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Python class

OutputImageContent

OutputImageContent

class max.pipelines.request.OutputImageContent(*, type='output_image', image_url=None, image_data=None, format=None, detail=None)

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Bases: BaseModel

Image content generated by the model in output messages.

Parameters:

• type (Literal['output_image'])
• image_url (str | None)
• image_data (str | None)
• format (str | None)
• detail (ImageDetail | None)

detail

detail: ImageDetail | None

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format

format: str | None

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from_numpy()

classmethod from_numpy(array, format='png', detail=None)

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Create an OutputImageContent from a numpy array.

Converts a numpy array containing image data to base64-encoded format suitable for the OpenResponses API.

For example, create a simple red image and encode it as PNG:

import numpy as np

from max.pipelines.request.open_responses import OutputImageContent

img_array = np.zeros((100, 100, 3), dtype=np.uint8)
img_array[:, :, 0] = 255  # Set red channel to max
output = OutputImageContent.from_numpy(img_array, format="png")

Parameters:

• array (ndarray[tuple[Any, ...], dtype[uint8]]) – A uint8 numpy array with values in [0, 255]. Expected shapes:
  • [H, W, C] for color images (C=3 for RGB, C=4 for RGBA)
  • [H, W] for grayscale images
• format (str) – The image format to use for encoding (such as "png", "jpeg", or "webp"). Defaults to "png".
• detail (ImageDetail | None) – Optional detail level for the generated image.

Returns:

An OutputImageContent instance with base64-encoded image data.

Raises:

• ImportError – If PIL/Pillow is not available.
• ValueError – If the array shape or dtype is invalid.

Return type:

OutputImageContent

image_data

image_data: str | None

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image_url

image_url: str | None

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model_config

model_config: ClassVar[ConfigDict] = {'frozen': True}

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Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

type

type: Literal['output_image']

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