{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b7388610",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ! pip install -r ../../../Installation/requirements.txt -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b4f4d0c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import asyncio\n",
    "from random import randint\n",
    "from typing import Annotated\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "from agent_framework import Agent\n",
    "from agent_framework.foundry import FoundryChatClient\n",
    "from azure.identity.aio import AzureCliCredential\n",
    "from pydantic import Field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8797600a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bc790a5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "client = FoundryChatClient(credential=AzureCliCredential())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "afd1618d",
   "metadata": {},
   "outputs": [],
   "source": [
    "agent = Agent(\n",
    "        client=client,\n",
    "        name = \"FoundryAgent\",\n",
    "        instructions=\"Write a haiku about Agent Framework\",\n",
    ")\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "91d210ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = \"Write a haiku about Agent Framework.\"\n",
    "response = await agent.run(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2651d7de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Silent agents weave  \\nFrameworks guide their restless thoughts  \\nTasks bloom into form'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response.text"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "agentdev",
   "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": "3.12.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}