Skip to main content

Python library for easily interacting with trained machine learning models

Project description

gradio_memotext

PyPI - Version

Python library for easily interacting with trained machine learning models

Installation

pip install gradio_memotext

Usage

import gradio as gr
from gradio_memotext import MemoText


example = MemoText().example_value()

demo = gr.Interface(
    lambda x:x,
    MemoText(),  # interactive version of your component
    MemoText(),  # static version of your component
    # examples=[[example]],  # uncomment this line to view the "example version" of your component
)


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

MemoText

Initialization

name type default description
value
str | Callable | None
None default text to provide in textbox. If a function is provided, the function will be called each time the app loads to set the initial value of this component.
placeholder
str | None
None placeholder hint to provide behind textbox.
label
str | I18nData | None
None the label for this component, displayed above the component if `show_label` is `True` 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 corresponds to.
every
Timer | float | None
None Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise). Can provide a Timer whose tick resets `value`, or a float that provides the regular interval for the reset Timer.
inputs
Component | Sequence[Component] | set[Component] | None
None Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise). `value` is recalculated any time the inputs change.
show_label
bool | None
None if True, will display label.
scale
int | None
None relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.
min_width
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
bool | None
None if True, will be rendered as an editable textbox; if False, editing will be disabled. If not provided, this is inferred based on whether the component is used as an input or output.
visible
bool
True If False, component will be hidden.
rtl
bool
False If True and `type` is "text", sets the direction of the text to right-to-left (cursor appears on the left of the text). Default is False, which renders cursor on the right.
elem_id
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
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
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.
key
int | str | tuple[int | str, ...] | None
None in a gr.render, Components with the same key across re-renders are treated as the same component, not a new component. Properties set in 'preserved_by_key' are not reset across a re-render.
preserved_by_key
list[str] | str | None
"value" A list of parameters from this component's constructor. Inside a gr.render() function, if a component is re-rendered with the same key, these (and only these) parameters will be preserved in the UI (if they have been changed by the user or an event listener) instead of re-rendered based on the values provided during constructor.

Events

name description
change Triggered when the value of the MemoText 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 MemoText.
submit This listener is triggered when the user presses the Enter key while the MemoText is focused.

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, passes text value as a {str} into the function.
  • As input: Should return, expects a {str} returned from function and sets textarea value to it.
def predict(
    value: str | None
) -> str | None:
    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_memotext-0.0.4.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

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

gradio_memotext-0.0.4-py3-none-any.whl (2.1 MB view details)

Uploaded Python 3

File details

Details for the file gradio_memotext-0.0.4.tar.gz.

File metadata

  • Download URL: gradio_memotext-0.0.4.tar.gz
  • Upload date:
  • Size: 2.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for gradio_memotext-0.0.4.tar.gz
Algorithm Hash digest
SHA256 c98c7ac3c6d307bdf2956b60a841f44af95c4947024a58d424060bbc77d12aed
MD5 9d210c51a11f5ad925ab445521c7f9da
BLAKE2b-256 8b65684e518c3115eb9b8d4e89342b9c4557882ecdb411f48a4209308aab6152

See more details on using hashes here.

File details

Details for the file gradio_memotext-0.0.4-py3-none-any.whl.

File metadata

File hashes

Hashes for gradio_memotext-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 baec9a4fd430ce3c71dc9b37b0c8cfa6e8d653c2e05a855d2735cefa7bdf625e
MD5 6a560ddd0474495be9647830232b96a3
BLAKE2b-256 e26e51ed8f63b1bcac5152b901570bd6724434a82f63a1685a0bc3290c10898b

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