{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## OpenAI Assistants in AutoGen\n", "\n", "This notebook shows a very basic example of the [`GPTAssistantAgent`](https://github.com/microsoft/autogen/blob/main/autogen/agentchat/contrib/gpt_assistant_agent.py#L16C43-L16C43), which is an experimental AutoGen agent class that leverages the [OpenAI Assistant API](https://platform.openai.com/docs/assistants/overview) for conversational capabilities, working with\n", "`UserProxyAgent` in AutoGen." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "OpenAI client config of GPTAssistantAgent(assistant) - model: gpt-4-turbo-preview\n", "GPT Assistant only supports one OpenAI client. Using the first client in the list.\n", "No matching assistant found, creating a new assistant\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33muser_proxy\u001b[0m (to assistant):\n", "\n", "Print hello world\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33massistant\u001b[0m (to user_proxy):\n", "\n", "```python\n", "print(\"Hello, world!\")\n", "```\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n", "\u001b[33muser_proxy\u001b[0m (to assistant):\n", "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", "Hello, world!\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33massistant\u001b[0m (to user_proxy):\n", "\n", "TERMINATE\n", "\n", "\n", "--------------------------------------------------------------------------------\n" ] }, { "data": { "text/plain": [ "ChatResult(chat_id=None, chat_history=[{'content': 'Print hello world', 'role': 'assistant'}, {'content': '```python\\nprint(\"Hello, world!\")\\n```\\n', 'role': 'user'}, {'content': 'exitcode: 0 (execution succeeded)\\nCode output: \\nHello, world!\\n', 'role': 'assistant'}, {'content': 'TERMINATE\\n', 'role': 'user'}], summary='\\n', cost=({'total_cost': 0}, {'total_cost': 0}), human_input=[])" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import logging\n", "import os\n", "\n", "from autogen import AssistantAgent, UserProxyAgent, config_list_from_json\n", "from autogen.agentchat.contrib.gpt_assistant_agent import GPTAssistantAgent\n", "\n", "logger = logging.getLogger(__name__)\n", "logger.setLevel(logging.WARNING)\n", "\n", "assistant_id = os.environ.get(\"ASSISTANT_ID\", None)\n", "\n", "config_list = config_list_from_json(\"OAI_CONFIG_LIST\")\n", "llm_config = {\"config_list\": config_list}\n", "\n", "assistant_config = {\"assistant_id\": assistant_id}\n", "\n", "gpt_assistant = GPTAssistantAgent(\n", " name=\"assistant\",\n", " instructions=AssistantAgent.DEFAULT_SYSTEM_MESSAGE,\n", " llm_config=llm_config,\n", " assistant_config=assistant_config,\n", ")\n", "\n", "user_proxy = UserProxyAgent(\n", " name=\"user_proxy\",\n", " code_execution_config={\n", " \"work_dir\": \"coding\",\n", " \"use_docker\": False,\n", " }, # Please set use_docker=True if docker is available to run the generated code. Using docker is safer than running the generated code directly.\n", " is_termination_msg=lambda msg: \"TERMINATE\" in msg[\"content\"],\n", " human_input_mode=\"NEVER\",\n", " max_consecutive_auto_reply=1,\n", ")\n", "user_proxy.initiate_chat(gpt_assistant, message=\"Print hello world\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33muser_proxy\u001b[0m (to assistant):\n", "\n", "Write py code to eval 2 + 2\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33massistant\u001b[0m (to user_proxy):\n", "\n", "```python\n", "# Calculate 2+2 and print the result\n", "result = 2 + 2\n", "print(result)\n", "```\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n", "\u001b[33muser_proxy\u001b[0m (to assistant):\n", "\n", "exitcode: 0 (execution succeeded)\n", "Code output: \n", "4\n", "\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33massistant\u001b[0m (to user_proxy):\n", "\n", "The Python code successfully calculated \\(2 + 2\\) and printed the result, which is \\(4\\).\n", "\n", "TERMINATE\n", "\n", "\n", "--------------------------------------------------------------------------------\n" ] }, { "data": { "text/plain": [ "ChatResult(chat_id=None, chat_history=[{'content': 'Write py code to eval 2 + 2', 'role': 'assistant'}, {'content': '```python\\n# Calculate 2+2 and print the result\\nresult = 2 + 2\\nprint(result)\\n```\\n', 'role': 'user'}, {'content': 'exitcode: 0 (execution succeeded)\\nCode output: \\n4\\n', 'role': 'assistant'}, {'content': 'The Python code successfully calculated \\\\(2 + 2\\\\) and printed the result, which is \\\\(4\\\\).\\n\\nTERMINATE\\n', 'role': 'user'}], summary='The Python code successfully calculated \\\\(2 + 2\\\\) and printed the result, which is \\\\(4\\\\).\\n\\n\\n', cost=({'total_cost': 0}, {'total_cost': 0}), human_input=[])" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "user_proxy.initiate_chat(gpt_assistant, message=\"Write py code to eval 2 + 2\", clear_history=True)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Permanently deleting assistant...\n" ] } ], "source": [ "gpt_assistant.delete_assistant()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.10.13" } }, "nbformat": 4, "nbformat_minor": 2 }