SD3.5 Simple

# 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({
    "3": {
        "class_type": "KSampler",
        "inputs": {
            "cfg": 4.01,
            "denoise": 1,
            "latent_image": [
                "53",
                0
            ],
            "model": [
                "4",
                0
            ],
            "negative": [
                "40",
                0
            ],
            "positive": [
                "16",
                0
            ],
            "sampler_name": "euler",
            "scheduler": "sgm_uniform",
            "seed": 585483408983215,
            "steps": 20
        },
        "_meta": {
            "title": "KSampler"
        }
    },
    "4": {
        "class_type": "CheckpointLoaderSimple",
        "inputs": {
            "ckpt_name": "sd3.5_large_fp8_scaled.safetensors"
        },
        "_meta": {
            "title": "Load Checkpoint"
        }
    },
    "8": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "3",
                0
            ],
            "vae": [
                "4",
                2
            ]
        },
        "_meta": {
            "title": "VAE Decode"
        }
    },
    "9": {
        "class_type": "SaveImage",
        "inputs": {
            "filename_prefix": "ComfyUI",
            "images": [
                "8",
                0
            ]
        },
        "_meta": {
            "title": "Save Image"
        }
    },
    "16": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "4",
                1
            ],
            "text": "A richly detailed painted illustration of an ancient, hulking reptilian drake-folk shaman standing full-length amid a vast expanse of scorched volcanic badlands and smoking fissures. The venerable saurian has thick, weathered emerald-and-bronze scales, deep-set cataract-filmed golden eyes, and long, braided silver-white spines cascading down its hunched shoulders. Clad in archaic Bronze Age ceremonial regalia of hammered verdigris copper plates, coarse crimson weaves, and polished bone talismans, it leans upon a massive gnarled staff topped with a smoldering amber brazier. Wisps of ember-sparked gold smoke drift across the sprawling landscape, illuminating cracked obsidian earth and distant jagged crags under a low-hanging twilight sky. Warm ochre, fiery rust, and deep jade tones harmonize across the atmospheric expanse."
        },
        "_meta": {
            "title": "Positive Prompt"
        }
    },
    "40": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "4",
                1
            ],
            "text": ""
        },
        "_meta": {
            "title": "Negative Prompt"
        }
    },
    "53": {
        "class_type": "EmptySD3LatentImage",
        "inputs": {
            "batch_size": 1,
            "height": 768,
            "width": 1344
        },
        "_meta": {
            "title": "EmptySD3LatentImage"
        }
    }
})

# 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)