{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "load_dotenv()\n",
    "\n",
    "from azure.identity import DefaultAzureCredential, get_bearer_token_provider\n",
    "from openai import OpenAI\n",
    "\n",
    "# This sample uses the Azure OpenAI Responses API via the stable /openai/v1/ endpoint.\n",
    "# GitHub Models is deprecated (retiring July 2026) and does not support the Responses API,\n",
    "# so we call Azure OpenAI directly instead.\n",
    "endpoint = os.environ[\"AZURE_OPENAI_ENDPOINT\"]\n",
    "deployment = os.environ.get(\"AZURE_OPENAI_DEPLOYMENT\", \"gpt-4o-mini\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Authenticate with Entra ID (run `az login` first). No API version is needed with the v1 endpoint.\n",
    "token_provider = get_bearer_token_provider(\n",
    "    DefaultAzureCredential(),\n",
    "    \"https://cognitiveservices.azure.com/.default\",\n",
    ")\n",
    "\n",
    "client = OpenAI(\n",
    "    base_url=f\"{endpoint.rstrip('/')}/openai/v1/\",\n",
    "    api_key=token_provider,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "role = \"travel agent\"\n",
    "company = \"contoso travel\"\n",
    "responsibility = \"booking flights\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = client.responses.create(\n",
    "    model=deployment,\n",
    "    input=[\n",
    "        {\"role\": \"system\", \"content\": \"\"\"You are an expert at creating AI agent assistants. \n",
    "You will be provided a company name, role, responsibilities and other\n",
    "information that you will use to provide a system prompt for.\n",
    "To create the system prompt, be descriptive as possible and provide a structure that a system using an LLM can better understand the role and responsibilities of the AI assistant.\"\"\"},\n",
    "        {\"role\": \"user\", \"content\": f\"You are {role} at {company} that is responsible for {responsibility}.\"},\n",
    "    ],\n",
    "    # Optional parameters\n",
    "    temperature=1.0,\n",
    "    max_output_tokens=1000,\n",
    "    top_p=1.0,\n",
    "    store=False,\n",
    ")\n",
    "\n",
    "print(response.output_text)\n"
   ]
  }
 ],
 "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": "3.13.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}