Wan2.1 Alpha T2V

# 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": 6,
            "denoise": 1,
            "latent_image": [
                "40",
                0
            ],
            "model": [
                "48",
                0
            ],
            "negative": [
                "7",
                0
            ],
            "positive": [
                "6",
                0
            ],
            "sampler_name": "uni_pc",
            "scheduler": "simple",
            "seed": 558449140107503,
            "steps": 20
        },
        "_meta": {
            "title": "KSampler"
        }
    },
    "6": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "38",
                0
            ],
            "text": "\"Medium shot. A little girl holds a bubble wand and blows out colorful bubbles that float and pop in the air. The background of this video is transparent. Realistic style.\"\t"
        },
        "_meta": {
            "title": "CLIP Text Encode (Positive Prompt)"
        }
    },
    "7": {
        "class_type": "CLIPTextEncode",
        "inputs": {
            "clip": [
                "38",
                0
            ],
            "text": "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
        },
        "_meta": {
            "title": "CLIP Text Encode (Negative Prompt) Useless s"
        }
    },
    "8": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "3",
                0
            ],
            "vae": [
                "39",
                0
            ]
        },
        "_meta": {
            "title": "RGB VAE Decode"
        }
    },
    "37": {
        "class_type": "UNETLoader",
        "inputs": {
            "unet_name": "wan2.1_t2v_14B_fp8_scaled.safetensors",
            "weight_dtype": "default"
        },
        "_meta": {
            "title": "Load Wan 2.1 t2v 14B"
        }
    },
    "38": {
        "class_type": "CLIPLoader",
        "inputs": {
            "clip_name": "umt5_xxl_fp8_e4m3fn_scaled.safetensors",
            "device": "default",
            "type": "wan"
        },
        "_meta": {
            "title": "Load Text Encoder"
        }
    },
    "39": {
        "class_type": "VAELoader",
        "inputs": {
            "vae_name": "wan_alpha_2.1_vae_rgb_channel.safetensors"
        },
        "_meta": {
            "title": "Load VAE"
        }
    },
    "40": {
        "class_type": "EmptyHunyuanLatentVideo",
        "inputs": {
            "batch_size": 1,
            "height": 480,
            "length": 33,
            "width": 832
        },
        "_meta": {
            "title": "Empty Hunyuan Video 1.0 Latent"
        }
    },
    "48": {
        "class_type": "ModelSamplingSD3",
        "inputs": {
            "model": [
                "65",
                0
            ],
            "shift": 5
        },
        "_meta": {
            "title": "ModelSamplingSD3"
        }
    },
    "51": {
        "class_type": "VAELoader",
        "inputs": {
            "vae_name": "wan_alpha_2.1_vae_alpha_channel.safetensors"
        },
        "_meta": {
            "title": "Load VAE"
        }
    },
    "52": {
        "class_type": "VAEDecode",
        "inputs": {
            "samples": [
                "3",
                0
            ],
            "vae": [
                "51",
                0
            ]
        },
        "_meta": {
            "title": "Alpha VAE Decode"
        }
    },
    "65": {
        "class_type": "LoraLoaderModelOnly",
        "inputs": {
            "lora_name": "wan_alpha_2.1_rgba_lora.safetensors",
            "model": [
                "37",
                0
            ],
            "strength_model": 1
        },
        "_meta": {
            "title": "Load LoRA"
        }
    },
    "80": {
        "class_type": "SaveAnimatedWEBP",
        "inputs": {
            "filename_prefix": "ComfyUI",
            "fps": 16,
            "images": [
                "86",
                0
            ],
            "lossless": True,
            "method": "default",
            "quality": 80
        },
        "_meta": {
            "title": "Save Animated WEBP"
        }
    },
    "82": {
        "class_type": "ImageToMask",
        "inputs": {
            "channel": "red",
            "image": [
                "52",
                0
            ]
        },
        "_meta": {
            "title": "Convert Image to Mask"
        }
    },
    "84": {
        "class_type": "InvertMask",
        "inputs": {
            "mask": [
                "82",
                0
            ]
        },
        "_meta": {
            "title": "Invert Mask"
        }
    },
    "86": {
        "class_type": "JoinImageWithAlpha",
        "inputs": {
            "alpha": [
                "84",
                0
            ],
            "image": [
                "8",
                0
            ]
        },
        "_meta": {
            "title": "Join Image with Alpha"
        }
    }
})

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