dspy.Audio

dspy.Audio

Bases: Type

Functions

adapt_to_native_lm_feature(signature: type[Signature], field_name: str, lm: LM, lm_kwargs: dict[str, Any]) -> type[Signature] classmethod

Adapt the custom type to the native LM feature if possible.

When the LM and configuration supports the related native LM feature, e.g., native tool calling, native reasoning, etc., we adapt the signature and lm_kwargs to enable the native LM feature.

Parameters:

Name	Type	Description	Default
signature	type[Signature]	The DSPy signature for the LM call.	required
field_name	str	The name of the field in the signature to adapt to the native LM feature.	required
lm	LM	The LM instance.	required
lm_kwargs	dict[str, Any]	The keyword arguments for the LM call, subject to in-place updates if adaptation if required.	required

Returns:

Type	Description
type[Signature]	The adapted signature. If the custom type is not natively supported by the LM, return the original
type[Signature]	signature.

Source code in dspy/adapters/types/base_type.py

@classmethod
def adapt_to_native_lm_feature(
    cls,
    signature: type["Signature"],
    field_name: str,
    lm: "LM",
    lm_kwargs: dict[str, Any],
) -> type["Signature"]:
    """Adapt the custom type to the native LM feature if possible.

    When the LM and configuration supports the related native LM feature, e.g., native tool calling, native
    reasoning, etc., we adapt the signature and `lm_kwargs` to enable the native LM feature.

    Args:
        signature: The DSPy signature for the LM call.
        field_name: The name of the field in the signature to adapt to the native LM feature.
        lm: The LM instance.
        lm_kwargs: The keyword arguments for the LM call, subject to in-place updates if adaptation if required.

    Returns:
        The adapted signature. If the custom type is not natively supported by the LM, return the original
        signature.
    """
    return signature

description() -> str classmethod

Description of the custom type

Source code in dspy/adapters/types/base_type.py

@classmethod
def description(cls) -> str:
    """Description of the custom type"""
    return ""

extract_custom_type_from_annotation(annotation) classmethod

Extract all custom types from the annotation.

This is used to extract all custom types from the annotation of a field, while the annotation can have arbitrary level of nesting. For example, we detect Tool is in list[dict[str, Tool]].

Source code in dspy/adapters/types/base_type.py

@classmethod
def extract_custom_type_from_annotation(cls, annotation):
    """Extract all custom types from the annotation.

    This is used to extract all custom types from the annotation of a field, while the annotation can
    have arbitrary level of nesting. For example, we detect `Tool` is in `list[dict[str, Tool]]`.
    """
    # Direct match. Nested type like `list[dict[str, Event]]` passes `isinstance(annotation, type)` in python 3.10
    # while fails in python 3.11. To accommodate users using python 3.10, we need to capture the error and ignore it.
    try:
        if isinstance(annotation, type) and issubclass(annotation, cls):
            return [annotation]
    except TypeError:
        pass

    origin = get_origin(annotation)
    if origin is None:
        return []

    result = []
    # Recurse into all type args
    for arg in get_args(annotation):
        result.extend(cls.extract_custom_type_from_annotation(arg))

    return result

format() -> list[dict[str, Any]]

Source code in dspy/adapters/types/audio.py

def format(self) -> list[dict[str, Any]]:
    try:
        data = self.data
    except Exception as e:
        raise ValueError(f"Failed to format audio for DSPy: {e}")
    return [{
        "type": "input_audio",
        "input_audio": {
            "data": data,
            "format": self.audio_format
        }
    }]

from_array(array: Any, sampling_rate: int, format: str = 'wav') -> Audio classmethod

Process numpy-like array and encode it as base64. Uses sampling rate and audio format for encoding.

Source code in dspy/adapters/types/audio.py

@classmethod
def from_array(
    cls, array: Any, sampling_rate: int, format: str = "wav"
) -> "Audio":
    """
    Process numpy-like array and encode it as base64. Uses sampling rate and audio format for encoding.
    """
    if not SF_AVAILABLE:
        raise ImportError("soundfile is required to process audio arrays.")

    byte_buffer = io.BytesIO()
    sf.write(
        byte_buffer,
        array,
        sampling_rate,
        format=format.upper(),
        subtype="PCM_16",
    )
    encoded_data = base64.b64encode(byte_buffer.getvalue()).decode("utf-8")
    return cls(data=encoded_data, audio_format=format)

from_file(file_path: str) -> Audio classmethod

Read local audio file and encode it as base64.

