diff --git a/docs/getting_started.ipynb b/docs/getting_started.ipynb
index 96e39eb82..abe537c8e 100644
--- a/docs/getting_started.ipynb
+++ b/docs/getting_started.ipynb
@@ -3396,6 +3396,231 @@
         "response = client.scoring.score(input_rows=rows, scoring_functions=scoring_params)\n",
         "pprint(response)\n"
       ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "ad077440",
+      "metadata": {},
+      "source": [
+        "## 4. Image Understanding with Llama 3.2\n",
+        "\n",
+        "Below is a complete example of using Together's Llama Stack 0.1 server at https://llama-stack.together.ai to ask Llama 3.2 questions about an image."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "82e381ec",
+      "metadata": {},
+      "source": [
+        "### 4.1 Setup and helpers\n",
+        "\n",
+        "Below we install the Llama Stack client 0.1, download the example image, define two image helpers, and set Llama Stack Together server URL and Llama 3.2 model name.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "865fc5a8",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "!pip install llama-stack-client==0.1.0"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "44e05e16",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "!wget https://raw.githubusercontent.com/meta-llama/llama-models/refs/heads/main/Llama_Repo.jpeg"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "469750f7",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from PIL import Image\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "def display_image(path):\n",
+        "  img = Image.open(path)\n",
+        "  plt.imshow(img)\n",
+        "  plt.axis('off')\n",
+        "  plt.show()\n",
+        "\n",
+        "display_image(\"Llama_Repo.jpeg\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "a2c1e1c2",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import base64\n",
+        "\n",
+        "def encode_image(image_path):\n",
+        "    with open(image_path, \"rb\") as image_file:\n",
+        "        base64_string = base64.b64encode(image_file.read()).decode(\"utf-8\")\n",
+        "        base64_url = f\"data:image/png;base64,{base64_string}\"\n",
+        "        return base64_url"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "c565f99e",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from llama_stack_client import LlamaStackClient\n",
+        "\n",
+        "LLAMA_STACK_API_TOGETHER_URL=\"https://llama-stack.together.ai\"\n",
+        "LLAMA32_11B_INSTRUCT = \"meta-llama/Llama-3.2-11B-Vision-Instruct\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "7737cd41",
+      "metadata": {},
+      "source": [
+        "### 4.2 Using Llama Stack Chat API\n",
+        "\n",
+        "The code below uses the Llama Stack 0.1's chat API to interact with Llama 3.2:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "d7914894",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from llama_stack_client.lib.inference.event_logger import EventLogger\n",
+        "\n",
+        "async def run_main(image_path: str, prompt):\n",
+        "    client = LlamaStackClient(\n",
+        "        base_url=LLAMA_STACK_API_TOGETHER_URL,\n",
+        "    )\n",
+        "\n",
+        "    message = {\n",
+        "        \"role\": \"user\",\n",
+        "        \"content\": [\n",
+        "            {\n",
+        "                \"type\": \"image\",\n",
+        "                \"image\": {\n",
+        "                     \"url\": {\n",
+        "                          \"uri\": encode_image(image_path)\n",
+        "                     }\n",
+        "                }\n",
+        "            },\n",
+        "            {\n",
+        "                \"type\": \"text\",\n",
+        "                \"text\": prompt,\n",
+        "            }\n",
+        "        ]\n",
+        "    }\n",
+        "\n",
+        "    response = client.inference.chat_completion(\n",
+        "        messages=[message],\n",
+        "        model_id=LLAMA32_11B_INSTRUCT,\n",
+        "        stream=False,\n",
+        "    )\n",
+        "\n",
+        "    print(response.completion_message.content.lower().strip())"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "4ee09b97",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "await run_main(\"Llama_Repo.jpeg\",\n",
+        "     \"How many different colors are those llamas?\\\n",
+        "     What are those colors?\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "e741d7b9",
+      "metadata": {},
+      "source": [
+        "### 4.3 Using Llama Stack Agent API\n",
+        "\n",
+        "The code below uses the Llama Stack 0.1's Agent API to interact with Llama 3.2:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "f9a83275",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from llama_stack_client.lib.agents.agent import Agent\n",
+        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
+        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
+        "\n",
+        "async def run_main(image_path, prompt):\n",
+        "    base64_image = encode_image(image_path)\n",
+        "\n",
+        "    client = LlamaStackClient(\n",
+        "        base_url=LLAMA_STACK_API_TOGETHER_URL,\n",
+        "    )\n",
+        "\n",
+        "    agent_config = AgentConfig(\n",
+        "        model=LLAMA32_11B_INSTRUCT,\n",
+        "        instructions=\"You are a helpful assistant\",\n",
+        "        enable_session_persistence=False,\n",
+        "    )\n",
+        "\n",
+        "    agent = Agent(client, agent_config)\n",
+        "    session_id = agent.create_session(\"test-session\")\n",
+        "\n",
+        "    response = agent.create_turn(\n",
+        "        messages=[{\n",
+        "            \"role\": \"user\",\n",
+        "            \"content\": [\n",
+        "                {\n",
+        "                    \"type\": \"image\",\n",
+        "                    \"image\": {\n",
+        "                         \"url\": {\n",
+        "                              \"uri\": encode_image(image_path)\n",
+        "                         }\n",
+        "                    }\n",
+        "                },\n",
+        "                {\n",
+        "                    \"type\": \"text\",\n",
+        "                    \"text\": prompt,\n",
+        "                }\n",
+        "            ]\n",
+        "        }],\n",
+        "        session_id=session_id,\n",
+        "    )\n",
+        "\n",
+        "    for log in EventLogger().log(response):\n",
+        "        log.print()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "15d0098b",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "await run_main(\"Llama_Repo.jpeg\",\n",
+        "         \"How many different colors are those llamas?\\\n",
+        "         What are those colors?\")"
+      ]
     }
   ],
   "metadata": {