GPUs SDK 利用ガイド

pip install novita-gpus

import novita_gpus

novita_gpus.api_key = "sk_xxxx"

endpoint = novita_gpus.Endpoint("0f43a6867e05fddd")
job = endpoint.run({
    "prompt": "a red apple on a table"
})

print(job.status())
output = job.output(timeout=300)
print(output)

import novita_gpus

novita_gpus.api_key = "sk_xxxx"

endpoint = novita_gpus.Endpoint("0f43a6867e05fddd")

job = endpoint.run({
    "workflow": {
        "4": {
            "class_type": "CheckpointLoaderSimple",
            "inputs": {"ckpt_name": "flux1-dev-fp8.safetensors"},
        },
        "5": {
            "class_type": "EmptyLatentImage",
            "inputs": {"width": 512, "height": 512, "batch_size": 1},
        },
        "6": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "a red apple on a table"},
        },
        "7": {
            "class_type": "CLIPTextEncode",
            "inputs": {"clip": ["4", 1], "text": "blurry, low quality"},
        },
        "3": {
            "class_type": "KSampler",
            "inputs": {
                "model": ["4", 0],
                "positive": ["6", 0],
                "negative": ["7", 0],
                "latent_image": ["5", 0],
                "seed": 42,
                "steps": 10,
                "cfg": 7,
                "sampler_name": "euler",
                "scheduler": "normal",
                "denoise": 1,
            },
        },
        "8": {
            "class_type": "VAEDecode",
            "inputs": {"samples": ["3", 0], "vae": ["4", 2]},
        },
        "9": {
            "class_type": "SaveImage",
            "inputs": {"filename_prefix": "test", "images": ["8", 0]},
        },
    },
    "output_node_id": "9",
})

print(job.status())
print(job.output(timeout=300))

import time
import novita_gpus


def handler(job: dict) -> dict:
    job_id = job["id"]
    job_input = job.get("input", {})
    prompt = job_input.get("prompt", "hello")

    novita_gpus.progress_update(job, {
        "status": "running",
        "message": "job accepted",
    })

    time.sleep(1)

    return {
        "job_id": job_id,
        "prompt": prompt,
        "result": "ok",
    }


if __name__ == "__main__":
    novita_gpus.start({"handler": handler})

IMAGE=<your-registry>/comfyui-worker:v0.0.1

docker buildx build --platform linux/amd64 \
  -t "$IMAGE" \
  --push .

o8UJWkag5WTn-async

export NOVITA_API_KEY="sk_xxxx"
export NOVITA_ENDPOINT_ID="o8UJWkag5WTn"
export NOVITA_APP_NAME="async"

python submit_task.py \
  --endpoint "$NOVITA_ENDPOINT_ID" \
  --app-name "$NOVITA_APP_NAME" \
  --api-key "$NOVITA_API_KEY"

endpoint_name = f"{args.endpoint}-{args.app_name}"
endpoint = novita_gpus.Endpoint(endpoint_name, api_key=args.api_key)

BUCKET_ENDPOINT_URL=https://<your-bucket-endpoint>
BUCKET_ACCESS_KEY_ID=<your-access-key-id>
BUCKET_SECRET_ACCESS_KEY=<your-secret-access-key>
BUCKET_NAME=<your-bucket-name>

import novita_gpus


def handler(job: dict) -> dict:
    image_url = novita_gpus.upload_image(job["id"], "/tmp/output.png")

    return {
        "images": [
            {
                "filename": "output.png",
                "url": image_url,
            }
        ]
    }


if __name__ == "__main__":
    novita_gpus.start({"handler": handler})

import novita_gpus

file_url = novita_gpus.upload_file("result.json", "/tmp/result.json")
bytes_url = novita_gpus.upload_bytes("result.txt", b"hello")

return {"error": "invalid input"}