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Description:

gradiopromptweighting 0.0.2

gradio_promptweighting

Simple component for creating prompt weighting for real-time generation.
Installation
pip install gradio_promptweighting

Usage
import gradio as gr
from gradio_promptweighting import PromptWeighting

example = PromptWeighting().example_value()

def predict(input):
return (input, input)

with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
prompt = PromptWeighting(
value=[
{"prompt": "a cat", "scale": 1.5},
{"prompt": "a dog", "scale": 1},
{"prompt": "a bird", "scale": 0.5},
],
step=0.001,
info="Please drag up or down to adjust the weight of the prompt.",
)
btn = gr.Button("Update Prompt")
with gr.Column():
text = gr.Textbox(
label="Prompt",
placeholder="",
)
prompt2 = PromptWeighting(min=0, max=10, step=0.001)
inputs = [prompt]
outputs = [text, prompt2]

btn.click(fn=predict, inputs=inputs, outputs=outputs, show_progress=False)
prompt.change(
fn=predict,
inputs=inputs,
outputs=outputs,
queue=False,
trigger_mode="always_last",
show_progress=False,
)

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

PromptWeighting
Initialization

name
type
default
description

value

str | dict | list | Callable | None

None
default text to provide in textbox. If callable, the function will be called whenever the app loads to set the initial value of the component.

placeholder

str | None

None
placeholder hint to provide behind textbox.

label

str | None

None
component name in interface.

every

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. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.

show_label

bool | None

None
if True, will display label.

info

str | None

None
None

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.

min

float | None

None
None

max

float | None

None
None

step

float | None

None
None

Events

name
description

change
Triggered when the value of the PromptWeighting 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 PromptWeighting.

submit
This listener is triggered when the user presses the Enter key while the PromptWeighting 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