> ## Documentation Index
> Fetch the complete documentation index at: https://docs-preprod.sambanova.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Vision

Using SambaNova supported vision models, users can process multimodal inputs consisting of text and  images. These models understand and analyze images to then generate text based on the context. Learn how to query SambaNova vision models using OpenAI’s Python client.

## Make a query with an image

On SambaNova, the vision model request follows OpenAI’s multimodal input format which accepts both text and image inputs in a structured payload. While the call is similar to [Text Generation](/en/features/text-generation), it differs by including an encoded image file, referenced via the `image_path` variable. A helper function is used to convert this image into a base64 string, allowing it to be passed alongside the text in the request.

<Steps>
  <Step title="Step 1">
    Make a new Python file and copy the code below.;

    <Note>
      This example uses the Llama-4-Maverick-17B-128E-Instruct model.
    </Note>

    <CodeGroup>
      ```python helloWorld.py
      import openai
      import base64

      client = openai.OpenAI(
          base_url="your-sambanova-base-url",
          api_key="your-sambanova-api-key",
      )

      # Helper function to encode the image
      def encode_image(image_path):
        with open(image_path, "rb") as image_file:
          return base64.b64encode(image_file.read()).decode('utf-8')

      # The path to your image
      image_path = "sample.JPEG"

      # The base64 string of the image
      image_base64 = encode_image(image_path)

      print(image_base64)

      response = client.chat.completions.create(
          model="Llama-4-Maverick-17B-128E-Instruct",
          messages=[
              {
                  "role": "user",
                  "content": [
                      {"type": "text", "text": "What is happening in this image?"},
                      {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_base64}"}}
                  ]
              }
          ]
      )

      print(response.choices[0].message.content)
      ```
    </CodeGroup>
  </Step>

  <Step title="Step 2">
    Use your SambaNova API key and base URL from the [API keys and URLs](/en/get-started/api-keys-urls) page to replace the string fields `"your-sambanova-api-key"` and `"your-sambanova-base-url"`in the construction of the client.
  </Step>

  <Step title="Step 3">
    Select an image and move it to a suitable path that you can specify in the lines.

    ```python
    # The path to your image
    image_path = "sample.JPEG"
    ```
  </Step>

  <Step title="Step 4">
    Verify the prompt to pair with the image in the `content` portion of the `user` prompt.
  </Step>

  <Step title="Step 5">
    Run the Python file to receive the text output.
  </Step>
</Steps>