Exception as e:
            # 异常处理，显示错误信息
            ui.run_sync(lambda: append_and_refresh_ui_messages('Albert', f"Error: {e}"))
        finally:
            # 确保在对话结束后刷新UI（虽然回调已经刷新，但以防万一）
            ui.run_sync(chat_messages.refresh)


    with ui.scroll_area().classes('w-full h-60 p-3 bg-white overflow-auto'):
        chat_messages()

    with ui.footer().style('position: fixed; left: 0; bottom: 0; width: 100%; background: white; padding: 10px; box-shadow: 0 -2px 5px rgba(0,0,0,0.1);'):
        task_input = ui.input().style('width: calc(100% - 100px);').on('keydown.enter', send) # 支持回车发送
        ui.button('Send', on_click=send).style('width: 90px;')

ui.run(title='Chat with Albert')