# `gradio_unifiedaudio` PyPI - Version Python library for easily interacting with trained machine learning models ## Installation ```bash pip install gradio_unifiedaudio ``` ## Usage ```python import gradio as gr from gradio_unifiedaudio import UnifiedAudio from pathlib import Path import numpy as np import time example = UnifiedAudio().example_inputs() dir_ = Path(__file__).parent def add_to_stream(audio, instream): if instream is None: ret = audio else: ret = (audio[0], np.concatenate((instream[1], audio[1]))) return audio, ret def stop_recording(audio): return UnifiedAudio(value=audio, streaming=False) def stop_playing(): return UnifiedAudio(value=None, streaming=True), None with gr.Blocks() as demo: mic = UnifiedAudio(sources=["microphone"], streaming=True) stream = gr.State() mic.stop_recording(stop_recording, stream, mic) # mic.end(lambda: [None, None], None, [mic, stream]) mic.end(stop_playing, None, [mic, stream]) mic.stream(add_to_stream, [mic, stream], [mic, stream]) if __name__ == '__main__': demo.launch() ``` ## `UnifiedAudio` ### Initialization
name type default description
value ```python str | pathlib.Path | tuple[int, numpy.ndarray] | Callable | None ``` None A path, URL, or [sample_rate, numpy array] tuple (sample rate in Hz, audio data as a float or int numpy array) for the default value that UnifiedAudio component is going to take. If callable, the function will be called whenever the app loads to set the initial value of the component.
image ```python str | None ``` None A path or URL to an image to display above the audio component. If None, no image will be displayed.
sources ```python list["upload" | "microphone"] | None ``` None A list of sources permitted for audio. "upload" creates a box where user can drop an audio file, "microphone" creates a microphone input. The first element in the list will be used as the default source. If None, defaults to ["upload", "microphone"], or ["microphone"] if `streaming` is True.
type ```python "numpy" | "filepath" ``` "numpy" The format the audio file is converted to before being passed into the prediction function. "numpy" converts the audio to a tuple consisting of: (int sample rate, numpy.array for the data), "filepath" passes a str path to a temporary file containing the audio.
label ```python str | None ``` None The label for this component. Appears above the component and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.
every ```python float | None ``` None If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
show_label ```python bool | None ``` None if True, will display label.
container ```python bool ``` True If True, will place the component in a container - providing some extra padding around the border.
scale ```python int | None ``` None relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.
min_width ```python int ``` 160 minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.
interactive ```python bool | None ``` None if True, will allow users to upload and edit a audio file; if False, can only be used to play audio. If not provided, this is inferred based on whether the component is used as an input or output.
visible ```python bool ``` True If False, component will be hidden.
streaming ```python bool ``` False If set to True when used in a `live` interface as an input, will automatically stream webcam feed. When used set as an output, takes audio chunks yield from the backend and combines them into one streaming audio output.
elem_id ```python str | None ``` None An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
elem_classes ```python list[str] | str | None ``` None An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
render ```python bool ``` True If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
format ```python "wav" | "mp3" ``` "wav" The file format to save audio files. Either 'wav' or 'mp3'. wav files are lossless but will tend to be larger files. mp3 files tend to be smaller. Default is wav. Applies both when this component is used as an input (when `type` is "format") and when this component is used as an output.
autoplay ```python bool ``` False Whether to automatically play the audio when the component is used as an output. Note: browsers will not autoplay audio files if the user has not interacted with the page yet.
show_share_button ```python bool | None ``` None If True, will show a share icon in the corner of the component that allows user to share outputs to Hugging Face Spaces Discussions. If False, icon does not appear. If set to None (default behavior), then the icon appears if this Gradio app is launched on Spaces, but not otherwise.
min_length ```python int | None ``` None The minimum length of audio (in seconds) that the user can pass into the prediction function. If None, there is no minimum length.
max_length ```python int | None ``` None The maximum length of audio (in seconds) that the user can pass into the prediction function. If None, there is no maximum length.
waveform_options ```python WaveformOptions | None ``` None A dictionary of options for the waveform display. Options include: waveform_color (str), waveform_progress_color (str), show_controls (bool), skip_length (int). Default is None, which uses the default values for these options.
### Events | name | description | |:-----|:------------| | `stream` | This listener is triggered when the user streams the UnifiedAudio. | | `change` | Triggered when the value of the UnifiedAudio changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input. | | `clear` | This listener is triggered when the user clears the UnifiedAudio using the X button for the component. | | `play` | This listener is triggered when the user plays the media in the UnifiedAudio. | | `pause` | This listener is triggered when the media in the UnifiedAudio stops for any reason. | | `stop` | This listener is triggered when the user reaches the end of the media playing in the UnifiedAudio. | | `start_recording` | This listener is triggered when the user starts recording with the UnifiedAudio. | | `pause_recording` | This listener is triggered when the user pauses recording with the UnifiedAudio. | | `stop_recording` | This listener is triggered when the user stops recording with the UnifiedAudio. | | `upload` | This listener is triggered when the user uploads a file into the UnifiedAudio. | | `end` | This listener is triggered when the user reaches the end of the media playing in the UnifiedAudio. | ### User function The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both). - When used as an Input, the component only impacts the input signature of the user function. - When used as an output, the component only impacts the return signature of the user function. The code snippet below is accurate in cases where the component is used as both an input and an output. - **As output:** Is passed, the preprocessed input data sent to the user's function in the backend. - **As input:** Should return, audio data in either of the following formats: a tuple of (sample_rate, data), or a string filepath or URL to an audio file, or None. ```python def predict( value: tuple[int, numpy.ndarray] | str | None ) -> tuple[int, numpy.ndarray] | str | pathlib.Path | bytes | None: return value ``` ## `WaveformOptions` ```python class WaveformOptions(TypedDict, total=False): waveform_color: str waveform_progress_color: str show_controls: bool skip_length: int ```