tags	gradio-custom-component ui form settings dataclass
title	gradio_propertysheet
short_description	Property Sheet Component for Gradio
colorFrom	blue
colorTo	green
sdk	gradio
pinned	true
app_file	space.py

gradio_propertysheet

💻 Component GitHub Code

The PropertySheet component for Gradio allows you to automatically generate a complete and interactive settings panel from a standard Python dataclass. It's designed to bring the power of IDE-like property editors directly into your Gradio applications.

Key Features

• Automatic UI Generation: Instantly converts dataclass fields into a structured UI.
• Rich Component Support: Automatically maps Python types to UI controls:
  • str -> Text Input
  • int, float -> Number Input
  • bool -> Styled Checkbox
  • typing.Literal -> Dropdown
• Metadata-Driven Components: Force a specific component using metadata:
  • metadata={"component": "slider"}
  • metadata={"component": "radio"}
  • metadata={"component": "colorpicker"}
• Nested Groups: Nested dataclasses are rendered as collapsible groups for organization.
• Conditional Visibility: Show or hide fields based on the value of others using interactive_if metadata.
• Built-in Helpers:
  • Tooltips: Add help text to any property's metadata for an info icon.
  • Reset Button: Each property gets a button to reset its value to default.
• Accordion Layout: The entire component can act as a main collapsible accordion panel using the open parameter.
• Theme-Aware: Designed to look and feel native in all Gradio themes.
• Dynamic Updates: Supports advanced patterns where changing one field (e.g., a model selector) can dynamically update the options of another field (e.g., a sampler dropdown).

Installation

pip install gradio_propertysheet

Usage

import os
import json
import gradio as gr
from dataclasses import dataclass, field, asdict
from typing import List, Literal
from gradio_propertysheet import PropertySheet
from gradio_htmlinjector import HTMLInjector

PAG_LAYERS = {
    "down.blocks.1": "down.blocks.1",
    "down.blocks.1.attn.0": "down.blocks.1.attentions.0",
    "down.blocks.1.attn.1": "down.blocks.1.attentions.1",
    "down.blocks.2": "down.blocks.2",
    "down.blocks.2.attn.0": "down.blocks.2.attentions.0",
    "down.blocks.2.attn.1": "down.blocks.2.attentions.1",
    "mid": "mid",
    "up.blocks.0": "up.blocks.0",
    "up.blocks.0.attn.0": "up.blocks.0.attentions.0",
    "up.blocks.0.attn.1": "up.blocks.0.attentions.1",
    "up.blocks.0.attn.2": "up.blocks.0.attentions.2",
    "up.blocks.1": "up.blocks.1",
    "up.blocks.1.attn.0": "up.blocks.1.attentions.0",
    "up.blocks.1.attn.1": "up.blocks.1.attentions.1",
    "up.blocks.1.attn.2": "up.blocks.1.attentions.2",  
}

# --- 1. Dataclass Definitions ---
@dataclass
class PAGSettings:
    """Defines settings for Perturbed Attention Guidance."""
    enable_pag: bool = field(default=False, metadata={"label": "Enable PAG"})
  
    pag_layers: List[str] = field(
        default_factory=list,  # Use default_factory for mutable types like lists
        metadata={
            "component": "multiselect_checkbox", # Our new custom component type
            "choices": list(PAG_LAYERS.keys()),  # Provide the list of all possible options
            "label": "PAG Layers",
            "interactive_if": {"field": "enable_pag", "value": True},
            "help": "Select the UNet layers where Perturbed Attention Guidance should be applied."
        }
    )  
    pag_scale: float = field(default=3.0,  metadata={
            "component": "slider",
            "label": "PAG Scale",
            "minimum": 0.0,
            "maximum": 1.0,
            "step": 0.01            
        })
    
@dataclass
class EffectBase:
    """Base class with common effect settings."""
    strength: float = field(
        default=0.5,
        metadata={
            "component": "slider",
            "label": "Effect Strength",
            "minimum": 0.0,
            "maximum": 1.0,
            "step": 0.01,
            # This rule depends on the 'is_active' field from the child class
            "interactive_if": {"field": "is_active", "value": True}
        }
    )

@dataclass
class EffectSettings(EffectBase):
    """Child class that adds the activation control."""
    is_active: bool = field(
        default=True,
        metadata={"label": "Enable Effect"}
    )

