DemonGatanjieuandClaude Opus 5.5
8ecc261949
Every block in api/blocks names what it gives a block after it ("gives": its sampler and its
output node; {} for one that changes the step it is put on) and its own model loader
("own_model"). api/block_chain.py builds a list of steps on a new tab: the picture first, each
next block anchored to what the step before gave, by near_node_id and a new page-only
save_node_id (canvas_roles.js findRoles pins the output node), so a canvas with several
samplers and outputs is no guess. add_nodes' answer names the block it built.
Redraw with another model and face/hand detailing now take the step before's picture
("$save.images") instead of the sampler's decode, which after an enlargement is the older
picture. The two-model routes are built as two-step chains; routes.json no longer names the
loaders.
Checked through the real page on the test ComfyUI: the Tile route on two Anima models (base on
Harem 1.5, Tile redraw on Kirazuri v4, from the base's picture and prompts), then face and hand
detailing after it took the Tile step's colour-matched picture.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
251 lines
6.1 KiB
JSON
251 lines
6.1 KiB
JSON
{
|
||
"job": "picture",
|
||
"rank": 1,
|
||
"short": "a picture from words",
|
||
"standalone": true,
|
||
"title": {
|
||
"zh": "出图",
|
||
"en": "Make a picture"
|
||
},
|
||
"about": {
|
||
"zh": "在空画布上按模型的家族搭好出图的节点：SDXL 一类是一个 checkpoint，Anima 是模型、文本编码器、VAE 三个文件；设置用验证过的那一套。",
|
||
"en": "Builds the nodes that make a picture on an empty canvas, by the model's family: one checkpoint for SDXL and its kin, the model, text encoder and VAE files for Anima; with the tested settings."
|
||
},
|
||
"source": {
|
||
"zh": "ComfyUI 的默认出图流程；Anima 的设置来自你验证过的两段放大卡的底图那一段",
|
||
"en": "ComfyUI's default text-to-image graph; Anima's settings from the base pass of the user's tested two-pass card"
|
||
},
|
||
"packs": {},
|
||
"nodes": {
|
||
"model": {
|
||
"class_type": "CheckpointLoaderSimple",
|
||
"_meta": {
|
||
"title": "Model"
|
||
},
|
||
"inputs": {
|
||
"ckpt_name": "$model"
|
||
}
|
||
},
|
||
"positive": {
|
||
"class_type": "CLIPTextEncode",
|
||
"inputs": {
|
||
"text": "",
|
||
"clip": [
|
||
"model",
|
||
1
|
||
]
|
||
}
|
||
},
|
||
"negative": {
|
||
"class_type": "CLIPTextEncode",
|
||
"inputs": {
|
||
"text": "",
|
||
"clip": [
|
||
"model",
|
||
1
|
||
]
|
||
}
|
||
},
|
||
"size": {
|
||
"class_type": "EmptyLatentImage",
|
||
"inputs": {
|
||
"width": 832,
|
||
"height": 1216,
|
||
"batch_size": 1
|
||
}
|
||
},
|
||
"sampler": {
|
||
"class_type": "KSampler",
|
||
"inputs": {
|
||
"model": [
|
||
"model",
|
||
0
|
||
],
|
||
"positive": [
|
||
"positive",
|
||
0
|
||
],
|
||
"negative": [
|
||
"negative",
|
||
0
|
||
],
|
||
"latent_image": [
|
||
"size",
|
||
0
|
||
],
|
||
"steps": 28,
|
||
"cfg": 5.5,
|
||
"sampler_name": "euler_ancestral",
|
||
"scheduler": "normal",
|
||
"denoise": 1.0
|
||
}
|
||
},
|
||
"decode": {
|
||
"class_type": "VAEDecode",
|
||
"inputs": {
|
||
"samples": [
|
||
"sampler",
|
||
0
|
||
],
|
||
"vae": [
|
||
"model",
|
||
2
|
||
]
|
||
}
|
||
},
|
||
"save": {
|
||
"class_type": "SaveImage",
|
||
"inputs": {
|
||
"images": [
|
||
"decode",
|
||
0
|
||
],
|
||
