LoadAndSettingParameters01
The integrated preset node that lets tweaks stick
- POS A
- POS C
- NEG A
- NEG C
- ckpt_name
- stop_at_clip_layer
- vae
- Steps
- CFG
- sampler_name
- scheduler
This is the version that answers the complaint the split design creates: "I fixed the clip skip and it reverted anyway." LoadAndSettingParameters01 merges the preset picker and the parameter display into a single node, and it changes when the preset applies - which is the whole point.
What's different from the two-node setup
In the split design (LoadPresetForSetting01 + SettingParameters01), the preset is re-read at queue execution, so manual edits get overwritten. Here, the preset only rewrites the widgets at the moment you pick it from the dropdown. After that, whatever's on the widgets is what runs. Tweak ClipNum from -2 to -1, bump CFG a bit, fine-tune the prompt - it sticks. The README positions this as the fine-tuning-friendly option, and it earns that.
The tradeoff the author is honest about: the node auto-selects a preset when it's created. That means if you drag an image back into ComfyUI to rebuild the workflow from its embedded metadata, the node re-applies the preset and wipes your values. That's the exact scenario where the split version behaves better. So the rule of thumb: live-tweaking one graph in front of you → use this; repeatedly loading saved workflows → the split version's predictable queue-time behavior is what you actually want.
How it works
Same websocket handshake as the rest of the pack: the Python side pushes a my.custom.message to the frontend, js/web.js rewrites the widget values, and the node returns whatever the widgets show. The preset fires when the dropdown value changes, not on every queue.
The output roster matches SettingParameters01:
- POS A / POS C / NEG A / NEG C - four text prompts for your CLIPTextEncode nodes.
- ckpt_name →
CheckpointLoaderSimple'sckpt_nameinput. - stop_at_clip_layer (INT) →
CLIPSetLastLayer. Negative numbering, default -1; -2 is the classic anime/Pony value. - vae - a genuinely loaded VAE object, straight into
VAEDecode. - Steps / CFG / sampler_name / scheduler →
KSampler.
For the KSampler and CheckpointLoaderSimple connections, right-click → Convert Widget to Input on the target widgets first - the README shows exactly this for ckpt_name.
Install
Via ComfyUI Manager (search "ComfyUI_mittimiLoadPreset"), or manually:
cd ComfyUI/custom_nodes
git clone https://github.com/mittimi/ComfyUI_mittimiLoadPreset
Restart ComfyUI. Only dependency is toml, no model downloads.
Before you commit
The README's top banner says this pack is retired in favor of ComfyUI_mittimiLoadPreset2 and won't receive updates. For a one-off workflow it's perfectly serviceable; if you're building something you'll maintain, v2 is the path the author is actually supporting.
Inputs (12)
| Name | Type | Default | Description |
|---|---|---|---|
| preset | COMBO | 3 options: (testing)preset.toml, PRESET TEMPLATE.toml, [Sample] PonyRealismSetting.toml | |
| PosPromptA | STRING | — | |
| PosPromptC | STRING | — | |
| NegPromptA | STRING | — | |
| NegPromptC | STRING | — | |
| checkpoint_name | COMBO | 0 options: | |
| ClipNum | INT | -1-10–-1 | — |
| vae_name | COMBO | 0 options: | |
| Steps | INT | — | |
| CFG | FLOAT | — | |
| SamplerName | COMBO | 34 options: euler, euler_cfg_pp, euler_ancestral, euler_ancestral_cfg_pp, heun, heunpp2, +28 | |
| Scheduler | COMBO | 9 options: normal, karras, exponential, sgm_uniform, simple, ddim_uniform, +3 |
Outputs (11)
| Name | Type | Description |
|---|---|---|
| POS A | STRING | — |
| POS C | STRING | — |
| NEG A | STRING | — |
| NEG C | STRING | — |
| ckpt_name | — | |
| stop_at_clip_layer | INT | — |
| vae | VAE | — |
| Steps | INT | — |
| CFG | FLOAT | — |
| sampler_name | euler,euler_cfg_pp,euler_ancestral,euler_ancestral_cfg_pp,heun,heunpp2,dpm_2,dpm_2_ancestral,lms,dpm_fast,dpm_adaptive,dpmpp_2s_ancestral,dpmpp_2s_ancestral_cfg_pp,dpmpp_sde,dpmpp_sde_gpu,dpmpp_2m,dpmpp_2m_cfg_pp,dpmpp_2m_sde,dpmpp_2m_sde_gpu,dpmpp_3m_sde,dpmpp_3m_sde_gpu,ddpm,lcm,ipndm,ipndm_v,deis,res_multistep,res_multistep_cfg_pp,res_multistep_ancestral,res_multistep_ancestral_cfg_pp,gradient_estimation,ddim,uni_pc,uni_pc_bh2 | — |
| scheduler | normal,karras,exponential,sgm_uniform,simple,ddim_uniform,beta,linear_quadratic,kl_optimal | — |