HiDream I1 Dev

# 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": 1,
            "denoise": 1,
            "latent_image": [
                "53",
                0
            ],
            "model": [
                "70",
                0
            ],
            "negative": [
                "40",
                0
            ],
            "positive": [
                "16",
                0
            ],
            "sampler_name": "lcm",
            "scheduler": "normal",
            "seed": 426270906276990,
            "steps": 28
        },
        "_meta": {
            "title": "KSampler"
        }
    },
    "8": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "3",
                0
            ],
            "vae": [
                "55",
                0
            ]
        },
        "_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": [
                "54",
                0
            ],
            "text": "A photograph of an albino woman with white skin and dark hair wearing black in the style of old baroque oil paintings, with soft focus, wearing a pearl necklace around her neck, with a dark background, with rosy cheeks, with a long veil covering her face, looking straight ahead"
        },
        "_meta": {
            "title": "Positive Prompt"
        }
    },
    "40": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "54",
                0
            ],
            "text": "bad ugly jpeg artifacts"
        },
        "_meta": {
            "title": "Negative Prompt"
        }
    },
    "53": {
        "class_type": "EmptySD3LatentImage",
        "inputs": {
            "batch_size": 1,
            "height": 1024,
            "width": 1024
        },
        "_meta": {
            "title": "EmptySD3LatentImage"
        }
    },
    "54": {
        "class_type": "QuadrupleCLIPLoader",
        "inputs": {
            "clip_name1": "clip_l_hidream.safetensors",
            "clip_name2": "clip_g_hidream.safetensors",
            "clip_name3": "t5xxl_fp8_e4m3fn_scaled.safetensors",
            "clip_name4": "llama_3.1_8b_instruct_fp8_scaled.safetensors"
        },
        "_meta": {
            "title": "Load CLIP (Quadruple)"
        }
    },
    "55": {
        "class_type": "VAELoader",
        "inputs": {
            "vae_name": "ae.safetensors"
        },
        "_meta": {
            "title": "Load VAE"
        }
    },
    "70": {
        "class_type": "ModelSamplingSD3",
        "inputs": {
            "model": [
                "76",
                0
            ],
            "shift": 6.000000000000001
        },
        "_meta": {
            "title": "ModelSamplingSD3"
        }
    },
    "76": {
        "class_type": "UNETLoader",
        "inputs": {
            "unet_name": "hidream_i1_dev_fp8.safetensors",
            "weight_dtype": "default"
        },
        "_meta": {
            "title": "Load Diffusion Model"
        }
    }
})

# run() also passes api_key to the partner nodes in this workflow.
job = client.run(workflow, api_key=api_key)