Create a product mockup
Apply a design to a product using two reference images.
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- ComfyUI
从代码中调用该模型
以下请求使用与体验区相同的预设图和设置。每次提交都可能开始一次付费运行；如果提交结果未知，请勿自动重试。
1 获取 API 密钥 ↗
What you need
- Runs on
- Comfy Cloud
- 密钥
- COMFY_API_KEY
- 你的文件
- 由代码根据链接上传
需要付费的 Cloud 方案和额度。
# Python 3.10+: pip install comfy-sdk==0.4.0
import os
from comfy_sdk import Comfy
api_key = os.environ.get("COMFY_API_KEY", "").strip()
if not api_key: raise RuntimeError("Set COMFY_API_KEY")
os.environ.setdefault("COMFY_BASE_URL", "https://cloud.comfy.org")
client = Comfy(api_key=api_key)
workflow = client.workflows.from_json({
"9": {
"class_type": "SaveImage",
"inputs": {
"filename_prefix": "Flux2",
"images": [
"62:8",
0
]
},
"_meta": {
"title": "Save Image"
}
},
"42": {
"class_type": "LoadImage",
"inputs": {
"image": "UPLOADED_image1_FILENAME"
},
"_meta": {
"title": "Load Image"
}
},
"46": {
"class_type": "LoadImage",
"inputs": {
"image": "UPLOADED_image2_FILENAME"
},
"_meta": {
"title": "Load Image"
}
},
"62:10": {
"class_type": "VAELoader",
"inputs": {
"vae_name": "flux2-vae.safetensors"
},
"_meta": {
"title": "Load VAE"
}
},
"62:12": {
"class_type": "UNETLoader",
"inputs": {
"unet_name": "flux2_dev_fp8mixed.safetensors",
"weight_dtype": "default"
},
"_meta": {
"title": "Load Diffusion Model"
}
},
"62:13": {
"class_type": "SamplerCustomAdvanced",
"inputs": {
"guider": [
"62:22",
0
],
"latent_image": [
"62:47",
0
],
"noise": [
"62:25",
0
],
"sampler": [
"62:16",
0
],
"sigmas": [
"62:48",
0
]
},
"_meta": {
"title": "SamplerCustomAdvanced"
}
},
"62:16": {
"class_type": "KSamplerSelect",
"inputs": {
"sampler_name": "euler"
},
"_meta": {
"title": "KSamplerSelect"
}
},
"62:22": {
"class_type": "BasicGuider",
"inputs": {
"conditioning": [
"62:39",
0
],
"model": [
"62:93",
0
]
},
"_meta": {
"title": "Basic Guider"
}
},
"62:25": {
"class_type": "RandomNoise",
"inputs": {
"noise_seed": 315616751694460
},
"_meta": {
"title": "RandomNoise"
}
},
"62:26": {
"class_type": "FluxGuidance",
"inputs": {
"conditioning": [
"62:6",
0
],
"guidance": 4
},
"_meta": {
"title": "FluxGuidance"
}
},
"62:38": {
"class_type": "CLIPLoader",
"inputs": {
"clip_name": "mistral_3_small_flux2_fp8.safetensors",
"device": "default",
"type": "flux2"
},
"_meta": {
"title": "Load CLIP"
}
},
"62:39": {
"class_type": "ReferenceLatent",
"inputs": {
"conditioning": [
"62:43",
0
],
"latent": [
"62:40",
0
]
},
"_meta": {
"title": "Set Reference Latent"
}
},
"62:40": {
"class_type": "VAEEncode",
"inputs": {
"pixels": [
"62:41",
0
],
"vae": [
"62:10",
0
]
},
"_meta": {
"title": "VAE Encode"
}
},
"62:41": {
"class_type": "ImageScaleToTotalPixels",
"inputs": {
"image": [
"46",
0
],
"megapixels": 1,
"resolution_steps": 1,
"upscale_method": "area"
},
"_meta": {
"title": "Scale Image to Total Pixels"
