The first release includes the helper nodes created for the advanced Z-Image Base / Z-Image Turbo PiD workflow, but the package name is intentionally broad so more EmberFrame nodes can be added later.

Nodes

EmberFrame SamplerCustomAdvanced Capture
EmberFrame Normalize ZImage/Flux Latent
EmberFrame Attach Sigma To Latent
EmberFrame Latent Capture Inspector
EmberFrame Sequential Wildcard Prompt
EmberFrame Wildcard Rule Builder
EmberFrame Wildcard Config Combiner
EmberFrame Wildcard Prompt Assembler
EmberFrame MP Aspect Resolution Selector

The pack also includes the small wildcard text files directly referenced by the example workflow:

framing_wildcard.txt
camera_angle_wildcard.txt
lingerie.txt
Prompt_Civit_connoisseur34_07.txt

What This Does Not Include

This pack does not include NVIDIA PiD, PiD checkpoints, Z-Image models, VAE files, upscalers, ControlNet models, or the Merserk ComfyUI-PiD wrapper.

The example workflow still needs its larger external node packs, including ComfyUI-PiD, rgthree-comfy, ComfyUI-Image-Saver, ComfyUI-Easy-Use, ComfyUI-KJNodes, RES4LYF, ControlNet/Depth nodes, SeedVR2, Ultimate SD Upscale, and the other packs listed inside the workflow note.

This pack replaces the separate lightweight/helper packs:

ComfyUI-PiD-AdvancedSampler
ComfyUI-SequentialWildcardPrompt
ComfyUI-WildcardPromptAssembler
ComfyUI-WildcardPromptToolkit
mp_aspect_res_selector

Install

Copy or clone this folder into:

ComfyUI/custom_nodes/emberframe-nodes

Restart Comfy. The new nodes appear under:

EmberFrame/PiD
EmberFrame/Prompt
EmberFrame/Resolution

Z-Image / Flux PiD Scale Rule

For Z-Image / Flux PiD, treat PiD as a 4x decoder:

scale = 4

Both 2k and 2kto4k are sr4x checkpoints. 2kto4k means a higher-resolution 4x decoder, not a 2x decoder.

Known-good examples:

Want about 1088 x 1920 final:
Generate around 272 x 480, then PiD scale = 4, ckpt = 2k.

Want about 2176 x 3840 final:
Generate around 544 x 960, then PiD scale = 4, ckpt = 2kto4k.

Using scale = 1 or scale = 2 with Z-Image / Flux PiD can produce warped or distorted images.

Working Final-Latent PiD Path

This is the simplest path that worked well in testing:

ZiB sampler output
  -> ZiT sampler latent_image

ZiT sampler output or denoised_output
  -> EmberFrame Normalize ZImage/Flux Latent
  -> PiD Decode latent

VAE Decode of ZiT output
  -> optional preview / baseline_image

Recommended PiD settings:

backbone = zimage
pid_ckpt_type = 2k or 2kto4k
pid_steps = 4
scale = 4
cfg_scale = 1
sigma = 0

For final latent use, keep EmberFrame Normalize ZImage/Flux Latent set to:

direction = comfy_to_pid
scale_factor = 0.3611
shift_factor = 0.1159

Intermediate Capture Path

The capture node can also capture intermediate sampler state:

ZiT EmberFrame SamplerCustomAdvanced Capture pid_latent
  -> PiD Prepare latent

ZiT EmberFrame SamplerCustomAdvanced Capture pid_sigma
  -> PiD Prepare sigma

PiD Prepare
  -> PiD Sample
  -> PiD Finalize

Useful diagnostic settings:

capture_tensor_source = x
sigma_source = next
capture_debug = true

If you feed output, denoised_output, or capture_tensor_source = final_latent into PiD, normalize it first with EmberFrame Normalize ZImage/Flux Latent. If you feed callback x directly, test before adding normalization, because callback x is already in the sampler/model latent space.

Good things to publish:

this custom node code
README / install notes
sanitized example screenshots
sanitized example workflow JSON

Do not publish:

downloaded PiD checkpoints
Z-Image / Flux checkpoints
.safetensors, .ckpt, .pth, .pt, .gguf, or model folders
generated images if they contain private metadata or prompts
workflow JSON containing private prompts, personal file paths, API keys, private model paths, or paid/private model names
your full Comfy portable folder

Before publishing, review wildcard text files and workflow prompts. Remove anything you do not want to make public.

License Notes

This pack is GPL-3.0 because the sampler-capture node mirrors behavior from Comfy's GPL-3.0 sampler implementation.

The Merserk ComfyUI-PiD wrapper is MIT licensed and NVIDIA PiD weights/checkpoints may have separate model-card terms. Do not redistribute model weights in this repository.

README.md

EmberFrame Nodes