{
  "prompt": {
    "1": {
      "class_type": "UNETLoader",
      "inputs": {
        "unet_name": "flux-2-klein-4b-fp8.safetensors",
        "weight_dtype": "default"
      }
    },
    "2": {
      "class_type": "CLIPLoader",
      "inputs": {
        "clip_name": "qwen_3_4b.safetensors",
        "type": "flux2",
        "device": "default"
      }
    },
    "3": {
      "class_type": "VAELoader",
      "inputs": {
        "vae_name": "flux2-vae.safetensors"
      }
    },
    "4": {
      "class_type": "CLIPTextEncode",
      "inputs": {
        "text": "High-fidelity photographic wardrobe edit of the reference, with the garment design as the only substantive change. Keep the same face, exact expression and gaze, black hair, skin tone, anatomy, body proportions, original hand and finger placement, elbow bend, clear umbrella and ribs, rainy neon street, train and background lights. Keep the original camera viewpoint and framing. New garments must be coherent three-dimensional clothing with correct seams, collars, closures, fabric weight, fit and folds; adapt them to the existing pose rather than changing her body. Match the original wet-street lighting and reflections. No beauty retouch, no captions, no logos. Wardrobe design: A luxurious deep-emerald velvet evening gown with a modest wide boat neckline, long fitted sleeves, a subtly shaped waist and one elegant diagonal draped fold across the bodice, small cream pearl drop earrings. The visible upper-body silhouette must remain consistent with her original anatomy and pose. Rich directional velvet highlights catch the existing cyan and pink city reflections without turning the fabric metallic. Refined formal evening styling, no tiara, no gloves, no facial or hair changes.",
        "clip": [
          "2",
          0
        ]
      }
    },
    "5": {
      "class_type": "ConditioningZeroOut",
      "inputs": {
        "conditioning": [
          "4",
          0
        ]
      }
    },
    "6": {
      "class_type": "EmptyFlux2LatentImage",
      "inputs": {
        "width": 1008,
        "height": 576,
        "batch_size": 1
      }
    },
    "7": {
      "class_type": "RandomNoise",
      "inputs": {
        "noise_seed": 20263008
      }
    },
    "8": {
      "class_type": "KSamplerSelect",
      "inputs": {
        "sampler_name": "euler"
      }
    },
    "9": {
      "class_type": "Flux2Scheduler",
      "inputs": {
        "steps": 4,
        "width": 1008,
        "height": 576
      }
    },
    "10": {
      "class_type": "CFGGuider",
      "inputs": {
        "model": [
          "1",
          0
        ],
        "positive": [
          "22",
          0
        ],
        "negative": [
          "23",
          0
        ],
        "cfg": 1.0
      }
    },
    "11": {
      "class_type": "SamplerCustomAdvanced",
      "inputs": {
        "noise": [
          "7",
          0
        ],
        "guider": [
          "10",
          0
        ],
        "sampler": [
          "8",
          0
        ],
        "sigmas": [
          "9",
          0
        ],
        "latent_image": [
          "6",
          0
        ]
      }
    },
    "12": {
      "class_type": "VAEDecode",
      "inputs": {
        "samples": [
          "11",
          0
        ],
        "vae": [
          "3",
          0
        ]
      }
    },
    "13": {
      "class_type": "SaveImage",
      "inputs": {
        "images": [
          "12",
          0
        ],
        "filename_prefix": "spark_demos/outfits_10_refined/09_evening"
      }
    },
    "20": {
      "class_type": "LoadImage",
      "inputs": {
        "image": "ref_01.png"
      }
    },
    "21": {
      "class_type": "VAEEncode",
      "inputs": {
        "pixels": [
          "20",
          0
        ],
        "vae": [
          "3",
          0
        ]
      }
    },
    "22": {
      "class_type": "ReferenceLatent",
      "inputs": {
        "conditioning": [
          "4",
          0
        ],
        "latent": [
          "21",
          0
        ]
      }
    },
    "23": {
      "class_type": "ReferenceLatent",
      "inputs": {
        "conditioning": [
          "5",
          0
        ],
        "latent": [
          "21",
          0
        ]
      }
    }
  }
}