test_image.cjs•1.6 kB
const { InferenceClient } = require('@huggingface/inference');
const fs = require('fs');
async function generateImage() {
try {
const client = new InferenceClient('TEst_TOKEN');
console.log('이미지 생성 중...');
const image = await client.textToImage({
provider: "fal-ai",
model: "black-forest-labs/FLUX.1-schnell",
inputs: "A cute poodle dog sleeping peacefully, curled up in a cozy bed, soft lighting, peaceful atmosphere, high quality, detailed",
parameters: { num_inference_steps: 5 }
});
console.log('이미지 생성 완료!');
console.log('이미지 타입:', typeof image);
// Convert to base64
let base64;
if (typeof image === 'string') {
base64 = image;
} else if (image && typeof image === 'object' && 'arrayBuffer' in image) {
const arrayBuffer = await image.arrayBuffer();
base64 = Buffer.from(arrayBuffer).toString('base64');
} else {
base64 = Buffer.from(image).toString('base64');
}
console.log('Base64 길이:', base64.length);
console.log('Base64 미리보기:', base64.substring(0, 100) + '...');
// Save to file
const buffer = Buffer.from(base64, 'base64');
fs.writeFileSync('poodle_sleeping.png', buffer);
console.log('이미지가 poodle_sleeping.png로 저장되었습니다!');
} catch (error) {
console.error('오류 발생:', error.message);
}
}
generateImage();
