1942ecee76
* Relax verify_first_message_correctness to accept any function call * Also allow missing internal monologue if request_heartbeat * Cleanup * get instead of raw dict access * Support attach in memgpt autogen agent * Add docs example * Add documentation, cleanup
89 lines
3.1 KiB
Python
89 lines
3.1 KiB
Python
"""Example of how to add MemGPT into an AutoGen groupchat and chat with docs.
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See https://memgpt.readthedocs.io/en/latest/autogen/#loading-documents
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Based on the official AutoGen example here: https://github.com/microsoft/autogen/blob/main/notebook/agentchat_groupchat.ipynb
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Begin by doing:
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pip install "pyautogen[teachable]"
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pip install pymemgpt
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or
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pip install -e . (inside the MemGPT home directory)
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"""
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import os
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import autogen
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from memgpt.autogen.memgpt_agent import create_autogen_memgpt_agent, create_memgpt_autogen_agent_from_config
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# This config is for autogen agents that are not powered by MemGPT
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config_list = [
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{
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"model": "gpt-4",
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"api_key": os.getenv("OPENAI_API_KEY"),
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}
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]
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# This config is for autogen agents that powered by MemGPT
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config_list_memgpt = [
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{
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"model": "gpt-4",
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},
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]
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USE_AUTOGEN_WORKFLOW = True
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# Set to True if you want to print MemGPT's inner workings.
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DEBUG = False
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interface_kwargs = {
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"debug": DEBUG,
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"show_inner_thoughts": DEBUG,
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"show_function_outputs": DEBUG,
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}
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llm_config = {"config_list": config_list, "seed": 42}
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llm_config_memgpt = {"config_list": config_list_memgpt, "seed": 42}
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# The user agent
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user_proxy = autogen.UserProxyAgent(
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name="User_proxy",
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system_message="A human admin.",
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code_execution_config={"last_n_messages": 2, "work_dir": "groupchat"},
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human_input_mode="TERMINATE", # needed?
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default_auto_reply="...", # Set a default auto-reply message here (non-empty auto-reply is required for LM Studio)
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)
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# In our example, we swap this AutoGen agent with a MemGPT agent
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# This MemGPT agent will have all the benefits of MemGPT, ie persistent memory, etc.
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if not USE_AUTOGEN_WORKFLOW:
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coder = create_autogen_memgpt_agent(
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"MemGPT_coder",
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persona_description="I am a 10x engineer, trained in Python. I was the first engineer at Uber "
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"(which I make sure to tell everyone I work with).",
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user_description=f"You are participating in a group chat with a user ({user_proxy.name}) " f"and a product manager ({pm.name}).",
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model=config_list_memgpt[0]["model"],
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interface_kwargs=interface_kwargs,
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)
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else:
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coder = create_memgpt_autogen_agent_from_config(
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"MemGPT_coder",
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llm_config=llm_config_memgpt,
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system_message=f"I am a 10x engineer, trained in Python. I was the first engineer at Uber "
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f"(which I make sure to tell everyone I work with).\n"
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f"You are participating in a group chat with a user ({user_proxy.name}).",
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interface_kwargs=interface_kwargs,
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)
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coder.attach("memgpt_research_paper") # See https://memgpt.readthedocs.io/en/latest/autogen/#loading-documents
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# Initialize the group chat between the user and two LLM agents (PM and coder)
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groupchat = autogen.GroupChat(agents=[user_proxy, coder], messages=[], max_round=12)
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manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
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# Begin the group chat with a message from the user
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user_proxy.initiate_chat(
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manager,
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message="Tell me what a virtual context in MemGPT is. Search your archival memory.",
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)
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