ImageBase64Content

Base classes

Name	Children	Inherits
BaseImageContent llmling_agent.models.content Base for image content.	ImageURLContent ImageBase64Content	BaseContent

⋔ Inheritance diagram

graph TD
  94890200657616["content.ImageBase64Content"]
  94890194365632["content.BaseImageContent"]
  94890199950896["content.BaseContent"]
  94890183243792["schema.Schema"]
  94890170496944["main.BaseModel"]
  139970493684192["builtins.object"]
  94890194365632 --> 94890200657616
  94890199950896 --> 94890194365632
  94890183243792 --> 94890199950896
  94890170496944 --> 94890183243792
  139970493684192 --> 94890170496944

🛈 DocStrings

Bases: BaseImageContent

Image from base64 data.

Source code in src/llmling_agent/models/content.py

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_openai_format(self) -> dict[str, Any]:
        """Convert to OpenAI API format for vision models."""
        data_url = f"data:{self.mime_type};base64,{self.data}"
        content = {"url": data_url, "detail": self.detail or "auto"}
        return {"type": "image_url", "image_url": content}

    @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

@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

@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())

to_openai_format

to_openai_format() -> dict[str, Any]

Convert to OpenAI API format for vision models.

Source code in src/llmling_agent/models/content.py

def to_openai_format(self) -> dict[str, Any]:
    """Convert to OpenAI API format for vision models."""
    data_url = f"data:{self.mime_type};base64,{self.data}"
    content = {"url": data_url, "detail": self.detail or "auto"}
    return {"type": "image_url", "image_url": content}

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