1.1 Starter - Text to Image

# 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({
    "76": {
        "class_type": "SaveImage",
        "inputs": {
            "filename_prefix": "comfyui-airport-editorial",
            "images": [
                "30:43",
                0
            ]
        },
        "_meta": {
            "title": "Save Image"
        }
    },
    "30:39": {
        "class_type": "CLIPLoader",
        "inputs": {
            "clip_name": "qwen_3_4b.safetensors",
            "device": "default",
            "type": "lumina2"
        },
        "_meta": {
            "title": "Load CLIP"
        }
    },
    "30:40": {
        "class_type": "VAELoader",
        "inputs": {
            "vae_name": "ae.safetensors"
        },
        "_meta": {
            "title": "Load VAE"
        }
    },
    "30:41": {
        "class_type": "EmptySD3LatentImage",
        "inputs": {
            "batch_size": 1,
            "height": 1088,
            "width": 1920
        },
        "_meta": {
            "title": "EmptySD3LatentImage"
        }
    },
    "30:42": {
        "class_type": "ConditioningZeroOut",
        "inputs": {
            "conditioning": [
                "30:45",
                0
            ]
        },
        "_meta": {
            "title": "Conditioning Zero Out"
        }
    },
    "30:43": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "30:44",
                0
            ],
            "vae": [
                "30:40",
                0
            ]
        },
        "_meta": {
            "title": "VAE Decode"
        }
    },
    "30:44": {
        "class_type": "KSampler",
        "inputs": {
            "cfg": 1,
            "denoise": 1,
            "latent_image": [
                "30:41",
                0
            ],
            "model": [
                "30:47",
                0
            ],
            "negative": [
                "30:42",
                0
            ],
            "positive": [
                "30:45",
                0
            ],
            "sampler_name": "res_multistep",
            "scheduler": "simple",
            "seed": 336703310549440,
            "steps": 8
        },
        "_meta": {
            "title": "KSampler"
        }
    },
    "30:45": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "30:39",
                0
            ],
            "text": "A high-fashion editorial photograph captures an avant-garde model reclining elongated across an expansive expanse of stark negative space against a bold, flat electric-cerulean backdrop. Hard, unyielding direct studio strobe lighting casts razor-sharp, pitch-black shadows across the seamless paper, creating an intense, hyper-stylized mood. The model wears a sculptural canary-yellow latex coat paired with glossy obsidian boots, creating an arresting chromatic clash. Angular cheekbones and slicked-back raven hair gleam under the punishing flash, highlighting dramatic graphic eyeliner and a poised, defiant expression. The figure stretches diagonally across the breadth of the scene, surrounded by saturated, unbroken color, with crisp geometric silhouettes defining the hyper-saturated, electric aesthetic."
        },
        "_meta": {
            "title": "CLIP Text Encode (Prompt)"
        }
    },
    "30:46": {
        "class_type": "UNETLoader",
        "inputs": {
            "unet_name": "z_image_turbo_bf16.safetensors",
            "weight_dtype": "default"
        },
        "_meta": {
            "title": "Load Diffusion Model"
        }
    },
    "30:47": {
        "class_type": "ModelSamplingAuraFlow",
        "inputs": {
            "model": [
                "30:46",
                0
            ],
            "sampling": "flow",
            "shift": 3
        },
        "_meta": {
            "title": "ModelSamplingAuraFlow"
        }
    }
})

# 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("76"):
    output.to_file(output.name)