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enhance-replicate /wan22-comfyui-full-prep:b4419736
Input schema
The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.
| Field | Type | Default value | Description |
|---|---|---|---|
| prompt |
string
|
A baby dressed in a fluffy outfit is gently nose-to-nose with a small kitten. The background is softly blurred, highlighting the tender interaction between them.
|
Text prompt for video generation (only used with default WAN2.2 workflow)
|
| workflow_json |
string
|
{
"6": {
"inputs": {
"text": "A baby dressed in a fluffy outfit is gently nose-to-nose with a small kitten. The background is softly blurred, highlighting the tender interaction between them.",
"clip": [
"12",
0
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"7": {
"inputs": {
"text": "色调艳丽, 过曝, 静态, 细节模糊不清, 字幕, 风格, 作品, 画作, 画面, 静止, 整体发灰, 最差质量, 低质量, JPEG压缩残留, 丑陋的, 残缺的, 多余的手指, 画得不好的手部, 画得不好的脸部, 畸形的, 毁容的, 形态畸形的肢体, 手指融合, 静止不动的画面, 杂乱的背景, 三条腿, 背景人很多, 倒着走",
"clip": [
"12",
0
]
},
"class_type": "CLIPTextEncode",
"_meta": {
"title": "CLIP Text Encode (Prompt)"
}
},
"12": {
"inputs": {
"clip_name": "umt5_xxl_fp8_e4m3fn_scaled.safetensors",
"type": "wan",
"device": "default"
},
"class_type": "CLIPLoader",
"_meta": {
"title": "Load CLIP"
}
},
"14": {
"inputs": {
"vae_name": "wan_2.1_vae.safetensors"
},
"class_type": "VAELoader",
"_meta": {
"title": "Load VAE"
}
},
"44": {
"inputs": {
"add_noise": "disable",
"noise_seed": 270712418741028,
"steps": 8,
"cfg": 1,
"sampler_name": "res_multistep",
"scheduler": "beta",
"start_at_step": 4,
"end_at_step": 10000,
"return_with_leftover_noise": "disable",
"model": [
"48",
0
],
"positive": [
"6",
0
],
"negative": [
"7",
0
],
"latent_image": [
"45",
0
]
},
"class_type": "KSamplerAdvanced",
"_meta": {
"title": "KSampler (Advanced)"
}
},
"45": {
"inputs": {
"add_noise": "enable",
"noise_seed": 868084697386425,
"steps": 8,
"cfg": 1,
"sampler_name": "res_multistep",
"scheduler": "beta",
"start_at_step": 0,
"end_at_step": 4,
"return_with_leftover_noise": "enable",
"model": [
"47",
0
],
"positive": [
"6",
0
],
"negative": [
"7",
0
],
"latent_image": [
"73",
0
]
},
"class_type": "KSamplerAdvanced",
"_meta": {
"title": "KSampler (Advanced)"
}
},
"46": {
"inputs": {
"unet_name": "Wan2.2-T2V-A14B-HighNoise-Q4_K_M.gguf"
},
"class_type": "UnetLoaderGGUF",
"_meta": {
"title": "Unet Loader (GGUF)"
}
},
"47": {
"inputs": {
"shift": 8.000000000000002,
"model": [
"50",
0
]
},
"class_type": "ModelSamplingSD3",
"_meta": {
"title": "ModelSamplingSD3"
}
},
"48": {
"inputs": {
"shift": 8.000000000000002,
"model": [
"51",
0
]
},
"class_type": "ModelSamplingSD3",
"_meta": {
"title": "ModelSamplingSD3"
}
},
"49": {
"inputs": {
"unet_name": "Wan2.2-T2V-A14B-LowNoise-Q4_K_M.gguf"
},
"class_type": "UnetLoaderGGUF",
"_meta": {
"title": "Unet Loader (GGUF)"
}
},
"50": {
"inputs": {
"lora_name": "lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors",
"strength_model": 1.0000000000000002,
"model": [
"58",
0
]
},
"class_type": "LoraLoaderModelOnly",
"_meta": {
"title": "LoraLoaderModelOnly"
