"# Auto Generated Agent Chat: GPTAssistant with Code Interpreter\n",
"The latest released Assistants API by OpenAI allows users to build AI assistants within their own applications. The Assistants API currently supports three types of tools: Code Interpreter, Retrieval, and Function calling. In this notebook, we demonstrate how to enable `GPTAssistantAgent` to use code interpreter. \n",
"\n",
"## Requirements\n",
"\n",
"AutoGen requires `Python>=3.8`. To run this notebook example, please install:\n",
"```bash\n",
"pip install pyautogen\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set your API Endpoint\n",
"\n",
"The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file."
"It first looks for environment variable \"OAI_CONFIG_LIST\" which needs to be a valid json string. If that variable is not found, it then looks for a json file named \"OAI_CONFIG_LIST\". It filters the configs by models (you can filter by other keys as well).\n",
"Currently Azure OpenAi does not support assistant api. You can set the value of config_list in any way you prefer. Please refer to this [notebook](https://github.com/microsoft/autogen/blob/main/website/docs/llm_endpoint_configuration.ipynb) for full code examples of the different methods."
"We demonstrate task solving using `GPTAssistantAgent` with code interpreter. Pass `code_interpreter` in `tools` parameter to enable `GPTAssistantAgent` with code interpreter. It will write code and automatically execute it in a sandbox. The agent will receive the results from the sandbox environment and act accordingly.\n",
"\n",
"### Example 1: Math Problem Solving\n",
"In this example, we demonstrate how to use code interpreter to solve math problems.\n"
"OpenAI client config of GPTAssistantAgent(Coder Assistant) - model: gpt-4-turbo\n",
"Matching assistant found, using the first matching assistant: {'id': 'asst_xBMxObFj0TzDex04NAKbBCmP', 'created_at': 1710321320, 'description': None, 'file_ids': [], 'instructions': 'You are an expert at solving math questions. Write code and run it to solve math problems. Reply TERMINATE when the task is solved and there is no problem.', 'metadata': {}, 'model': 'gpt-4-turbo', 'name': 'Coder Assistant', 'object': 'assistant', 'tools': [ToolCodeInterpreter(type='code_interpreter')]}\n"
" instructions=\"You are an expert at solving math questions. Write code and run it to solve math problems. Reply TERMINATE when the task is solved and there is no problem.\",\n",
")\n",
"\n",
"user_proxy = UserProxyAgent(\n",
" name=\"user_proxy\",\n",
" is_termination_msg=lambda msg: \"TERMINATE\" in msg[\"content\"],\n",
" \"use_docker\": False, # 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",
"To draw a line chart showing the population trend in the US, we first need to obtain the data that contains the population figures over a range of years. As I don't have access to the internet in this environment, I cannot download the data directly. However, if you can provide the data, I can proceed to create a line chart for you.\n",
"For the purpose of this demonstration, let's assume we have some hypothetical US population data for a few years. I'll generate some sample data and create a line chart using the `matplotlib` library in Python.\n",
"Here is a line chart that illustrates the hypothetical US population trend from 2010 to 2020. The data used here is for demonstration purposes only. If you have actual population data, you can provide it, and I will update the chart accordingly.\n",
"ChatResult(chat_id=None, chat_history=[{'content': 'Draw a line chart to show the population trend in US. Show how you solved it with code.', 'role': 'assistant'}, {'content': \"To draw a line chart showing the population trend in the US, we first need to obtain the data that contains the population figures over a range of years. As I don't have access to the internet in this environment, I cannot download the data directly. However, if you can provide the data, I can proceed to create a line chart for you.\\n\\nFor the purpose of this demonstration, let's assume we have some hypothetical US population data for a few years. I'll generate some sample data and create a line chart using the `matplotlib` library in Python.\\n\\nHere's how we can do it:\\n\\n\\nReceived file id=assistant-tvLtfOn6uAJ9kxmnxgK2OXID\\n\\nHere is a line chart that illustrates the hypothetical US population trend from 2010 to 2020. The data used here is for demonstration purposes only. If you have actual population data, you can provide it, and I will update the chart accordingly.\\n\\nTERMINATE\\n\", 'role': 'user'}], summary=\"To draw a line chart showing the population trend in the US, we first need to obtain the data that contains the population figures over a range of years. As I don't have access to the internet in this environment, I cannot download the data directly. However, if you can provide the data, I can proceed to create a line chart for you.\\n\\nFor the purpose of this demonstration, let's assume we have some hypothetical US population data for a few years. I'll generate some sample data and create a line chart using the `matplotlib` library in Python.\\n\\nHere's how we can do it:\\n\\n\\nReceived file id=assistant-tvLtfOn6uAJ9kxmnxgK2OXID\\n\\nHere is a line chart that illustrates the hypothetical US population trend from 2010 to 2020. The data used here is for demonstration purposes only. If you have actual population data, you can provide it, and I will update the chart accordingly.\\n\\n\\n\", cost=({'total_cost': 0}, {'total_cost': 0}), human_input=[])"
