Kling O1: Image to Video

# 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({
    "1": {
        "class_type": "SaveVideo",
        "inputs": {
            "filename_prefix": "video/kling-omni-t2v",
            "format": "auto",
            "format.codec": "auto",
            "video": [
                "2",
                0
            ]
        },
        "_meta": {
            "title": "Save Video"
        }
    },
    "2": {
        "class_type": "KlingOmniProImageToVideoNode",
        "inputs": {
            "aspect_ratio": "16:9",
            "duration": 3,
            "generate_audio": False,
            "model_name": "kling-video-o1",
            "prompt": "An indoor scene at night where the quokka in a white bathrobe sits by a window, looking out at the stars. The camera slowly zooms in on its contemplative face, then pulls back to reveal the knitted sheep character approaching with a warm drink. The sheep's light blue sweater glows softly in the warm room light. Candles flicker on a nearby table, casting dancing shadows. The atmosphere is cozy, peaceful, and filled with quiet companionship.",
            "reference_images": [
                "4",
                0
            ],
            "resolution": "1080p",
            "seed": 0
        },
        "_meta": {
            "title": "Kling 3.0 Omni Image to Video"
        }
    },
    "3": {
        "class_type": "LoadImage",
        "inputs": {
            "image": "sheep_knit.jpg"
        },
        "_meta": {
            "title": "Load Image"
        }
    },
    "4": {
        "class_type": "BatchImagesNode",
        "inputs": {
            "images.image0": [
                "3",
                0
            ],
            "images.image1": [
                "5",
                0
            ],
            "images.image2": [
                "6",
                0
            ]
        },
        "_meta": {
            "title": "Batch Images"
        }
    },
    "5": {
        "class_type": "LoadImage",
        "inputs": {
            "image": "quokka_bath.jpg"
        },
        "_meta": {
            "title": "Load Image"
        }
    },
    "6": {
        "class_type": "LoadImage",
        "inputs": {
            "image": "quokka_relax.jpg"
        },
        "_meta": {
            "title": "Load Image"
        }
    }
})

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