MemGPT/memgpt/autogen/examples/memgpt_coder_autogen.ipynb
Charles Packer ec7fa25c07
Update AutoGen documentation and notebook example (#540)
* Update AutoGen documentation

* Update webui.md

* Update webui.md

* Update lmstudio.md

* Update lmstudio.md

* Update mkdocs.yml

* Update README.md

* Update README.md

* Update README.md

* Update autogen.md

* Update local_llm.md

* Update local_llm.md

* Update autogen.md

* Update autogen.md

* Update autogen.md

* refreshed the autogen examples + notebook (notebook is untested)

* unrelated patch of typo I noticed

* poetry remove pyautogen, then manually removed autogen extra in .toml

* add pdf dependency

---------

Co-authored-by: Sarah Wooders <sarahwooders@gmail.com>
2023-11-30 17:45:04 -08:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "591be0c0-7332-4c57-adcf-fecc578eeb67",
"metadata": {
"id": "591be0c0-7332-4c57-adcf-fecc578eeb67"
},
"source": [
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/cpacker/MemGPT/blob/main/memgpt/autogen/examples/memgpt_coder_autogen.ipynb\">\n",
" <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "43d71a67-3a01-4543-99ad-7dce12d793da",
"metadata": {
"id": "43d71a67-3a01-4543-99ad-7dce12d793da"
},
"outputs": [],
"source": [
"%pip install pyautogen"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b3754942-819b-4df9-be3f-6cfb3ca101dc",
"metadata": {
"id": "b3754942-819b-4df9-be3f-6cfb3ca101dc"
},
"outputs": [],
"source": [
"%pip install pymemgpt"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bd6df0ac-66a6-4dc7-9262-4c2ad05fab91",
"metadata": {
"id": "bd6df0ac-66a6-4dc7-9262-4c2ad05fab91"
},
"outputs": [],
"source": [
"# You can get an OpenAI API key at https://platform.openai.com\n",
"OPENAI_API_KEY = \"YOUR_API_KEY\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0cb9b18c-3662-4206-9ff5-de51a3aafb36",
"metadata": {
"id": "0cb9b18c-3662-4206-9ff5-de51a3aafb36"
},
"outputs": [],
"source": [
"\"\"\"Example of how to add MemGPT into an AutoGen groupchat\n",
"\n",
"Based on the official AutoGen example here: https://github.com/microsoft/autogen/blob/main/notebook/agentchat_groupchat.ipynb\n",
"\"\"\"\n",
"\n",
"import autogen\n",
"from memgpt.autogen.memgpt_agent import create_memgpt_autogen_agent_from_config\n",
"\n",
"\n",
"# This config is for AutoGen agents that are not powered by MemGPT\n",
"config_list = [\n",
" {\n",
" \"model\": \"gpt-4\",\n",
" \"api_key\": OPENAI_API_KEY,\n",
" },\n",
"]\n",
"llm_config = {\"config_list\": config_list, \"seed\": 42}\n",
"\n",
"\n",
"# This config is for AutoGen agents that powered by MemGPT\n",
"config_list_memgpt = [\n",
" {\n",
" \"model\": \"gpt-4\",\n",
" \"preset\": \"memgpt_chat\",\n",
" \"model_wrapper\": None,\n",
" \"model_endpoint_type\": \"openai\",\n",
" \"model_endpoint\": \"https://api.openai.com/v1\",\n",
" \"context_window\": 8192, # gpt-4 context window\n",
" },\n",
"]\n",
"llm_config_memgpt = {\"config_list\": config_list_memgpt, \"seed\": 42}"
]
},
{
"cell_type": "code",
"source": [
"# The user agent\n",
"user_proxy = autogen.UserProxyAgent(\n",
" name=\"User_proxy\",\n",
" system_message=\"A human admin.\",\n",
" code_execution_config={\"last_n_messages\": 2, \"work_dir\": \"groupchat\"},\n",
" human_input_mode=\"TERMINATE\", # needed?\n",
" default_auto_reply=\"...\", # Set a default auto-reply message here\n",
")\n",
"\n",
"# The agent playing the role of the product manager (PM)\n",
"# Let's make this a non-MemGPT agent\n",
"pm = autogen.AssistantAgent(\n",
" name=\"Product_manager\",\n",
" system_message=\"Creative in software product ideas.\",\n",
" llm_config=llm_config,\n",
" default_auto_reply=\"...\", # Set a default auto-reply message here\n",
")\n",
"\n",
"# If USE_MEMGPT is False, then this example will be the same as the official AutoGen repo (https://github.com/microsoft/autogen/blob/main/notebook/agentchat_groupchat.ipynb)\n",
"# If USE_MEMGPT is True, then we swap out the \"coder\" agent with a MemGPT agent\n",
"USE_MEMGPT = True\n",
"\n",
"if not USE_MEMGPT:\n",
" # In the AutoGen example, we create an AssistantAgent to play the role of the coder\n",
" coder = autogen.AssistantAgent(\n",
" name=\"Coder\",\n",
" llm_config=llm_config,\n",
" )\n",
"\n",
"else:\n",
" # In our example, we swap this AutoGen agent with a MemGPT agent\n",
" # This MemGPT agent will have all the benefits of MemGPT, ie persistent memory, etc.\n",
"\n",
" # We can use interface_kwargs to control what MemGPT outputs are seen by the groupchat\n",
" interface_kwargs = {\n",
" \"debug\": False,\n",
" \"show_inner_thoughts\": True,\n",
" \"show_function_outputs\": False,\n",
" }\n",
"\n",
" coder = create_memgpt_autogen_agent_from_config(\n",
" \"MemGPT_coder\",\n",
" llm_config=llm_config_memgpt,\n",
" system_message=f\"I am a 10x engineer, trained in Python. I was the first engineer at Uber \"\n",
" f\"(which I make sure to tell everyone I work with).\\n\"\n",
" f\"You are participating in a group chat with a user ({user_proxy.name}) \"\n",
" f\"and a product manager ({pm.name}).\",\n",
" interface_kwargs=interface_kwargs,\n",
" default_auto_reply=\"...\", # Set a default auto-reply message here (non-empty auto-reply is required for LM Studio)\n",
" )"
],
"metadata": {
"id": "flVCXXKirZ-c"
},
"id": "flVCXXKirZ-c",
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Initialize the group chat between the user and two LLM agents (PM and coder)\n",
"groupchat = autogen.GroupChat(agents=[user_proxy, pm, coder], messages=[], max_round=12)\n",
"manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)\n",
"\n",
"# Begin the group chat with a message from the user\n",
"user_proxy.initiate_chat(\n",
" manager,\n",
" message=\"I want to design an app to make me one million dollars in one month. Yes, your heard that right.\",\n",
")"
],
"metadata": {
"id": "GvLSBuEhreO1"
},
"id": "GvLSBuEhreO1",
"execution_count": null,
"outputs": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.6"
},
"colab": {
"provenance": []
}
},
"nbformat": 4,
"nbformat_minor": 5
}