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
```bash
pip install gradio_propertysheet
```
## Usage
```python
import os
import json
import gradio as gr
from dataclasses import dataclass, field, asdict
from typing import Literal
from gradio_propertysheet import PropertySheet
from gradio_htmlinjector import HTMLInjector
# --- 1. Dataclass Definitions (unchanged) ---
@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", # string normal
"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."
}
)
# Option 1: Literal values
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'."
}
)
# Option 2: neq operand
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."
}
)
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,
"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,
"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 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"}
)
quantization: QuantizationSettings = field(
default_factory=QuantizationSettings,
metadata={"label": "Quantization 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 (unchanged) ---
initial_render_config = RenderConfig()
initial_env_config = EnvironmentConfig()
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 (unchanged) ---
def inject_assets():
"""
This function prepares the payload of CSS, JS, and Body HTML for injection.
"""
popup_html = """"""
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."
)
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 = 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")
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
)
def change_visibility(is_visible, render_cfg, env_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(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
generate.click(
fn=change_visibility,
inputs=[sidebar_visible, render_state, env_state],
outputs=[sidebar_visible, render_sheet, environment_sheet, generate],
)
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],
)
#In version 0.0.7, I moved the undo function to a new `undo` event. This was necessary to avoid conflict with the `change` event where it was previously implemented.
# Now you need to implement the undo event for the undo button to work. You can simply receive the component as input and set it as output.
def render_undo(updated_config: RenderConfig, current_state: RenderConfig):
if updated_config is None:
return current_state, asdict(current_state), current_state
return updated_config, asdict(updated_config), current_state
def environment_undo(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
render_sheet.undo(fn=render_undo,
inputs=[render_sheet, render_state],
outputs=[render_sheet, output_render_json, render_state]
)
environment_sheet.undo(fn=environment_undo,
inputs=[environment_sheet, env_state],
outputs=[environment_sheet, output_env_json, env_state],
)
demo.load(
fn=lambda r_cfg, e_cfg: (asdict(r_cfg), asdict(e_cfg)),
inputs=[render_state, env_state],
outputs=[output_render_json, output_env_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 |
```python typing.Optional[typing.Any][Any, None] ``` | None |
The initial dataclass instance to render. |
label |
```python str | None ``` | None |
The main label for the component, displayed in the accordion header. |
root_label |
```python str ``` | "General" |
The label for the root group of properties. |
show_group_name_only_one |
```python bool ``` | True |
If True, only the group name is shown when there is a single group. |
root_properties_first |
```python bool ``` | True |
If True (default), root-level properties are rendered before nested groups. If False, they are rendered after. |
disable_accordion |
```python bool ``` | False |
If True, disables the accordion functionality. |
visible |
```python bool ``` | True |
If False, the component will be hidden. |
open |
```python bool ``` | True |
If False, the accordion will be collapsed by default. |
elem_id |
```python str | None ``` | None |
An optional string that is assigned as the id of this component in the DOM. |
scale |
```python int | None ``` | None |
The relative size of the component in its container. |
width |
```python int | str | None ``` | None |
The width of the component in pixels. |
height |
```python int | str | None ``` | None |
The maximum height of the component's content area in pixels before scrolling. |
min_width |
```python int | None ``` | None |
The minimum width of the component in pixels. |
container |
```python bool ``` | True |
If True, wraps the component in a container with a background. |
elem_classes |
```python list[str] | str | None ``` | None |
An optional list of strings that are assigned as the classes of this component in the DOM. |