AudioBase64Content

Base classes

Name	Children	Inherits
AudioContent llmling_agent.models.content Base for audio content.	AudioURLContent AudioBase64Content	BaseContent

⋔ Inheritance diagram

graph TD
  94398671310176["content.AudioBase64Content"]
  94398671755136["content.AudioContent"]
  94398671379648["content.BaseContent"]
  94398659048192["schema.Schema"]
  94398652298960["main.BaseModel"]
  140214144997856["builtins.object"]
  94398671755136 --> 94398671310176
  94398671379648 --> 94398671755136
  94398659048192 --> 94398671379648
  94398652298960 --> 94398659048192
  140214144997856 --> 94398652298960

🛈 DocStrings

Bases: AudioContent

Audio from base64 data.

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

class AudioBase64Content(AudioContent):
    """Audio from base64 data."""

    type: Literal["audio_base64"] = Field("audio_base64", init=False)
    """Base64-encoded audio."""

    data: str
    """Audio data in base64 format."""

    format: str | None = None  # mp3, wav, etc
    """Audio format."""

    def to_openai_format(self) -> dict[str, Any]:
        """Convert to OpenAI API format for audio models."""
        data_url = f"data:audio/{self.format or 'mp3'};base64,{self.data}"
        content = {"url": data_url, "format": self.format or "auto"}
        return {"type": "audio", "audio": content}

    @classmethod
    def from_bytes(cls, data: bytes, audio_format: str = "mp3") -> Self:
        """Create from raw bytes."""
        return cls(data=base64.b64encode(data).decode(), format=audio_format)

    @classmethod
    def from_path(cls, path: JoinablePathLike) -> Self:
        """Create from file path with auto format detection."""
        import mimetypes

        from upathtools import to_upath

        path_obj = to_upath(path)
        mime_type, _ = mimetypes.guess_type(str(path_obj))
        fmt = (
            mime_type.removeprefix("audio/")
            if mime_type and mime_type.startswith("audio/")
            else "mp3"
        )

        return cls(data=base64.b64encode(path_obj.read_bytes()).decode(), format=fmt)

    @property
    def mime_type(self) -> str:
        """Return the MIME type of the audio."""
        return f"audio/{self.format or 'mp3'}"

data instance-attribute

data: str

Audio data in base64 format.

format class-attribute instance-attribute

format: str | None = None

Audio format.

mime_type property

mime_type: str

Return the MIME type of the audio.

type class-attribute instance-attribute

type: Literal['audio_base64'] = Field('audio_base64', init=False)

Base64-encoded audio.

from_bytes classmethod

from_bytes(data: bytes, audio_format: str = 'mp3') -> Self

Create from raw bytes.

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

@classmethod
def from_bytes(cls, data: bytes, audio_format: str = "mp3") -> Self:
    """Create from raw bytes."""
    return cls(data=base64.b64encode(data).decode(), format=audio_format)

from_path classmethod

from_path(path: JoinablePathLike) -> Self

Create from file path with auto format detection.

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

@classmethod
def from_path(cls, path: JoinablePathLike) -> Self:
    """Create from file path with auto format detection."""
    import mimetypes

    from upathtools import to_upath

    path_obj = to_upath(path)
    mime_type, _ = mimetypes.guess_type(str(path_obj))
    fmt = (
        mime_type.removeprefix("audio/")
        if mime_type and mime_type.startswith("audio/")
        else "mp3"
    )

    return cls(data=base64.b64encode(path_obj.read_bytes()).decode(), format=fmt)

to_openai_format

to_openai_format() -> dict[str, Any]

Convert to OpenAI API format for audio models.

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

def to_openai_format(self) -> dict[str, Any]:
    """Convert to OpenAI API format for audio models."""
    data_url = f"data:audio/{self.format or 'mp3'};base64,{self.data}"
    content = {"url": data_url, "format": self.format or "auto"}
    return {"type": "audio", "audio": content}

Show source on GitHub