wehub-resource-sync
89 lines
3.6 KiB
Python
89 lines
3.6 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import mimetypes
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from typing import Any, ClassVar, Literal, TypeVar
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from numpy import ndarray
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from pydantic import Field
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from semantic_kernel.contents.binary_content import BinaryContent
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from semantic_kernel.contents.const import AUDIO_CONTENT_TAG, ContentTypes
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from semantic_kernel.utils.feature_stage_decorator import experimental
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_T = TypeVar("_T", bound="AudioContent")
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@experimental
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class AudioContent(BinaryContent):
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"""Audio Content class.
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This can be created either the bytes data or a data uri, additionally it can have a uri.
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The uri is a reference to the source, and might or might not point to the same thing as the data.
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Use the .from_audio_file method to create an instance from an audio file.
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This reads the file and guesses the mime_type.
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If both data_uri and data is provided, data will be used and a warning is logged.
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Args:
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uri (Url | None): The reference uri of the content.
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data_uri (DataUrl | None): The data uri of the content.
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data (str | bytes | None): The data of the content.
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data_format (str | None): The format of the data (e.g. base64).
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mime_type (str | None): The mime type of the audio, only used with data.
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kwargs (Any): Any additional arguments:
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inner_content (Any): The inner content of the response,
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this should hold all the information from the response so even
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when not creating a subclass a developer can leverage the full thing.
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ai_model_id (str | None): The id of the AI model that generated this response.
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metadata (dict[str, Any]): Any metadata that should be attached to the response.
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"""
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content_type: Literal[ContentTypes.AUDIO_CONTENT] = Field(default=AUDIO_CONTENT_TAG, init=False) # type: ignore
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tag: ClassVar[str] = AUDIO_CONTENT_TAG
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def __init__(
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self,
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uri: str | None = None,
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data_uri: str | None = None,
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data: str | bytes | ndarray | None = None,
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data_format: str | None = None,
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mime_type: str | None = None,
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**kwargs: Any,
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):
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"""Create an Audio Content object, either from a data_uri or data.
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Args:
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uri: The reference uri of the content.
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data_uri: The data uri of the content.
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data: The data of the content.
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data_format: The format of the data (e.g. base64).
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mime_type: The mime type of the audio, only used with data.
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kwargs: Any additional arguments:
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inner_content: The inner content of the response,
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this should hold all the information from the response so even
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when not creating a subclass a developer
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can leverage the full thing.
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ai_model_id: The id of the AI model that generated this response.
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metadata: Any metadata that should be attached to the response.
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"""
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super().__init__(
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uri=uri,
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data_uri=data_uri,
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data=data,
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data_format=data_format,
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mime_type=mime_type,
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**kwargs,
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)
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@classmethod
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def from_audio_file(cls: type[_T], path: str) -> _T:
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"""Create an instance from an audio file."""
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mime_type = mimetypes.guess_type(path)[0]
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with open(path, "rb") as audio_file:
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return cls(data=audio_file.read(), data_format="base64", mime_type=mime_type, uri=path)
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def to_dict(self) -> dict[str, Any]:
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"""Convert the instance to a dictionary."""
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return {"type": "audio_url", "audio_url": {"uri": str(self)}}
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