Node Settings

overview configure node parameters to control how each node processes data in your workflow understanding parameter types helps you fine tune your ai generation results accessing node settings node settings appear directly in the node body on the canvas click on any parameter field to edit its value for additional options right click on a node select properties from the context menu view and edit all node properties parameter types nodes use different parameter types depending on what kind of input they need numeric parameters type description example values integer (int) whole numbers only 1, 512, 1024 float (float) decimal numbers 0 5, 7 5, 0 75 seed random seed for generation any integer; 1 for random numeric fields often have constraints min/max values limits the range you can enter step controls increment when using arrows or sliders 💡 tip use the same seed value to reproduce identical results set seed to 1 for random generation each run text parameters type description example string single line text input filenames, simple values text (multiline) multi line text area prompts, descriptions selection parameters type description how to use dropdown choose from predefined options click to open list, select option combo select from available items often populated dynamically (e g , model lists) boolean parameters value meaning true / on feature enabled false / off feature disabled toggle by clicking the checkbox or switch common node parameters sampler nodes parameter type description steps integer number of denoising steps (more = higher quality, slower) cfg float classifier free guidance scale (how closely to follow prompt) sampler name dropdown which sampling algorithm to use scheduler dropdown how to schedule the denoising process denoise float amount of noise to remove (1 0 = full generation) image size nodes parameter type description width integer image width in pixels height integer image height in pixels batch size integer number of images to generate loader nodes parameter type description ckpt name combo checkpoint model to load lora name combo lora model to apply strength float how strongly to apply the lora input types inputs on the left side of nodes accept connections from other nodes input appearance meaning solid dot required input (must be connected) hollow dot / ring optional input (can be left empty) optional inputs allow the node to run with default behavior when not connected widgets vs inputs some parameters can work as both widgets (editable in the node) and inputs (connected from another node) widget mode edit the value directly in the node input mode value comes from a connected node right click on convertible parameters to toggle between modes tips & best practices start with defaults most nodes have sensible defaults; adjust after seeing initial results small changes adjust one parameter at a time to understand its effect save presets note down parameter combinations that work well for your use cases check tooltips hover over parameters for descriptions of what they do troubleshooting parameter won't accept my value? solution the value may be outside the allowed range check for min/max constraints on numeric fields dropdown is empty? solution the dropdown may populate from loaded resources ensure required models or files are loaded earlier in the workflow changes not taking effect? solution re run the workflow after changing parameters some changes only apply on the next execution related documentation https //docs floyo ai/nodes https //docs floyo ai/adding nodes https //docs floyo ai/core nodes vs custom nodes https //docs floyo ai/running workflows