There are many nodes available for use within the Workflow Editor, but several nodes will be used the most often
Denoising Latents & Noise
The Denoise Latents node is a central node in the Workflow Editor. The node takes many different inputs including the positive & negative conditioning, initial random noise, as well as any ControlNets, IP-Adapter or masks that might be used.
Generally, the Denoise Latents node will be connected to a Noise node. This Noise node creates a noised image of the selected width and height. To use a random seed to created the noised image, a Random Integer node can be connected the Noise node.This is shown in the image below:
Model Loading, Prompts & Conditioning
Model loading is done through the Main Model node. The CLIP will usually connect to the Prompt nodes, with the UNet being passed to the Denoise Latents node.
Conditioning is necessary for the latent diffusion process, whether empty or not. As a result, the Denoising node requires positive and negative conditioning inputs. Conditioning is reliant on a CLIP text encoder provided by the Model Loader node. This is show in image below:
ControlNets
The ControlNet node outputs a Control, which can be provided as input to a Denoise Latents node. Depending on the type of ControlNet desired, ControlNet nodes might require an image processor node, such as a Canny, Depth or OpenPose Processor, which prepares an input image for use with ControlNet. Multiple ControlNets can be used together by passing the ControlNets into a Collection node and passing the collection to the Denoise Latents node, as show below.
LoRAs
The Lora Loader node lets you load a LoRA and pass it as output. The LoRA node is used similarly to the Main Model Loader node, but sits in-between the Prompt nodes and the Main Model node.
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