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ImageBase64Content

Base classes

Name Children Inherits
BaseImageContent
llmling_agent.models.content
Base for image content.

⋔ Inheritance diagram

graph TD
  94060275456640["content.ImageBase64Content"]
  94060279283504["content.BaseImageContent"]
  94060279310192["content.BaseContent"]
  94060260503136["schema.Schema"]
  94060251496624["main.BaseModel"]
  140544442243552["builtins.object"]
  94060279283504 --> 94060275456640
  94060279310192 --> 94060279283504
  94060260503136 --> 94060279310192
  94060251496624 --> 94060260503136
  140544442243552 --> 94060251496624

🛈 DocStrings

Bases: BaseImageContent

Image from base64 data.

Source code in src/llmling_agent/models/content.py 
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class ImageBase64Content(BaseImageContent):
    """Image from base64 data."""

    type: Literal["image_base64"] = Field("image_base64", init=False)
    """Base64-encoded image."""

    data: str
    """Base64-encoded image data."""

    mime_type: str = "image/jpeg"
    """MIME type of the image."""

    def to_pydantic_ai(self) -> BinaryImage:
        binary_data = base64.b64decode(self.data)
        return BinaryImage(data=binary_data, media_type=self.mime_type or "image/jpeg")

    @classmethod
    def from_bytes(
        cls,
        data: bytes,
        *,
        detail: DetailLevel | None = None,
        description: str | None = None,
    ) -> ImageBase64Content:
        """Create image content from raw bytes.

        Args:
            data: Raw image bytes
            detail: Optional detail level for processing
            description: Optional description of the image
        """
        content = base64.b64encode(data).decode()
        return cls(data=content, detail=detail, description=description)

    @classmethod
    def from_pil_image(cls, image: PIL.Image.Image) -> ImageBase64Content:
        """Create content from PIL Image."""
        with io.BytesIO() as buffer:
            image.save(buffer, format="PNG")
            return cls(data=base64.b64encode(buffer.getvalue()).decode())

data instance-attribute 

data: str

Base64-encoded image data.

mime_type class-attribute instance-attribute 

mime_type: str = 'image/jpeg'

MIME type of the image.

type class-attribute instance-attribute 

type: Literal['image_base64'] = Field('image_base64', init=False)

Base64-encoded image.

from_bytes classmethod 

from_bytes(
    data: bytes, *, detail: DetailLevel | None = None, description: str | None = None
) -> ImageBase64Content

Create image content from raw bytes.

Parameters:

Name Type Description Default
data bytes

Raw image bytes

 required
detail DetailLevel | None

Optional detail level for processing

 None
description str | None

Optional description of the image

 None
Source code in src/llmling_agent/models/content.py 
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@classmethod
def from_bytes(
    cls,
    data: bytes,
    *,
    detail: DetailLevel | None = None,
    description: str | None = None,
) -> ImageBase64Content:
    """Create image content from raw bytes.

    Args:
        data: Raw image bytes
        detail: Optional detail level for processing
        description: Optional description of the image
    """
    content = base64.b64encode(data).decode()
    return cls(data=content, detail=detail, description=description)

from_pil_image classmethod 

from_pil_image(image: Image) -> ImageBase64Content

Create content from PIL Image.

Source code in src/llmling_agent/models/content.py 
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@classmethod
def from_pil_image(cls, image: PIL.Image.Image) -> ImageBase64Content:
    """Create content from PIL Image."""
    with io.BytesIO() as buffer:
        image.save(buffer, format="PNG")
        return cls(data=base64.b64encode(buffer.getvalue()).decode())

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