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Using ComfyUI Workflows with Zero Experience

It's as easy as using a mini-app. No experience needed.

LiblibAI - A Leading AI Creation Platform in China

Liblib offers many free workflows for advanced image generation tasks like face swapping, model dressing, product photo lighting/backgrounds, and meme creation. There’s a daily free quota, with paid options for heavier use.

ComfyUI is the underlying image generation engine. Don’t worry about the technical details right now:

Liblib’s workflows are essentially ComfyUI programs. You just need to know how to use them, not how to build them. Here are the three scenarios you’ll encounter:

1️⃣ The Workflow Has a “Run” Button

This means the creator packaged the workflow as an app. Click, run, and you’re good to go. You won’t see the underlying complexity.

2️⃣ No App, Just Light Blue Buttons

These buttons open the ComfyUI interface. Expect a black screen and a bit of a wait. It’ll look like a complex circuit board.

Creators usually include instructions. Find and read them—they’ll vary. Example:

3️⃣ Light Blue Buttons, No Instructions

The creator skipped the instructions. First, check the workflow’s complexity.

Tip: Mouse wheel zooms, spacebar + drag moves the view.

If it’s simple (few nodes), you can probably still use it. Look for these two key node types:

  • Image uploads (look for the “choose file to upload” button):
  • Text input (a black input box, usually for prompts):

Upload images, add prompts, and run. It should work.

If it’s too complex, find a different workflow with instructions.


⚠️ Troubleshooting Errors

You might see errors pop up:

Don’t worry! Close the error. The program will highlight the problem node in red:

Zoom in. It’s usually a node for loading an AI model:

The creator likely used their local model file names. These might not match Liblib’s. The node can’t find the correct model.

Here’s the fix: Note the names of each option, especially the part before the decimal (the model name). Click each model and choose the closest match from the dropdown (exact matches are best):

Re-select models for all error nodes, then run again.

This fixes most errors.

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