autogen/notebook/agentchat_oai_assistant_twoagents_basic.ipynb
olgavrou a911d1c2ec
set use_docker to default to True (#1147)
* set use_docker to default to true

* black formatting

* centralize checking and add env variable option

* set docker env flag for contrib tests

* set docker env flag for contrib tests

* better error message and cleanup

* disable explicit docker tests

* docker is installed so can't check for that in test

* pr comments and fix test

* rename and fix function descriptions

* documentation

* update notebooks so that they can be run with change in default

* add unit tests for new code

* cache and restore env var

* skip on windows because docker is running in the CI but there are problems connecting the volume

* update documentation

* move header

* update contrib tests
2024-01-18 17:03:49 +00:00

213 lines
6.4 KiB
Plaintext

{
"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": [
"assistant_id was None, 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",
"Please run this Python code to print \"Hello, World!\" to the console.\n",
"\n",
"\n",
"--------------------------------------------------------------------------------\n",
"\u001b[31m\n",
">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"execute_code was called without specifying a value for use_docker. Since the python docker package is not available, code will be run natively. Note: this fallback behavior is subject to change\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\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",
"The code executed successfully and printed \"Hello, World!\" as expected.\n",
"\n",
"TERMINATE\n",
"\n",
"\n",
"--------------------------------------------------------------------------------\n"
]
}
],
"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, \"assistant_id\": assistant_id}\n",
"\n",
"gpt_assistant = GPTAssistantAgent(\n",
" name=\"assistant\", instructions=AssistantAgent.DEFAULT_SYSTEM_MESSAGE, llm_config=llm_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",
"# Let's write a simple Python code to evaluate 2 + 2 and print the result.\n",
"\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"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"execute_code was called without specifying a value for use_docker. Since the python docker package is not available, code will be run natively. Note: this fallback behavior is subject to change\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\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 was executed successfully and the result of evaluating 2 + 2 is 4.\n",
"\n",
"TERMINATE\n",
"\n",
"\n",
"--------------------------------------------------------------------------------\n"
]
}
],
"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": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}