@dataclass
class EffectsConfig:
    """Main dataclass containing multiple effects with same-named control fields."""
    blur_effect: EffectSettings = field(
        default_factory=EffectSettings,
        metadata={"label": "Blur Effect"}
    )
    sharpen_effect: EffectSettings = field(
        default_factory=EffectSettings,
        metadata={"label": "Sharpen Effect"}
    )
    vignette_effect: EffectSettings = field(
        default_factory=EffectSettings,
        metadata={"label": "Vignette Effect"}
    )

@dataclass
class APISettings:
    api_key: str = field(
        default="ab123cd45ef67890ghij123klmno456p",
        metadata={
            "label": "API Key",            
            "component": "password", 
            "help": "Your secret API key. It will not be displayed."
        }
    )
    endpoint_url: str = field(
        default="https://api.example.com",
        metadata={
            "label": "API Endpoint",
            "component": "string", # Normal string
            "help": "The URL of the API server."
        }
    )

@dataclass
class QuantizationSettings:
    quantization_method: Literal["None", "Quanto Library", "Layerwise & Bnb"] = field(
        default="Layerwise & Bnb",
        metadata={
            "component": "radio",
            "label": "Quantization Method",
            "help": "Quantization mechanism to save VRAM and increase speed."
        }
    )
    quantize_mode_list: Literal["FP8", "INT8", "IN4"] = field(
        default="FP8",
        metadata={
            "interactive_if": {"field": "quantization_method", "value": ["Quanto Library", "Layerwise & Bnb"]},
            "component": "radio",
            "label": "Quantization Mode (List)",
            "help": "This becomes interactive if Quantization Method is 'Quanto' OR 'Layerwise'."
        }
    )
    quantize_mode_neq: Literal["FP8", "INT8", "IN4"] = field(
        default="FP8",
        metadata={
            "interactive_if": {"field": "quantization_method", "neq": "None"},
            "component": "radio",
            "label": "Quantization Mode (Not Equal)",
            "help": "This becomes interactive if Quantization Method is NOT 'None'."
        }
    )

@dataclass
class ModelSettings:
    model_type: Literal["SD 1.5", "SDXL", "Pony", "Custom"] = field(
        default="SDXL",
        metadata={
            "component": "dropdown",
            "label": "Base Model",
            "help": "Select the base diffusion model.",
            "visible": True
        }
    )
    custom_model_path: str = field(
        default="/path/to/default.safetensors",
        metadata={
            "label": "Custom Model Path",
            "interactive_if": {"field": "model_type", "value": "Custom"},
            "help": "Provide the local file path to your custom .safetensors or .ckpt model file. This is only active when 'Base Model' is set to 'Custom'."
        },
    )
    vae_path: str = field(
        default="",
        metadata={
            "label": "VAE Path (optional)",
            "help": "Optionally, provide a path to a separate VAE file to improve color and detail."
        }
    )

@dataclass
class SamplingSettings:
    scheduler: Literal["Karras", "Simple", "Exponential"] = field(
        default="Karras",
        metadata={
            "component": "radio",
            "label": "Scheduler",
            "help": "Determines how the noise schedule is interpreted during sampling. 'Karras' is often recommended for high-quality results."
        }
    )
    sampler_name: Literal["Euler", "Euler a", "DPM++ 2M Karras", "UniPC"] = field(
        default="DPM++ 2M Karras",
        metadata={
            "component": "dropdown",
            "label": "Sampler",
            "help": "The algorithm used to denoise the image over multiple steps. Different samplers can produce stylistically different results."
        }
    )
    steps: int = field(
        default=25,
        metadata={
            "component": "slider",
            "label": "Sampling Steps",
            "minimum": 1,
            "maximum": 150,
            "step": 1,
            "help": "The number of denoising steps. More steps can increase detail but also take longer. Values between 20-40 are common."
        }
    )
    cfg_scale: float = field(
        default=7.0,
        metadata={
            "component": "slider",
            "label": "CFG Scale",
            "minimum": 1.0,
            "maximum": 30.0,
            "step": 0.5,
            "help": "Classifier-Free Guidance Scale. Higher values make the image adhere more strictly to the prompt, while lower values allow for more creativity."
        }
    )
    enable_advanced: bool = field(
        default=False,
        metadata={
            "label": "Enable Advanced Settings",
            "help": "Check this box to reveal more experimental or fine-tuning options."
        }
    )
    advanced_option: float = field(
        default=0.5,
        metadata={
            "label": "Advanced Option",
            "component": "slider",
            "minimum": 0.0,
            "maximum": 1.0,
            "step": 0.01,
            "visible_if": {"field": "enable_advanced", "value": True},
            "interactive_if": {"field": "enable_advanced", "value": True},
            "help": "An example of an advanced setting that is only visible when the corresponding checkbox is enabled."
        },
    )
    temperature: float = field(
        default=1.0,
        metadata={
            "label": "Sampling Temperature",
            "component": "number_float",
            "minimum": 0.1,
            "maximum": 2.0,
            "step": 0.1,
            "visible_if": {"field": "enable_advanced", "value": True},
            "help": "Controls the randomness of the sampling process. A value of 1.0 is standard. Higher values increase diversity at the risk of artifacts."
        }
    )


