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MaybeOneOrMany module-attribute

MaybeOneOrMany = Union[_T, Sequence[_T], None]

A type that can be either a single item, a sequence of items, or None.

OneOrMany module-attribute

OneOrMany = Union[_T, Sequence[_T]]

A type that can be either a single item or a sequence of items.

StrOrImg module-attribute

StrOrImg = Union[String, Image]

A type that can be either a string or an image.

ContentList

Bases: BaseModel

Represent a list of contents containing text and images.

append

append(content: StrOrImg) -> None

Append a content to the list.

If the last content is a string, it will be concatenated with the new content.

Source code in src/appl/core/types/content.py
def append(self, content: StrOrImg) -> None:
    """Append a content to the list.

    If the last content is a string, it will be concatenated with the new content.
    """
    if is_string(content) and len(self.contents) and is_string(self.contents[-1]):
        self.contents[-1] += content  # type: ignore
    else:
        self.contents.append(content)

extend

extend(contents: list[StrOrImg]) -> None

Extend the list with multiple contents.

Source code in src/appl/core/types/content.py
def extend(self, contents: list[StrOrImg]) -> None:
    """Extend the list with multiple contents."""
    for content in contents:
        self.append(content)

get_contents

get_contents() -> List[Dict[str, Any]]

Return the contents as a list of dictionaries.

Source code in src/appl/core/types/content.py
def get_contents(self) -> List[Dict[str, Any]]:
    """Return the contents as a list of dictionaries."""

    def get_dict(content):
        if isinstance(content, Image):
            image_args = {"url": content.url}
            if content.detail:
                image_args["detail"] = content.detail
            return {"type": "image_url", "image_url": image_args}
        return {"type": "text", "text": str(content)}

    return [get_dict(c) for c in self.contents]

Image

Image(url: str, detail: Optional[str] = None)

Bases: BaseModel

Represent an image in the message.

See the guide for more information about the detail level.

Source code in src/appl/core/types/content.py
def __init__(self, url: str, detail: Optional[str] = None) -> None:
    """Initialize the image with the URL and detail level.

    See [the guide](https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding)
    for more information about the detail level.
    """
    super().__init__(url=url, detail=detail)

from_file classmethod

from_file(
    file: PathLike, detail: Optional[str] = None
) -> Image

Construct an image prompt from an image file.

Source code in src/appl/core/types/content.py
@classmethod
def from_file(cls, file: PathLike, detail: Optional[str] = None) -> "Image":
    """Construct an image prompt from an image file."""
    image = PIL.Image.open(file)
    return cls.from_image(image, detail)

from_image classmethod

from_image(
    image: ImageFile, detail: Optional[str] = None
) -> Image

Construct an image prompt from a PIL ImageFile.

Source code in src/appl/core/types/content.py
@classmethod
def from_image(cls, image: ImageFile, detail: Optional[str] = None) -> "Image":
    """Construct an image prompt from a PIL ImageFile."""
    buffered = BytesIO()
    # Save the image to the buffer in PNG format
    image.save(buffered, format="PNG")
    # Get the byte data from the buffer
    img_byte = buffered.getvalue()
    img_base64 = base64.b64encode(img_byte).decode("utf-8")
    return cls(url=f"data:image/png;base64,{img_base64}", detail=detail)