notebook/agentchat_oai_assistant_twoagents_basic.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# OpenAI Assistants in AutoGen\n",
    "\n",
    "This notebook shows a very basic example of the [`GPTAssistantAgent`](https://github.com/autogenhub/autogen/blob/main/autogen/agentchat/contrib/gpt_assistant_agent.py), 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": {
  "front_matter": {
   "description": "Two-agent chat with OpenAI assistants.",
   "tags": [
    "OpenAI Assistant"
   ]
  },
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