Class ComfyUIWorkflow

A class for creating a workflow using a fluent API.

Example

 const workflow = new ComfyUIWorkflow();
 const {
   KSampler,
   CheckpointLoaderSimple,
   EmptyLatentImage,
   CLIPTextEncode,
   VAEDecode,
   SaveImage,
   NODE1,
 } = workflow.classes;

 const seed = Math.floor(Math.random() * 2 ** 32);
 const pos = "best quality, 1girl";
 const neg = "worst quality, bad anatomy, embedding:NG_DeepNegative_V1_75T";
 const model1_name = "lofi_v5.baked.fp16.safetensors";
 const model2_name = "case-h-beta.baked.fp16.safetensors";
 const sampler_settings = {
   seed,
   steps: 35,
   cfg: 4,
   sampler_name: "dpmpp_2m_sde_gpu",
   scheduler: "karras",
   denoise: 1,
 };

 const [model1, clip1, vae1] = CheckpointLoaderSimple({
   ckpt_name: model1_name,
 });
 const [model2, clip2, vae2] = CheckpointLoaderSimple({
   ckpt_name: model2_name,
 });

 const dress_case = [
   "white yoga",
   "black office",
   "pink sportswear",
   "cosplay",
 ];

 const generate_pipeline = (model, clip, vae, pos, neg) => {
   const [latent_image] = EmptyLatentImage({
     width: 640,
     height: 960,
     batch_size: 1,
   });
   const [positive] = CLIPTextEncode({ text: pos, clip });
   const [negative] = CLIPTextEncode({ text: neg, clip });
   const [samples] = KSampler({
     ...sampler_settings,
     model,
     positive,
     negative,
     latent_image,
   });
   const [image] = VAEDecode({ samples, vae });
   return image;
 };

 for (const cloth of dress_case) {
   const input_pos = `${pos}, ${cloth} dress`;
   const image = generate_pipeline(model1, clip1, vae1, input_pos, neg);
   SaveImage({
     images: image,
     filename_prefix: `${cloth}-lofi-v5`,
   });

   const input_pos2 = `${pos}, ${cloth} dress`;
   const image2 = generate_pipeline(model2, clip2, vae2, input_pos2, neg);
   SaveImage({
     images: image2,
     filename_prefix: `${cloth}-case-h-beta`,
   });
 }

 return workflow;
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