summary_method(str or callable) - 一个字符串或者是一个能从对话中提取summary的可调用方法,默认是last_msg. summary_args(dict) - 一个字典,用于指定summary_method参数,默认{},支持的参数没有明说,已知的参数有summary_prompt和cache,其中默认的摘要Prompt为Summarize the takeaway from the conversation. Do n...
"max_turns": 2, "summary_method": "last_msg", }, { "recipient": AgentC, "message": "需要给AgentC的message", "max_turns": 2, "summary_method": "last_msg", }, { "recipient": AgentD, "message": "需要给AgentD的message", "max_turns": 2, "summary_method": "last_msg", },...
recipient 指定接收的Agent max_turns 指定最大对话回合数 summary_method和summary_args是用于指定对话结束后,如何输出本次对话摘要,默认为last_msg。 message 指定发起方的输入内容,可以是一个单一的字符串,ConversableAgent会自动将其转换为OpenAIAPI中所需要的content和role结构,我们也可以根据需求直接输入包含content和...
在顺序多Agent之间支持消息内容的结转(Carryover),由summary_method参数指定,该参数有两个默认值,分别是last_msg和reflection_with_llm。而遵循该参数的设计规范,即可实现自己的summary_method方法,如下所示: defmy_summary_method( sender: ConversableAgent, recipient: ConversableAgent, summary_args: dict, ): retu...
summary_method(str or callable) - 一个字符串或者是一个能从对话中提取summary的可调用方法,默认是last_msg. summary_args(dict) - 一个字典,用于指定summary_method参数,默认{},支持的参数没有明说,已知的参数有summary_prompt和cache,其中默认的摘要Prompt为Summarize the takeaway from the conversation. Do ...
"summary_method":"reflection_with_llm", }, { "sender": user_proxy, "recipient": content_creator, "message": content_creation_tasks[0], "carryover":"我希望在博客文章中包含一张数据表格或图表。", }, ] ) 这段代码是一个示例,展示了如何使用一个名为"autogen"的包来创建对话系统。在代码中:...
summary_method="last_msg" ) 1. 2. 3. 4. 5. 6. 输出如下: Critic (to Writer): Write a concise but engaging blogpost about DeepLearning.AI. Make sure the blogpost is within 100 words. --- Writer (to Critic): Title: Unveiling the Power of DeepLearning.AI Step into the world of ...
"summary_method": "reflection_with_llm", "max_turns": 1, "clear_history" : False }, { "sender": customer_proxy_agent, "recipient": customer_engagement_agent, "message": "Let's find something fun to read.", "max_turns": 1, ...
Please calculate the sum of even numbers from 0 to 1000.",# 聊天记录的总结方法,使用基于大语言模型的反思总结方法summary_method="reflection_with_llm",) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. ...
AssistantAgent( name="Rate_Recommender", llm_cnotallow=llm_config, max_consecutive_auto_reply=1, # Only reply once system_message=f"""You are a Proposal Generator and Rate Recommender. Your task is to create a structured project proposal.Wait until the Scope_Architect shares a summary ...