Source code in dspy/adapters/types/audio.py

@classmethod
def from_file(cls, file_path: str) -> "Audio":
    """
    Read local audio file and encode it as base64.
    """
    if not os.path.isfile(file_path):
        raise ValueError(f"File not found: {file_path}")

    mime_type, _ = mimetypes.guess_type(file_path)
    if not mime_type or not mime_type.startswith("audio/"):
        raise ValueError(f"Unsupported MIME type for audio: {mime_type}")

    with open(file_path, "rb") as file:
        file_data = file.read()

    audio_format = mime_type.split("/")[1]

    audio_format = _normalize_audio_format(audio_format)

    encoded_data = base64.b64encode(file_data).decode("utf-8")
    return cls(data=encoded_data, audio_format=audio_format)

from_url(url: str) -> Audio classmethod

Download an audio file from URL and encode it as base64.

Source code in dspy/adapters/types/audio.py

@classmethod
def from_url(cls, url: str) -> "Audio":
    """
    Download an audio file from URL and encode it as base64.
    """
    response = requests.get(url)
    response.raise_for_status()
    mime_type = response.headers.get("Content-Type", "audio/wav")
    if not mime_type.startswith("audio/"):
        raise ValueError(f"Unsupported MIME type for audio: {mime_type}")
    audio_format = mime_type.split("/")[1]

    audio_format = _normalize_audio_format(audio_format)

    encoded_data = base64.b64encode(response.content).decode("utf-8")
    return cls(data=encoded_data, audio_format=audio_format)

is_streamable() -> bool classmethod

Whether the custom type is streamable.

Source code in dspy/adapters/types/base_type.py

@classmethod
def is_streamable(cls) -> bool:
    """Whether the custom type is streamable."""
    return False

parse_lm_response(response: str | dict[str, Any]) -> Optional[Type] classmethod

Parse a LM response into the custom type.

Parameters:

Name	Type	Description	Default
response	str | dict[str, Any]	A LM response.	required

Returns:

Type	Description
Optional[Type]	A custom type object.

Source code in dspy/adapters/types/base_type.py

@classmethod
def parse_lm_response(cls, response: str | dict[str, Any]) -> Optional["Type"]:
    """Parse a LM response into the custom type.

    Args:
        response: A LM response.

    Returns:
        A custom type object.
    """
    return None

parse_stream_chunk(chunk: ModelResponseStream) -> Optional[Type] classmethod

Parse a stream chunk into the custom type.

Parameters:

Name	Type	Description	Default
chunk	ModelResponseStream	A stream chunk.	required

Returns:

Type	Description
Optional[Type]	A custom type object or None if the chunk is not for this custom type.

Source code in dspy/adapters/types/base_type.py

@classmethod
def parse_stream_chunk(cls, chunk: ModelResponseStream) -> Optional["Type"]:
    """
    Parse a stream chunk into the custom type.

    Args:
        chunk: A stream chunk.

    Returns:
        A custom type object or None if the chunk is not for this custom type.
    """
    return None

serialize_model()

Source code in dspy/adapters/types/base_type.py

@pydantic.model_serializer()
def serialize_model(self):
    formatted = self.format()
    if isinstance(formatted, list):
        return (
            f"{CUSTOM_TYPE_START_IDENTIFIER}{json.dumps(formatted, ensure_ascii=False)}{CUSTOM_TYPE_END_IDENTIFIER}"
        )
    return formatted

validate_input(values: Any) -> Any classmethod

Validate input for Audio, expecting 'data' and 'audio_format' keys in dictionary.

Source code in dspy/adapters/types/audio.py

@pydantic.model_validator(mode="before")
@classmethod
def validate_input(cls, values: Any) -> Any:
    """
    Validate input for Audio, expecting 'data' and 'audio_format' keys in dictionary.
    """
    if isinstance(values, cls):
        return {"data": values.data, "audio_format": values.audio_format}
    return encode_audio(values)

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