Qwen-Image 2512 Turbo

# 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({
    "103": {
        "class_type": "VAELoader",
        "inputs": {
            "vae_name": "qwen_image_vae.safetensors"
        },
        "_meta": {
            "title": "Load VAE"
        }
    },
    "104": {
        "class_type": "CLIPLoader",
        "inputs": {
            "clip_name": "qwen_2.5_vl_7b_fp8_scaled.safetensors",
            "device": "default",
            "type": "qwen_image"
        },
        "_meta": {
            "title": "Load CLIP"
        }
    },
    "105": {
        "class_type": "UNETLoader",
        "inputs": {
            "unet_name": "qwen_image_2512_fp8_e4m3fn.safetensors",
            "weight_dtype": "default"
        },
        "_meta": {
            "title": "Load Diffusion Model"
        }
    },
    "106": {
        "class_type": "KSampler",
        "inputs": {
            "cfg": 1,
            "denoise": 1,
            "latent_image": [
                "107",
                0
            ],
            "model": [
                "110",
                0
            ],
            "negative": [
                "128",
                0
            ],
            "positive": [
                "108",
                0
            ],
            "sampler_name": "euler",
            "scheduler": "simple",
            "seed": 318036859179089,
            "steps": 2
        },
        "_meta": {
            "title": "KSampler"
        }
    },
    "107": {
        "class_type": "EmptySD3LatentImage",
        "inputs": {
            "batch_size": 1,
            "height": 928,
            "width": 1664
        },
        "_meta": {
            "title": "EmptySD3LatentImage"
        }
    },
    "108": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "104",
                0
            ],
            "text": "A high-fashion editorial photograph captured from an extreme low-angle distance with a 24mm ultra-wide lens, featuring a solitary model posed dynamically across an expansive stark white salt flat under a blinding, high-noon sun. The model wears a sculptural crimson structured coat made of matte neoprene, layered over a gleaming liquid-mercury chrome corset and billowing saffron pleated organza trousers that catch the arid desert breeze. Bleached crystalline ground cracks extend diagonally toward a distant, razor-sharp mountain horizon, creating a striking graphic tension. Hard, cutting sunlight casts razor-edged, elongated shadows across the sun-baked mineral crust. The composition balances vast negative space with vivid saturated warmth, sharp geometric forms, and high-contrast editorial clarity across the panoramic desert expanse."
        },
        "_meta": {
            "title": "CLIP Text Encode (Positive Prompt)"
        }
    },
    "109": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "106",
                0
            ],
            "vae": [
                "103",
                0
            ]
        },
        "_meta": {
            "title": "VAE Decode"
        }
    },
    "110": {
        "class_type": "ModelSamplingAuraFlow",
        "inputs": {
            "model": [
                "114",
                0
            ],
            "sampling": "flow",
            "shift": 3
        },
        "_meta": {
            "title": "ModelSamplingAuraFlow"
        }
    },
    "114": {
        "class_type": "LoraLoaderModelOnly",
        "inputs": {
            "lora_name": "Wuli-Qwen-Image-2512-Turbo-LoRA-2steps-V1.0-bf16.safetensors",
            "model": [
                "105",
                0
            ],
            "strength_model": 1
        },
        "_meta": {
            "title": "Load LoRA"
        }
    },
    "123": {
        "class_type": "SaveImage",
        "inputs": {
            "filename_prefix": "Qwen-2512-2steps-LoRA",
            "images": [
                "109",
                0
            ]
        },
        "_meta": {
            "title": "Save Image"
        }
    },
    "128": {
        "class_type": "ConditioningZeroOut",
        "inputs": {
            "conditioning": [
                "108",
                0
            ]
        },
        "_meta": {
            "title": "Conditioning Zero Out"
        }
    }
})

# 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("123"):
    output.to_file(output.name)