}
},
"62:43": {
"class_type": "ReferenceLatent",
"inputs": {
"conditioning": [
"62:26",
0
],
"latent": [
"62:44",
0
]
},
"_meta": {
"title": "Set Reference Latent"
}
},
"62:44": {
"class_type": "VAEEncode",
"inputs": {
"pixels": [
"62:45",
0
],
"vae": [
"62:10",
0
]
},
"_meta": {
"title": "VAE Encode"
}
},
"62:45": {
"class_type": "ImageScaleToTotalPixels",
"inputs": {
"image": [
"42",
0
],
"megapixels": 1,
"resolution_steps": 1,
"upscale_method": "area"
},
"_meta": {
"title": "Scale Image to Total Pixels"
}
},
"62:47": {
"class_type": "EmptyFlux2LatentImage",
"inputs": {
"batch_size": 1,
"height": [
"62:66",
1
],
"width": [
"62:66",
0
]
},
"_meta": {
"title": "Empty Flux 2 Latent"
}
},
"62:48": {
"class_type": "Flux2Scheduler",
"inputs": {
"height": [
"62:66",
1
],
"steps": [
"62:94",
0
],
"width": [
"62:66",
0
]
},
"_meta": {
"title": "Flux2Scheduler"
}
},
"62:6": {
"class_type": "CLIPTextEncode",
"inputs": {
"clip": [
"62:38",
0
],
"text": "Apply the design from Reference Image 1 onto objects in Reference Image 2.\n"
},
"_meta": {
"title": "CLIP Text Encode (Positive Prompt)"
}
},
"62:66": {
"class_type": "GetImageSize",
"inputs": {
"image": [
"62:45",
0
]
},
"_meta": {
"title": "Get Image Size"
}
},
"62:8": {
"class_type": "VAEDecode",
"inputs": {
"samples": [
"62:13",
0
],
"vae": [
"62:10",
0
]
},
"_meta": {
"title": "VAE Decode"
}
},
"62:88": {
"class_type": "LoraLoaderModelOnly",
"inputs": {
"lora_name": "Flux2TurboComfyv2.safetensors",
"model": [
"62:12",
0
],
"strength_model": 1
},
"_meta": {
"title": "Load LoRA"
}
},
"62:90": {
"class_type": "PrimitiveInt",
"inputs": {
"value": 20
},
"_meta": {
"title": "Step"
}
},
"62:92": {
"class_type": "PrimitiveInt",
"inputs": {
"value": 8
},
"_meta": {
"title": "Step"
}
},
"62:93": {
"class_type": "ComfySwitchNode",
"inputs": {
"on_false": [
"62:12",
0
],
"on_true": [
"62:88",
0
],
"switch": [
"62:95",
0
]
},
"_meta": {
"title": "Switch (Model)"
}
},
"62:94": {
"class_type": "ComfySwitchNode",
"inputs": {
"on_false": [
"62:90",
0
],
"on_true": [
"62:92",
0
],
"switch": [
"62:95",
0
]
},
"_meta": {
"title": "Switch (Step)"
}
},
"62:95": {
"class_type": "PrimitiveBoolean",
"inputs": {
"value": False
},
"_meta": {
"title": "Enable 8steps LoRA"
}
}
})
workflow.set_input("42", "image", client.assets.from_url("https://cdn.jsdelivr.net/gh/Comfy-Org/workflow_templates@90c71fb78b3726392d010ff62a8e79e92d7296ad/input/image_flux2_input_ref_image.png"))
workflow.set_input("46", "image", client.assets.from_url("https://cdn.jsdelivr.net/gh/Comfy-Org/workflow_templates@90c71fb78b3726392d010ff62a8e79e92d7296ad/input/image_flux2_input_Illustration.png"))
# run() also passes api_key to the partner nodes in this workflow.
job = client.run(workflow, api_key=api_key)
for output in job.get_outputs("9"):
output.to_file(output.name)