{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Quickstart" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Via AgentChat, you can build applications quickly using preset agents.\n", "To illustrate this, we will begin with creating a single tool-use agent." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "vscode": { "languageId": "shellscript" } }, "outputs": [], "source": [ "pip install -U \"autogen-ext[openai,azure]\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To use Azure OpenAI models and AAD authentication,\n", "you can follow the instructions [here](./tutorial/models.ipynb#azure-openai).\n", "\n", "To use other models, see [Models](./tutorial/models.ipynb)." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "---------- user ----------\n", "What is the weather in New York?\n", "---------- weather_agent ----------\n", "[FunctionCall(id='call_ciy1Ecys9LH201cyim10xlnQ', arguments='{\"city\":\"New York\"}', name='get_weather')]\n", "---------- weather_agent ----------\n", "[FunctionExecutionResult(content='The weather in New York is 73 degrees and Sunny.', call_id='call_ciy1Ecys9LH201cyim10xlnQ')]\n", "---------- weather_agent ----------\n", "The weather in New York is currently 73 degrees and sunny.\n" ] } ], "source": [ "from autogen_agentchat.agents import AssistantAgent\n", "from autogen_agentchat.ui import Console\n", "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", "\n", "\n", "# Define a tool\n", "async def get_weather(city: str) -> str:\n", " \"\"\"Get the weather for a given city.\"\"\"\n", " return f\"The weather in {city} is 73 degrees and Sunny.\"\n", "\n", "\n", "async def main() -> None:\n", " agent = AssistantAgent(\n", " name=\"weather_agent\",\n", " model_client=OpenAIChatCompletionClient(\n", " model=\"gpt-4o\",\n", " # api_key=\"YOUR_API_KEY\",\n", " ),\n", " tools=[get_weather],\n", " system_message=\"You are a helpful assistant.\",\n", " reflect_on_tool_use=True,\n", " )\n", " await Console(agent.run_stream(task=\"What is the weather in New York?\"))\n", "\n", "\n", "# NOTE: if running this inside a Python script you'll need to use asyncio.run(main()).\n", "await main()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What's Next?\n", "\n", "Now that you have a basic understanding of how to define an agent, consider following the [tutorial](./tutorial/models) for a walkthrough on other features of AgentChat." ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 2 }