{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Quickstart"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "```{include} warning.md\n",
                "\n",
                "```\n",
                "\n",
                ":::{note}\n",
                "For installation instructions, please refer to the [installation guide](./installation).\n",
                ":::\n",
                "\n",
                "In AutoGen AgentChat, you can build applications quickly using preset agents.\n",
                "To illustrate this, we will begin with creating a team of a single agent\n",
                "that can use tools and respond to messages.\n",
                "\n",
                "The following code uses the OpenAI model. If you haven't already, you need to\n",
                "install the following package and extension:"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "vscode": {
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            "outputs": [],
            "source": [
                "pip install 'autogen-agentchat==0.4.0.dev6' 'autogen-ext[openai]==0.4.0.dev6'"
            ]
        },
        {
            "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)."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "---------- user ----------\n",
                        "What is the weather in New York?\n",
                        "---------- weather_agent ----------\n",
                        "[FunctionCall(id='call_AhTZ2q3TNL8x0qs00e3wIZ7y', arguments='{\"city\":\"New York\"}', name='get_weather')]\n",
                        "[Prompt tokens: 79, Completion tokens: 15]\n",
                        "---------- weather_agent ----------\n",
                        "[FunctionExecutionResult(content='The weather in New York is 73 degrees and Sunny.', call_id='call_AhTZ2q3TNL8x0qs00e3wIZ7y')]\n",
                        "---------- weather_agent ----------\n",
                        "The weather in New York is currently 73 degrees and sunny.\n",
                        "[Prompt tokens: 90, Completion tokens: 14]\n",
                        "---------- weather_agent ----------\n",
                        "TERMINATE\n",
                        "[Prompt tokens: 137, Completion tokens: 4]\n",
                        "---------- Summary ----------\n",
                        "Number of messages: 5\n",
                        "Finish reason: Text 'TERMINATE' mentioned\n",
                        "Total prompt tokens: 306\n",
                        "Total completion tokens: 33\n",
                        "Duration: 1.43 seconds\n"
                    ]
                }
            ],
            "source": [
                "from autogen_agentchat.agents import AssistantAgent\n",
                "from autogen_agentchat.task import Console, TextMentionTermination\n",
                "from autogen_agentchat.teams import RoundRobinGroupChat\n",
                "from autogen_ext.models import OpenAIChatCompletionClient\n",
                "\n",
                "\n",
                "# Define a tool\n",
                "async def get_weather(city: str) -> str:\n",
                "    return f\"The weather in {city} is 73 degrees and Sunny.\"\n",
                "\n",
                "\n",
                "async def main() -> None:\n",
                "    # Define an agent\n",
                "    weather_agent = AssistantAgent(\n",
                "        name=\"weather_agent\",\n",
                "        model_client=OpenAIChatCompletionClient(\n",
                "            model=\"gpt-4o-2024-08-06\",\n",
                "            # api_key=\"YOUR_API_KEY\",\n",
                "        ),\n",
                "        tools=[get_weather],\n",
                "    )\n",
                "\n",
                "    # Define termination condition\n",
                "    termination = TextMentionTermination(\"TERMINATE\")\n",
                "\n",
                "    # Define a team\n",
                "    agent_team = RoundRobinGroupChat([weather_agent], termination_condition=termination)\n",
                "\n",
                "    # Run the team and stream messages to the console\n",
                "    stream = agent_team.run_stream(task=\"What is the weather in New York?\")\n",
                "    await Console(stream)\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": [
                "The code snippet above introduces two high level concepts in AgentChat: *Agent* and *Team*.  An Agent helps us define what actions are taken when a message is received. Specifically, we use the {py:class}`~autogen_agentchat.agents.AssistantAgent` preset - an agent that can be given access to a model (e.g., LLM) and tools (functions) that it can then use to address tasks.  A Team helps us define the rules for how agents interact with each other.  In the  {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` team, agents respond in a sequential round-robin fashion.\n",
                "In this case, we have a single agent, so the same agent is used for each round."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## What's Next?\n",
                "\n",
                "Now that you have a basic understanding of how to define an agent and a team, consider following the [tutorial](./tutorial/index) for a walkthrough on other features of AgentChat.\n",
                "\n"
            ]
        }
    ],
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