Stable Diffusion Text-to-Image Generator: Generate Images from Text

const axios = require('axios');

const handler = async (m, { text, command, conn }) => { const payloads = { server_name: 'rose', prompt: ${text}, // your imagination go here width: 512, // 512-1024 height: 768, // 512-1024 steps: 25, // max 50 steps model_id: 'anything-v5', // default dream_shaper_ sampler: 'Euler a', // 2M SDE karras seed: null, // pass null or remove to get random seed cfg: 7.5, // max 15< image_num: 1, // max 4 negative_prompt: 'ugly', // something you dont want to appear in the image safety_checker: 'no', // set 'no' to replace nsfw image

	/* Another optional parameter */
	enhance_prompt: 'yes', // if 'yes' will add another prompt
	multi_lingual: 'yes', // pass 'yes' if you want to use other than the English language
	clip_skip: 2,
	panorama: 'no', // pass 'yes' if you want a panorama image
	lora_model: 'more_details', // use loaded lora_model
	hiresFix: 'no', // otherwise pass 'no'
	lora_strength: 1, // default 1
	embeddings_model: '',
	webhook: null, // will send post about generating progress
};

m.reply('_Preparing Stable diffusion..._');

const { data } = await axios
	.request({
		baseURL: 'https://api.itsrose.life',
		url: '/image/diffusion/txt2img',
		method: 'POST',
		params: {
			apikey: `${global.rose}`,
		},
		data: payloads,
	})
	.catch((e) => e?.response);

const { status, message, result } = data;

if (!status) {
	// something wrong with your payloads
	return m.reply(message); // see the message
}
const { images, metadata, generation_time } = result;
const second = result.generation_time.toFixed();
const model = metadata.model_id;
const schedule = metadata.scheduler;
const w = metadata.W;
const h = metadata.H;
const cfg = metadata.guidance_scale;
const step = metadata.steps;
const seed = metadata.seed;
const streng = metadata.clip_skip;

const medata = `*Generating Time*: ${second} second

prompt: ${text} model_id: ${model} scheduler: ${schedule} W: ${w} H: ${h} guidance_scale: ${cfg} steps: ${step} seed: ${seed} clip_skip: ${streng}`; await m.reply(medata);

try {
	for (const image of images) {
		await new Promise((resolve) => {
			setTimeout(async () => {
				await conn.sendMessage(m.chat, { image: { url: image } });
				resolve();
			}, generation_time * 1000);
		});
	}
} catch {
	m.reply(`Failed sending images : ${images.join(', ')}`);
}

};

handler.command = handler.help = ['txt2img']; handler.tags = ['ai']; handler.register = true; handler.limit = true;

module.exports = handler;