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prefect_openai.image

Module for generating and configuring OpenAI images.

Classes

ImageModel

Bases: Block

A block that contains config for an OpenAI Image Model. Learn more in the OpenAPI Image generation docs

Attributes:

Name Type Description
openai_credentials OpenAICredentials

The credentials used to authenticate with OpenAI.
size Literal['256x256', '512x512', '1024x1024']

The size of the image to generate.
n int

The number of images to generate.
response_format Literal['url', 'b64_json']

The format of the image to generate.
Example

Load a configured block: 

from prefect_openai import ImageModel

image_model = ImageModel.load("BLOCK_NAME")

Source code in prefect_openai/image.py 
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class ImageModel(Block):
    """
    A block that contains config for an OpenAI Image Model.
    Learn more in the [OpenAPI Image generation docs](
        https://beta.openai.com/docs/guides/images)

    Attributes:
        openai_credentials: The credentials used to authenticate with OpenAI.
        size: The size of the image to generate.
        n: The number of images to generate.
        response_format: The format of the image to generate.

    Example:
        Load a configured block:
        ```python
        from prefect_openai import ImageModel

        image_model = ImageModel.load("BLOCK_NAME")
        ```
    """

    openai_credentials: OpenAICredentials = Field(
        default=..., description="The credentials used to authenticate with OpenAI."
    )
    size: Literal["256x256", "512x512", "1024x1024"] = Field(
        default="256x256", description="The size of the image to generate."
    )
    n: int = Field(
        default=1,
        title="Number of images",
        description="The number of images to generate.",
    )
    response_format: Literal["url", "b64_json"] = Field(
        default="url", description="The format of the image to generate."
    )

    _block_type_name = "OpenAI Image Model"
    _logo_url = "https://cdn.sanity.io/images/3ugk85nk/production/760539393a7dbf93a143fb01c2a8b0fe7157a8d8-247x250.png"  # noqa

    @property
    def logger(self) -> Logger:
        """
        Returns a logger based on whether the ImageModel
        is called from within a flow or task run context.
        If a run context is present, the logger property returns a run logger.
        Else, it returns a default logger labeled with the class's name.

        Returns:
            The run logger or a default logger with the class's name.
        """
        try:
            return get_run_logger()
        except MissingContextError:
            return get_logger(self.__class__.__name__)

    @sync_compatible
    async def submit_prompt(
        self, prompt: str, **acreate_kwargs: Dict[str, Any]
    ) -> OpenAIObject:
        """
        Submits a prompt for the model to generate an image.
        Learn more in the [OpenAPI Image generation docs](
            https://beta.openai.com/docs/guides/images)

        Args:
            prompt: The prompt to use for the image.
            **acreate_kwargs: Additional keyword arguments to pass
                to [`openai.Image.acreate`](
                https://beta.openai.com/docs/api-reference/images/create).

        Returns:
            The OpenAIObject containing the image and associated metadata.

        Example:
            Create an OpenAI Image given a prompt:
            ```python
            from prefect_openai import ImageModel

            image_model = ImageModel.load("BLOCK_NAME")
            image_model.submit_prompt(prompt="A prompt for an image.")
            ```
        """
        client = self.openai_credentials.get_client()

        input_kwargs = dict(
            size=self.size,
            n=self.n,
            response_format=self.response_format,
        )
        input_kwargs.update(acreate_kwargs)
        creation = await client.Image.acreate(prompt=prompt, **input_kwargs)
        self.logger.info(
            f"Finished image completion, creating " f"{self.n} {self.size!r} image(s)."
        )
        return creation

Attributes

logger: Logger property

Returns a logger based on whether the ImageModel is called from within a flow or task run context. If a run context is present, the logger property returns a run logger. Else, it returns a default logger labeled with the class's name.

Returns:

Type Description
Logger

The run logger or a default logger with the class's name.

Functions

submit_prompt async

Submits a prompt for the model to generate an image. Learn more in the OpenAPI Image generation docs

Parameters:

Name Type Description Default
prompt str

The prompt to use for the image.

 required
**acreate_kwargs Dict[str, Any]

Additional keyword arguments to pass to openai.Image.acreate.

 {}

Returns:

Type Description
OpenAIObject

The OpenAIObject containing the image and associated metadata.
Example

Create an OpenAI Image given a prompt: 

from prefect_openai import ImageModel

image_model = ImageModel.load("BLOCK_NAME")
image_model.submit_prompt(prompt="A prompt for an image.")

Source code in prefect_openai/image.py 
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@sync_compatible
async def submit_prompt(
    self, prompt: str, **acreate_kwargs: Dict[str, Any]
) -> OpenAIObject:
    """
    Submits a prompt for the model to generate an image.
    Learn more in the [OpenAPI Image generation docs](
        https://beta.openai.com/docs/guides/images)

    Args:
        prompt: The prompt to use for the image.
        **acreate_kwargs: Additional keyword arguments to pass
            to [`openai.Image.acreate`](
            https://beta.openai.com/docs/api-reference/images/create).

    Returns:
        The OpenAIObject containing the image and associated metadata.

    Example:
        Create an OpenAI Image given a prompt:
        ```python
        from prefect_openai import ImageModel

        image_model = ImageModel.load("BLOCK_NAME")
        image_model.submit_prompt(prompt="A prompt for an image.")
        ```
    """
    client = self.openai_credentials.get_client()

    input_kwargs = dict(
        size=self.size,
        n=self.n,
        response_format=self.response_format,
    )
    input_kwargs.update(acreate_kwargs)
    creation = await client.Image.acreate(prompt=prompt, **input_kwargs)
    self.logger.info(
        f"Finished image completion, creating " f"{self.n} {self.size!r} image(s)."
    )
    return creation