💡 Auto Generate

Auto Generate is the pack's "one node, one image" box - the closest thing SDVN offers to an Automatic1111 generate button. You give it a model, a CLIP, a VAE, and a prompt, and it figures out the sampler, scheduler, CFG, step count, and upscale path on its own, then hands back a finished image. For anyone who bounced off ComfyUI because a basic text-to-image graph is a dozen wired nodes, this is the pack collapsing that whole graph into a single node.

The intelligence is in the auto-detection. It reads what kind of model you fed it - SD 1.5, SDXL, Flux - and sets the KSampler, scheduler, and CFG to sane values for that family, so you're not looking up "good settings for Flux" for the hundredth time. It adjusts steps by denoise using the pack's Step = Steps × Denoise rule, so a low-denoise pass doesn't waste full steps. It detects the prompt's language and translates to English. It supports dynamic prompts (turn on Random_prompt and feed a wildcard list to get variation each run). And crucially, it switches modes based on what you plug in: hand it an image and it becomes img2img; add a mask and it becomes inpaint; set Inpaint_model on if your checkpoint is an actual inpaint/fill model and it applies the optimal parameters for that.

The inputs a beginner touches are the obvious ones: model, clip, vae, Prompt, Negative, Image_size (a width,height string, default 1024,1024), Steps, and Denoise. Everything else can stay on its defaults until you need it. When you do need control, flip AdvSetting on and the manual knobs come alive - sampler_name, scheduler, cfg, FluxGuidance, and an Upscale_model picker - letting you override the auto choices. Auto_hires turns on the built-in hires-fix / upscale pass, Kontext_model flags the graph for a Kontext-style edit model, and the optional parameter input (type PARAMETER) is how you feed in ControlNet or Apply-Style settings exported from the pack's other nodes, joined together if you have several. The single image output is your result.

Who it's for: this is a beginner-onboarding node and an idea-sketching node, not a precision instrument. The ComfyUI community's own long-running complaint is that the tool has no natural beginner mode - every shared workflow assumes you already have the right nodes and know why they're wired that way - and Auto Generate is one answer to that, trading fine control for "type a prompt, get a picture." The flip side is the usual flip side of magic boxes: when the auto-detection guesses wrong, or you want a specific sampler the preset didn't pick, you're reaching for AdvSetting and half the convenience evaporates. Power users will still build the graph by hand. That's fine - the two audiences are different.

Install is the pack's shared path. ComfyUI Manager, search SDVN_Comfy_node; or cd ComfyUI/custom_nodes && git clone https://github.com/StableDiffusionVN/SDVN_Comfy_node, then pip install -r custom_nodes/SDVN_Comfy_node/requirements.txt from your ComfyUI root and restart. For the full feature set the README asks for a few companions - Dynamicprompts for the wildcards, TiledDiffusion for tiled upscaling, controlnet_aux if you're feeding it ControlNet parameters - and aria2c on Windows/macOS for the auto-download of upscale models.

One honest expectation-setter, since you likely landed here from a search: SDVN is a pack from the Vietnamese Stable Diffusion community (stablediffusion.vn), and it has almost no footprint in English-language r/comfyui discussion, so you won't find a stack of tutorials for this node. Judge it by dropping it in. If it saves you from wiring a graph, great; if you already think in graphs, it won't change your life. Troubleshooting-wise, the thing that bites is a wrong Image_size format (it wants width,height as a string) and expecting a negative prompt to matter on Flux, where the model ignores it.