@dataclass
class AdvancedSamplingSettings:
    override_sampler: bool = field(
        default=False,
        metadata={
            "label": "Override Sampler Settings",
            "help": "Enable this to activate special sampler-specific options below."
        }
    )
    custom_noise: float = field(
        default=1.0,
        metadata={
            "component": "slider",
            "label": "Custom Noise Multiplier",
            "minimum": 0.5,
            "maximum": 1.5,
            "step": 0.01,
            "interactive_if": {"field": "override_sampler", "value": True},
            "help": "A custom setting that is only active when 'Override Sampler Settings' is checked."
        }
    )


@dataclass
class RenderConfig:
    api_settings: APISettings = field(
        default_factory=APISettings,
        metadata={"label": "API Settings"}
    )
    randomize_seed: bool = field(
        default=True,
        metadata={
            "label": "Randomize Seed",
            "help": "If checked, a new random seed will be used for each generation. Uncheck to use the specific seed value below."
        }
    )
    seed: int = field(
        default=-1,
        metadata={
            "component": "number_integer",
            "label": "Seed",
            "help": "The seed for the random number generator. A value of -1 means a random seed will be chosen. The same seed and settings will produce the same image."
        }
    )
    model: ModelSettings = field(
        default_factory=ModelSettings,
        metadata={"label": "Model Settings"}
    )
    sampling: SamplingSettings = field(
        default_factory=SamplingSettings,
        metadata={"label": "Sampling Settings"}
    )
    
    advanced_sampling: AdvancedSamplingSettings = field(
        default_factory=AdvancedSamplingSettings,
        metadata={"label": "Advanced Sampling"}
    )
    
    quantization: QuantizationSettings = field(
        default_factory=QuantizationSettings,
        metadata={"label": "Quantization Settings"}
    )
    pag_settings: PAGSettings = field(default_factory=PAGSettings, metadata={"label": "PAG Settings"})
    tile_size: Literal[1024, 1280] = field(
        default=1280, 
        metadata={
            "component": "dropdown", 
            "label": "Tile Size", 
            "help": "The size (in pixels) of the square tiles to use when latent tiling is enabled."
        }
    )

@dataclass
class Lighting:
    sun_intensity: float = field(
        default=1.0,
        metadata={
            "component": "slider",
            "label": "Sun Intensity",
            "minimum": 0,
            "maximum": 5,
            "step": 0.1,
            "help": "Controls the brightness of the main light source in the scene."
        }
    )
    color: str = field(
        default="#FFDDBB",
        metadata={
            "component": "colorpicker",
            "label": "Sun Color",
            "help": "Sets the color of the main light source."
        }
    )

@dataclass
class EnvironmentConfig:
    background: Literal["Sky", "Color", "Image"] = field(
        default="Sky",
        metadata={
            "component": "dropdown",
            "label": "Background Type",
            "help": "Choose the type of background for the environment."
        }
    )
    lighting: Lighting = field(
        default_factory=Lighting,
        metadata={"label": "Lighting"}
    )

@dataclass
class EulerSettings:
    s_churn: float = field(
        default=0.0,
        metadata={
            "component": "slider",
            "label": "S_Churn",
            "minimum": 0.0,
            "maximum": 1.0,
            "step": 0.01,
            "help": "Stochasticity churn factor for Euler samplers. Adds extra noise at each step, affecting diversity. 0.0 is deterministic."
        }
    )

@dataclass
class DPM_Settings:
    karras_style: bool = field(
        default=True,
        metadata={
            "label": "Use Karras Sigma Schedule",
            "help": "If checked, uses the Karras noise schedule, which is often recommended for DPM++ samplers to improve image quality, especially in later steps."
        }
    )

