Skip to main content

Python library for easily interacting with trained machine learning models

Project description


tags: [gradio-custom-component, Slider] title: gradio_automationbus short_description: colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py

gradio_automationbus

Static Badge

Python library for easily interacting with trained machine learning models

Installation

pip install gradio_automationbus

Usage

import gradio as gr
from gradio_automationbus import AutomationBus


def passthrough(points):
    return points


with gr.Blocks() as demo:
    gr.Markdown("## Automation Lane Demo")
    with gr.Row():
        audio = gr.Audio(label="Audio", sources=["upload", "microphone"], type="filepath")
    with gr.Row():
        lane = AutomationBus(
            label="Automation",
            x_min=0.0,
            x_max=1.0,
            y_min=0.0,
            y_max=1.0,
            top_label="prompt a",
            bottom_label="prompt b",
        )

    # Remove waveform linkage for now

    # Echo points on release
    out = gr.JSON(label="Current Points")
    lane.release(fn=passthrough, inputs=lane, outputs=out)


if __name__ == "__main__":
    demo.launch(share=True)

AutomationBus

Initialization

name type default description
value
list[list[float]] | dict[str, Any] | Callable | None
None Initial points list ([[x, y], ...]) or an object {"points": [[x,y],...], "audio_url": str}.
x_min
float
0.0 Minimum x value of the canvas domain.
x_max
float
1.0 Maximum x value of the canvas domain.
y_min
float
0.0 Minimum y value of the canvas range.
y_max
float
1.0 Maximum y value of the canvas range.
precision
int | None
3 Number of decimal places to round values to when serializing.
audio_url
str | None
None Optional URL or path to an audio file to render waveform background.
shade_enabled
bool
True None
shade_above_color
str | None
"rgba(250, 204, 21, 0.25)" None
shade_below_color
str | None
"rgba(34, 197, 94, 0.25)" None
top_label
str | None
None None
bottom_label
str | None
None None
label
str | I18nData | None
None None
info
str | I18nData | None
None None
every
Timer | float | None
None None
inputs
Component | Sequence[Component] | set[Component] | None
None None
show_label
bool | None
None None
container
bool
True None
scale
int | None
None None
min_width
int
160 None
interactive
bool | None
None None
visible
bool | Literal["hidden"]
True None
elem_id
str | None
None None
elem_classes
list[str] | str | None
None None
render
bool
True None
key
int | str | tuple[int | str, ...] | None
None None
preserved_by_key
list[str] | str | None
"value" None
show_reset_button
bool
True Standard component options.

Events

name description
change Triggered when the value of the AutomationBus 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.
input This listener is triggered when the user changes the value of the AutomationBus.
release This listener is triggered when the user releases the mouse on this AutomationBus.

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 validated and rounded list of points.
def predict(
    value: list[list[float]]
) -> typing.Any:
    return value

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gradio_automationbus-0.0.1.tar.gz (2.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gradio_automationbus-0.0.1-py3-none-any.whl (2.0 MB view details)

Uploaded Python 3

File details

Details for the file gradio_automationbus-0.0.1.tar.gz.

File metadata

  • Download URL: gradio_automationbus-0.0.1.tar.gz
  • Upload date:
  • Size: 2.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.11

File hashes

Hashes for gradio_automationbus-0.0.1.tar.gz
Algorithm Hash digest
SHA256 9023c067fd8008c786831911a82e24a90eb05eaef6261ec405f3c92dd297789d
MD5 46cfa13d4fd53c3bdacdbdbd53555abf
BLAKE2b-256 ef44efff07cc627ca80d45bb7d486b6aed07767ea8b87a9636e8a032b4a3f584

See more details on using hashes here.

File details

Details for the file gradio_automationbus-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for gradio_automationbus-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9c35dd1b08bd47ca803f52b2cb076475cf82a22375f2be86265f1226adaa3b12
MD5 de1456c1a4c28ad4c20a39f8eafb1558
BLAKE2b-256 54b553dc20af348bc7601217ba9a6f0767bee4eadc9fa4d3863c63e1e35c1004

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page