Flux.1 Dev USO Reference Image Generation

# 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": "ComfyUI",
            "images": [
                "112:8",
                0
            ]
        },
        "_meta": {
            "title": "Save Image"
        }
    },
    "47": {
        "class_type": "LoadImage",
        "inputs": {
            "image": "UPLOADED_image_FILENAME"
        },
        "_meta": {
            "title": "Load Image"
        }
    },
    "112:109": {
        "class_type": "ImageScaleToMaxDimension",
        "inputs": {
            "image": [
                "47",
                0
            ],
            "largest_size": 512,
            "upscale_method": "area"
        },
        "_meta": {
            "title": "Scale Image to Max Dimension"
        }
    },
    "112:110": {
        "class_type": "EmptySD3LatentImage",
        "inputs": {
            "batch_size": 1,
            "height": 768,
            "width": 1344
        },
        "_meta": {
            "title": "EmptySD3LatentImage"
        }
    },
    "112:30": {
        "class_type": "CheckpointLoaderSimple",
        "inputs": {
            "ckpt_name": "flux1-dev-fp8.safetensors"
        },
        "_meta": {
            "title": "Load Checkpoint"
        }
    },
    "112:31": {
        "class_type": "KSampler",
        "inputs": {
            "cfg": 1,
            "denoise": 1,
            "latent_image": [
                "112:110",
                0
            ],
            "model": [
                "112:43",
                0
            ],
            "negative": [
                "112:48",
                0
            ],
            "positive": [
                "112:57:35",
                0
            ],
            "sampler_name": "euler",
            "scheduler": "simple",
            "seed": 1058487910949722,
            "steps": 20
        },
        "_meta": {
            "title": "KSampler"
        }
    },
    "112:39": {
        "class_type": "ModelPatchLoader",
        "inputs": {
            "name": "uso-flux1-projector-v1.safetensors"
        },
        "_meta": {
            "title": "Load Model Patch"
        }
    },
    "112:40": {
        "class_type": "CLIPVisionLoader",
        "inputs": {
            "clip_name": "sigclip_vision_patch14_384.safetensors"
        },
        "_meta": {
            "title": "Load CLIP Vision"
        }
    },
    "112:43": {
        "class_type": "LoraLoaderModelOnly",
        "inputs": {
            "lora_name": "uso-flux1-dit-lora-v1.safetensors",
            "model": [
                "112:30",
                0
            ],
            "strength_model": 1
        },
        "_meta": {
            "title": "Load LoRA"
        }
    },
    "112:48": {
        "class_type": "ConditioningZeroOut",
        "inputs": {
            "conditioning": [
                "112:6",
                0
            ]
        },
        "_meta": {
            "title": "Conditioning Zero Out"
        }
    },
    "112:51": {
        "class_type": "VAEEncode",
        "inputs": {
            "pixels": [
                "112:109",
                0
            ],
            "vae": [
                "112:30",
                2
            ]
        },
        "_meta": {
            "title": "VAE Encode"
        }
    },
    "112:57:35": {
        "class_type": "FluxGuidance",
        "inputs": {
            "conditioning": [
                "112:57:41",
                0
            ],
            "guidance": 3.5
        },
        "_meta": {
            "title": "FluxGuidance"
        }
    },
    "112:57:41": {
        "class_type": "FluxKontextMultiReferenceLatentMethod",
        "inputs": {
            "conditioning": [
                "112:57:44",
                0
            ],
            "reference_latents_method": "uxo/uno"
        },
        "_meta": {
            "title": "Edit Model Reference Method"
        }
    },
    "112:57:44": {
        "class_type": "ReferenceLatent",
        "inputs": {
            "conditioning": [
                "112:6",
                0
            ],
            "latent": [
                "112:51",
                0
            ]
        },
        "_meta": {
            "title": "Set Reference Latent"
        }
    },
    "112:6": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "112:30",
                1
            ],
            "text": "The same man from the reference photo, with the same face, eyes, stubble and wavy dark hair, now standing at the stern of a small wooden fishing boat at first light. He wears a heavy cream cable-knit sweater and an oilskin apron, sleeves pushed up, coiling a wet rope over one forearm and looking straight towards the camera with a calm, tired expression. Behind him a grey-green sea rolls under low clouds, gulls hang above the wake, and a rocky headland with a white lighthouse sits on the horizon. Cold dawn light comes from the left, catching salt spray on his face and the wet planks of the deck. Live-action documentary photograph, 35mm lens, natural colour, crisp detail on the knit and the rope, shallow depth of field on the far coastline."
        },
        "_meta": {
            "title": "CLIP Text Encode (Positive Prompt)"
        }
    },
    "112:8": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "112:31",
                0
            ],
            "vae": [
                "112:30",
                2
            ]
        },
        "_meta": {
            "title": "VAE Decode"
        }
    }
})
workflow.set_input("47", "image", client.assets.from_url("https://comfy.org/catalog-media/c94b548e-618e-481c-8ed2-fdf58b7b3f68/48639183-6716-4e49-9464-3f0958da2c31"))

# 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)