Lab 3 - Create A Simple AI Agent.ipynb

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   "source": [
    "# Lab 2: Create a Simple AI Agent\n",
    "\n",
    "In this lab, we'll introduce you to AI agents by creating a simple agent that will create a bar graph based on data that we give to it. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 1: Load packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from typing import Any\n",
    "from pathlib import Path\n",
    "from dotenv import load_dotenv\n",
    "from azure.ai.projects import AIProjectClient\n",
    "from azure.identity import DefaultAzureCredential\n",
    "from azure.ai.projects.models import CodeInterpreterTool\n",
    "\n",
    "load_dotenv() # Load environment variables from .env file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 2: Connect to your Azure AI Foundry project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Connecting to our Azure AI Foundry project, which will allow us to use the deployed gpt-4o model\n",
    "project_connection_string = os.getenv(\"AIPROJECT_CONNECTION_STRING\")\n",
    "model = os.getenv(\"CHAT_MODEL\")\n",
    "\n",
    "project_client = AIProjectClient.from_connection_string(\n",
    "    conn_str=project_connection_string, credential=DefaultAzureCredential()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Step 3: Create the simple AI Agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with project_client:\n",
    "    # Create an instance of the CodeInterpreterTool, which is responsible for generating the bar chart\n",
    "    code_interpreter = CodeInterpreterTool()\n",
    "\n",
    "    # The CodeInterpreterTool needs to be included in creation of the agent so that it can be used\n",
    "    agent = project_client.agents.create_agent(\n",
    "        model=model,\n",
    "        name=\"my-agent-barchart\",\n",
    "        instructions=\"You are a helpful agent.\",\n",
    "        tools=code_interpreter.definitions,\n",
    "        tool_resources=code_interpreter.resources,\n",
    "    )\n",
    "    print(f\"Created agent, agent ID: {agent.id}\")\n",
    "\n",
    "    # Create a thread which is a conversation session between an agent and a user.\n",
    "    thread = project_client.agents.create_thread()\n",
    "    print(f\"Created thread, thread ID: {thread.id}\")\n",
    "\n",
    "    # Create a prompt which contains the data + details for how the agent should generate the bar chart\n",
    "    prompt = \"Could you please create a bar chart for the using the following data and \\\n",
    "        provide the file to me? Name the file as health-plan-comparision.png. \\\n",
    "        Here is the data: \\\n",
    "        Provider\t    Monthly Premium\tDeductible\tOut-of-Pocket Limit \\\n",
    "        Northwind\t    $300\t\t$1,500\t\t$6,000 \\\n",
    "        Aetna\t\t    $350\t\t$1,000\t\t$5,500 \\\n",
    "        United Health\t$250\t\t$2,000\t\t$7,000 \\\n",
    "        Premera\t\t    $200\t\t$2,200\t\t$6,500 \\\n",
    "    \"\n",
    "    \n",
    "    # Create a message, with the prompt being the message content that is sent to the model\n",
    "    message = project_client.agents.create_message(\n",
    "        thread_id=thread.id,\n",
    "        role=\"user\",\n",
    "        content=prompt,\n",
    "    )\n",
    "    print(f\"Created message, message ID: {message.id}\")\n",
    "\n",
    "    # Run the agent to process tne message in the thread\n",
    "    run = project_client.agents.create_and_process_run(thread_id=thread.id, assistant_id=agent.id)\n",
    "    print(f\"Run finished with status: {run.status}\")\n",
    "\n",
    "    if run.status == \"failed\":\n",
    "        # Check if you got \"Rate limit is exceeded.\", then you want to increase the token limit\n",
    "        print(f\"Run failed: {run.last_error}\")\n",
    "\n",
    "    # Get all messages from the thread\n",
    "    messages = project_client.agents.list_messages(thread_id=thread.id)\n",
    "    print(f\"Messages: {messages}\")\n",
    "\n",
    "    # Generate an image file for the bar chart\n",
    "    for file_path_annotation in messages.file_path_annotations:\n",
    "        file_name = Path(file_path_annotation.text).name\n",
    "        project_client.agents.save_file(file_id=file_path_annotation.file_path.file_id, file_name=file_name)\n",
    "        print(f\"Saved image file to: {Path.cwd() / file_name}\")\n",
    "\n",
    "    # Delete the agent once done\n",
    "    project_client.agents.delete_agent(agent.id)\n",
    "    print(\"Deleted agent\")"
   ]
  }
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