# --- 2. Data Mappings and Initial Instances ---
initial_render_config = RenderConfig()
initial_env_config = EnvironmentConfig()
initial_effects_config = EffectsConfig()

sampler_settings_map_py = {
    "Euler": EulerSettings(),
    "DPM++ 2M Karras": DPM_Settings(),
    "UniPC": None,
    "CustomSampler": SamplingSettings()
}
model_settings_map_py = {
    "SDXL 1.0": DPM_Settings(),
    "Stable Diffusion 1.5": EulerSettings(),
    "Pony": None,
}

# --- 3. CSS & JS Injection function ---
def inject_assets():
    """
    This function prepares the payload of CSS, JS, and Body HTML for injection.
    """
    popup_html = """<div id="injected_flyout_container" class="flyout-sheet" style="display: none;"></div>"""
    css_code = ""
    js_code = ""

    try:
        with open("custom.css", "r", encoding="utf-8") as f:
            css_code += f.read() + "\n"
        with open("custom.js", "r", encoding="utf-8") as f:
            js_code += f.read() + "\n"
    except FileNotFoundError as e:
        print(f"Warning: Could not read asset file: {e}")
    return {"js": js_code, "css": css_code, "body_html": popup_html}


# --- 4. Gradio App Build ---
with gr.Blocks(theme=gr.themes.Ocean(), title="PropertySheet Demos") as demo:
    html_injector = HTMLInjector()
    gr.Markdown("# PropertySheet Component Demos")

    with gr.Row():
        # --- Flyout popup ---
        with gr.Column(
            elem_id="flyout_panel_source", elem_classes=["flyout-source-hidden"]
        ) as flyout_panel_source:
            close_btn = gr.Button("×", elem_classes=["flyout-close-btn"])
            flyout_sheet = PropertySheet(
                visible=True,
                container=False,
                label="Settings",
                show_group_name_only_one=False,
                disable_accordion=True,
            )

    with gr.Tabs():
        with gr.TabItem("Original Sidebar Demo"):
            gr.Markdown(
                "An example of using the `PropertySheet` component as a traditional sidebar for settings."
            )
            effects_state = gr.State(value=initial_effects_config)
            render_state = gr.State(value=initial_render_config)
            env_state = gr.State(value=initial_env_config)
            sidebar_visible = gr.State(False)
            with gr.Row():
                with gr.Column(scale=3):
                    generate_btn = gr.Button("Show Settings", variant="primary")
                    with gr.Row():
                        output_render_json = gr.JSON(label="Live Render State")
                        output_env_json = gr.JSON(label="Live Environment State")
                        output_effects_json = gr.JSON(label="Live Effects State")
                with gr.Column(scale=1):
                    render_sheet = PropertySheet(
                        value=initial_render_config,
                        label="Render Settings",
                        width=400,
                        height=550,
                        visible=False,
                        root_label="Generator",
                        interactive=True                        
                    )
                    environment_sheet = PropertySheet(
                        value=initial_env_config,
                        label="Environment Settings",
                        width=400,
                        open=False,
                        visible=False,
                        root_label="General",
                        interactive=True,
                        root_properties_first=False
                    )
                    effects_sheet = PropertySheet(
                        value=initial_effects_config,
                        label="Post-Processing Effects",
                        width=400,
                        visible=False,
                        interactive=True
                    )

            def change_visibility(is_visible, render_cfg, env_cfg, effects_cfg):
                new_visibility = not is_visible
                button_text = "Hide Settings" if new_visibility else "Show Settings"
                return (
                    new_visibility,
                    gr.update(visible=new_visibility, value=render_cfg),
                    gr.update(visible=new_visibility, value=env_cfg),
                    gr.update(visible=new_visibility, value=effects_cfg),
                    gr.update(value=button_text),
                )

            def handle_render_change(
                updated_config: RenderConfig, current_state: RenderConfig
            ):
                if updated_config is None:
                    return current_state, asdict(current_state), current_state
                if updated_config.model.model_type != "Custom":
                    updated_config.model.custom_model_path = "/path/to/default.safetensors"                
                return updated_config, asdict(updated_config), updated_config

            def handle_env_change(
                updated_config: EnvironmentConfig, current_state: EnvironmentConfig
            ):
                if updated_config is None:
                    return current_state, asdict(current_state), current_state
                return updated_config, asdict(updated_config), current_state
            
            def handle_effects_change(updated_config: EffectsConfig, current_state: EffectsConfig):
                if updated_config is None:
                    return current_state, asdict(current_state), current_state
                return updated_config, asdict(updated_config), updated_config