}
},
"51": {
"inputs": {
"lora_name": "lightx2v_T2V_14B_cfg_step_distill_v2_lora_rank64_bf16.safetensors",
"strength_model": 1.0000000000000002,
"model": [
"59",
0
]
},
"class_type": "LoraLoaderModelOnly",
"_meta": {
"title": "LoraLoaderModelOnly"
}
},
"58": {
"inputs": {
"lora_name": "Wan2.1_T2V_14B_FusionX_LoRA.safetensors",
"strength_model": 0.5000000000000001,
"model": [
"46",
0
]
},
"class_type": "LoraLoaderModelOnly",
"_meta": {
"title": "LoraLoaderModelOnly"
}
},
"59": {
"inputs": {
"lora_name": "Wan2.1_T2V_14B_FusionX_LoRA.safetensors",
"strength_model": 0.5000000000000001,
"model": [
"49",
0
]
},
"class_type": "LoraLoaderModelOnly",
"_meta": {
"title": "LoraLoaderModelOnly"
}
},
"64": {
"inputs": {
"frame_rate": 8,
"loop_count": 0,
"filename_prefix": "AnimateDiff",
"format": "video/h264-mp4",
"pix_fmt": "yuv420p",
"crf": 19,
"save_metadata": true,
"trim_to_audio": false,
"pingpong": false,
"save_output": true,
"images": [
"71",
0
]
},
"class_type": "VHS_VideoCombine",
"_meta": {
"title": "Video Combine 🎥🅥🅗🅢"
}
},
"65": {
"inputs": {
"tile_size": 512,
"overlap": 64,
"temporal_size": 64,
"temporal_overlap": 8,
"samples": [
"44",
0
],
"vae": [
"14",
0
]
},
"class_type": "VAEDecodeTiled",
"_meta": {
"title": "VAE Decode (Tiled)"
}
},
"69": {
"inputs": {
"upscale_model": [
"70",
0
],
"image": [
"65",
0
]
},
"class_type": "ImageUpscaleWithModel",
"_meta": {
"title": "Upscale Image (using Model)"
}
},
"70": {
"inputs": {
"model_name": "RealESRGAN_x2.pth"
},
"class_type": "UpscaleModelLoader",
"_meta": {
"title": "Load Upscale Model"
}
},
"71": {
"inputs": {
"ckpt_name": "rife47.pth",
"clear_cache_after_n_frames": 10,
"multiplier": 2,
"fast_mode": true,
"ensemble": true,
"scale_factor": 1,
"frames": [
"69",
0
]
},
"class_type": "RIFE VFI",
"_meta": {
"title": "RIFE VFI (recommend rife47 and rife49)"
}
},
"73": {
"inputs": {
"width": 384,
"height": 704,
"length": 41,
"batch_size": 1,
"vae": [
"14",
0
]
},
"class_type": "Wan22ImageToVideoLatent",
"_meta": {
"title": "Wan22ImageToVideoLatent"
}
}
}
|
Your ComfyUI workflow as JSON string or URL. Default: WAN2.2 text-to-video workflow. Get API format from ComfyUI using 'Save (API format)'. Instructions: https://github.com/replicate/cog-comfyui
|
| input_file |
string
|
Input image, video, tar or zip file. Read guidance on workflows and input files here: https://github.com/replicate/cog-comfyui. Alternatively, you can replace inputs with URLs in your JSON workflow and the model will download them.
|
|
| return_temp_files |
boolean
|
False
|
Return any temporary files, such as preprocessed controlnet images. Useful for debugging.
|
| output_format |
None
|
webp
|
Format of the output images
|
| output_quality |
integer
|
95
Max: 100 |
Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.
|
| randomise_seeds |
boolean
|
True
|
Automatically randomise seeds (seed, noise_seed, rand_seed)
|
| force_reset_cache |
boolean
|
False
|
Force reset the ComfyUI cache before running the workflow. Useful for debugging.
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}