"filename_prefix": "picture"
|
||
}
|
||
}
|
||
},
|
||
"variants": {
|
||
"anima": {
|
||
"files": {
|
||
"$text_encoder": [
|
||
"CLIPLoader",
|
||
"clip_name",
|
||
[
|
||
"qwen_3_06b",
|
||
"qwen3_06b"
|
||
]
|
||
],
|
||
"$vae": [
|
||
"VAELoader",
|
||
"vae_name",
|
||
[
|
||
"qwenimage",
|
||
"qwen_image"
|
||
]
|
||
]
|
||
},
|
||
"nodes": {
|
||
"model": {
|
||
"class_type": "UNETLoader",
|
||
"_meta": {
|
||
"title": "Model"
|
||
},
|
||
"inputs": {
|
||
"unet_name": "$model",
|
||
"weight_dtype": "default"
|
||
}
|
||
},
|
||
"text_encoder": {
|
||
"class_type": "CLIPLoader",
|
||
"inputs": {
|
||
"clip_name": "$text_encoder",
|
||
"type": "stable_diffusion"
|
||
}
|
||
},
|
||
"vae": {
|
||
"class_type": "VAELoader",
|
||
"inputs": {
|
||
"vae_name": "$vae"
|
||
}
|
||
},
|
||
"positive": {
|
||
"class_type": "CLIPTextEncode",
|
||
"inputs": {
|
||
"text": "",
|
||
"clip": [
|
||
"text_encoder",
|
||
0
|
||
]
|
||
}
|
||
},
|
||
"negative": {
|
||
"class_type": "CLIPTextEncode",
|
||
"inputs": {
|
||
"text": "",
|
||
"clip": [
|
||
"text_encoder",
|
||
0
|
||
]
|
||
}
|
||
},
|
||
"size": {
|
||
"class_type": "EmptyLatentImage",
|
||
"inputs": {
|
||
"width": 832,
|
||
"height": 1216,
|
||
"batch_size": 1
|
||
}
|
||
},
|
||
"sampler": {
|
||
"class_type": "KSampler",
|
||
"inputs": {
|
||
"model": [
|
||
"model",
|
||
0
|
||
],
|
||
"positive": [
|
||
"positive",
|
||
0
|
||
],
|
||
"negative": [
|
||
"negative",
|
||
0
|
||
],
|
||
"latent_image": [
|
||
"size",
|
||
0
|
||
],
|
||
"steps": 35,
|
||
"cfg": 4.4,
|
||
"sampler_name": "dpmpp_2m_sde_gpu",
|
||
"scheduler": "beta",
|
||
"denoise": 1.0
|
||
}
|
||
},
|
||
"decode": {
|
||
"class_type": "VAEDecode",
|
||
"inputs": {
|
||
"samples": [
|
||
"sampler",
|
||
0
|
||
],
|
||
"vae": [
|
||
"vae",
|
||
0
|
||
]
|
||
}
|
||
},
|
||
"save": {
|
||
"class_type": "SaveImage",
|
||
"inputs": {
|
||
"images": [
|
||
"decode",
|
||
0
|
||
],
|
||
"filename_prefix": "picture"
|
||
}
|
||
}
|
||
},
|
||
"after": "The picture's nodes are on the canvas, on the Anima model picked (the loader titled Model), with its text encoder and VAE and the tested sampling (35 steps, dpmpp_2m_sde_gpu, beta, cfg 4.4, 832x1216). run_workflow with prompt and negative fills them in. A style LoRA the user picked: add_lora. A second pass after it (enlarge, another model): add_nodes with that use."
|
||
}
|
||
},
|
||
"after": "The picture's nodes are on the canvas, on the checkpoint picked (the loader titled Model), with common SDXL settings (28 steps, euler_ancestral, cfg 5.5, 832x1216; get_model's author_examples has what the model's author used). run_workflow with prompt and negative fills them in. A style LoRA the user picked: add_lora. A second pass after it (enlarge, another model): add_nodes with that use.",
|
||
"gives": {
|
||
"sampler": "sampler",
|
||
"save": "save"
|
||
},
|
||
"notes": "SDXL's values are common ones, not tested per model here; Anima's are the base pass of the user's tested two-pass card.",
|
||
"tested": {
|
||
"gpu": "RTX 4050 Laptop",
|
||
"vram_gb": 6,
|
||
"date": "2026-11-03",
|
||
"runs": [
|
||
{
|
||
"model": "Anima (MiaoMiao Harem 1.5)",
|
||
"size": "832×1216",
|
||
"seconds": 78
|
||
}
|
||
]
|
||
}
|
||
}
|