            generate_btn.click(
                fn=change_visibility,             
                inputs=[sidebar_visible, render_state, env_state, effects_state],                
                outputs=[sidebar_visible, render_sheet, environment_sheet, effects_sheet, generate_btn],
            )
          
            render_sheet.change(
                fn=handle_render_change,
                inputs=[render_sheet, render_state],
                outputs=[render_sheet, output_render_json, render_state],
            )
            environment_sheet.change(
                fn=handle_env_change,
                inputs=[environment_sheet, env_state],
                outputs=[environment_sheet, output_env_json, env_state],
            )
            effects_sheet.change(
                fn=handle_effects_change,
                inputs=[effects_sheet, effects_state],
                outputs=[effects_sheet, output_effects_json, effects_state]
            )
            
            def on_undo(updated_config, current_state):
                if updated_config is None:
                    return current_state, asdict(current_state)
                return updated_config, asdict(updated_config)
            
            render_sheet.undo(
                fn=on_undo, 
                inputs=[render_sheet, render_state], 
                outputs=[render_state, output_render_json]
            )
            environment_sheet.undo(
                fn=on_undo, 
                inputs=[environment_sheet, env_state],
                outputs=[env_state, output_env_json],
            )
            effects_sheet.undo(
                fn=on_undo,
                inputs=[effects_sheet, effects_state],
                outputs=[effects_state, output_effects_json]
            )
            
            demo.load(
                fn=lambda r_cfg, e_cfg, ef_cfg: (asdict(r_cfg), asdict(e_cfg), asdict(ef_cfg)),
                inputs=[render_state, env_state, effects_state],
                outputs=[output_render_json, output_env_json, output_effects_json],
            )

        with gr.TabItem("Flyout Popup Demo"):
            gr.Markdown(
                "An example of attaching a `PropertySheet` as a flyout panel to other components."
            )

            # --- State Management ---
            flyout_visible = gr.State(False)
            active_anchor_id = gr.State(None)
            js_data_bridge = gr.Textbox(visible=False, elem_id="js_data_bridge")

            with gr.Column(elem_classes=["flyout-context-area"]):
                with gr.Row(
                    elem_classes=["fake-input-container", "no-border-dropdown"]
                ):
                    sampler_dd = gr.Dropdown(
                        choices=list(sampler_settings_map_py.keys()),
                        label="Sampler",
                        value="Euler",
                        elem_id="sampler_dd",
                        scale=10,
                    )
                    sampler_ear_btn = gr.Button(
                        "⚙️",
                        elem_id="sampler_ear_btn",
                        scale=1,
                        elem_classes=["integrated-ear-btn"],
                    )

                with gr.Row(
                    elem_classes=["fake-input-container", "no-border-dropdown"]
                ):
                    model_dd = gr.Dropdown(
                        choices=list(model_settings_map_py.keys()),
                        label="Model",
                        value="SDXL 1.0",
                        elem_id="model_dd",
                        scale=10,
                    )
                    model_ear_btn = gr.Button(
                        "⚙️",
                        elem_id="model_ear_btn",
                        scale=1,
                        elem_classes=["integrated-ear-btn"],
                    )

            # --- Event Logic ---
            def handle_flyout_toggle(
                is_vis, current_anchor, clicked_dropdown_id, settings_obj
            ):
                if is_vis and current_anchor == clicked_dropdown_id:
                    js_data = json.dumps({"isVisible": False, "anchorId": None})
                    return False, None, gr.update(), gr.update(value=js_data)
                else:
                    js_data = json.dumps(
                        {"isVisible": True, "anchorId": clicked_dropdown_id}
                    )
                    return (
                        True,
                        clicked_dropdown_id,
                        gr.update(value=settings_obj),
                        gr.update(value=js_data),
                    )

            def update_ear_visibility(selection, settings_map):
                has_settings = settings_map.get(selection) is not None
                return gr.update(visible=has_settings)

            def on_flyout_change(updated_settings, active_id, sampler_val, model_val):
                if updated_settings is None or active_id is None:
                    return
                if active_id == sampler_dd.elem_id:
                    sampler_settings_map_py[sampler_val] = updated_settings
                elif active_id == model_dd.elem_id:
                    model_settings_map_py[model_val] = updated_settings

            def close_the_flyout():
                js_data = json.dumps({"isVisible": False, "anchorId": None})
                return False, None, gr.update(value=js_data)

            js_update_flyout = "(jsonData) => { update_flyout_from_state(jsonData); }"

            sampler_dd.change(
                fn=lambda sel: update_ear_visibility(sel, sampler_settings_map_py),
                inputs=[sampler_dd],
                outputs=[sampler_ear_btn],
            ).then(
                fn=close_the_flyout,
                outputs=[flyout_visible, active_anchor_id, js_data_bridge],
            ).then(
                fn=None, inputs=[js_data_bridge], js=js_update_flyout
            )

            sampler_ear_btn.click(
                fn=lambda is_vis, anchor, sel: handle_flyout_toggle(
                    is_vis, anchor, sampler_dd.elem_id, sampler_settings_map_py.get(sel)
                ),
                inputs=[flyout_visible, active_anchor_id, sampler_dd],
                outputs=[
                    flyout_visible,
                    active_anchor_id,
                    flyout_sheet,
                    js_data_bridge,
                ],
            ).then(fn=None, inputs=[js_data_bridge], js=js_update_flyout)

            model_dd.change(
                fn=lambda sel: update_ear_visibility(sel, model_settings_map_py),
                inputs=[model_dd],
                outputs=[model_ear_btn],
            ).then(
                fn=close_the_flyout,
                outputs=[flyout_visible, active_anchor_id, js_data_bridge],
            ).then(
                fn=None, inputs=[js_data_bridge], js=js_update_flyout
            )

            model_ear_btn.click(
                fn=lambda is_vis, anchor, sel: handle_flyout_toggle(
                    is_vis, anchor, model_dd.elem_id, model_settings_map_py.get(sel)
                ),
                inputs=[flyout_visible, active_anchor_id, model_dd],
                outputs=[
                    flyout_visible,
                    active_anchor_id,
                    flyout_sheet,
                    js_data_bridge,
                ],
            ).then(fn=None, inputs=[js_data_bridge], js=js_update_flyout)

            flyout_sheet.change(
                fn=on_flyout_change,
                inputs=[flyout_sheet, active_anchor_id, sampler_dd, model_dd],
                outputs=None,
            )

            close_btn.click(
                fn=close_the_flyout,
                inputs=None,
                outputs=[flyout_visible, active_anchor_id, js_data_bridge],
            ).then(fn=None, inputs=[js_data_bridge], js=js_update_flyout)

            def initial_flyout_setup(sampler_val, model_val):
                return {
                    sampler_ear_btn: update_ear_visibility(
                        sampler_val, sampler_settings_map_py
                    ),
                    model_ear_btn: update_ear_visibility(
                        model_val, model_settings_map_py
                    ),
                }

            # --- App Load ---
            demo.load(fn=inject_assets, inputs=None, outputs=[html_injector]).then(
                fn=initial_flyout_setup,
                inputs=[sampler_dd, model_dd],
                outputs=[sampler_ear_btn, model_ear_btn],
            ).then(
                fn=None,
                inputs=None,
                outputs=None,
                js="() => { setTimeout(reparent_flyout, 200); }",
            )

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

PropertySheet

Initialization

name	type	default	description
value	typing.Optional[typing.Any][Any, None]	None	The initial dataclass instance to render.
label	str | None	None	The main label for the component, displayed in the accordion header.
root_label	str	"General"	The label for the root group of properties.
show_group_name_only_one	bool	True	If True, only the group name is shown when there is a single group.
root_properties_first	bool	True	If True (default), root-level properties are rendered before nested groups. If False, they are rendered after.
disable_accordion	bool	False	If True, disables the accordion functionality.
visible	bool	True	If False, the component will be hidden.
open	bool	True	If False, the accordion will be collapsed by default.
elem_id	str | None	None	An optional string that is assigned as the id of this component in the DOM.
scale	int | None	None	The relative size of the component in its container.
width	int | str | None	None	The width of the component in pixels.
height	int | str | None	None	The maximum height of the component's content area in pixels before scrolling.
min_width	int | None	None	The minimum width of the component in pixels.
container	bool	True	If True, wraps the component in a container with a background.
elem_classes	list[str] | str | None	None	An optional list of strings that are assigned as the classes of this component in the DOM.

Events

name	description
change	Triggered when the value of the PropertySheet 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 PropertySheet.
expand	This listener is triggered when the PropertySheet is expanded.
collapse	This listener is triggered when the PropertySheet is collapsed.
undo	This listener is triggered when the user clicks the undo button in component.

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, a new, updated instance of the dataclass.
• As input: Should return, the dataclass instance to process.

def predict(
    value: Any
) -> Any:
    return value