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"use server";
import { HfInference } from "@huggingface/inference";
import fs from "fs/promises";
import { Form } from "@/_types";
import prisma from "@/_utils/prisma";
export async function generate({ brand_name, industry, description }: Form) {
if (!process.env.PUBLIC_FILE_UPLOAD_DIR) {
throw new Error("PUBLIC_FILE_UPLOAD_DIR is not set");
}
const inference = new HfInference(process.env.HF_ACCESS_TOKEN, {
use_cache: false,
});
const prompt: any = await inference
.chatCompletion({
model: "meta-llama/Meta-Llama-3.1-70B-Instruct",
messages: [
{ role: "user", content: "lee, a noodle restaurant" },
{
role: "assistant",
content:
'logo,Minimalist,A pair of chopsticks and a bowl of rice with the word "Lee",',
},
{ role: "user", content: "cat shop" },
{ role: "assistant", content: "wablogo,Minimalist,Leaf and cat,logo," },
{ role: "user", content: "Ato, real estate company" },
{
role: "assistant",
content:
'logo,Minimalist,A man stands in front of a door,his shadow forming the word "A",',
},
{ role: "user", content: `${brand_name}, ${description}, ${industry}` },
],
temperature: 0.5,
max_tokens: 1024,
top_p: 0.7,
})
.then((res) => res)
.catch((err) => {
return { error: err.message };
});
if (prompt?.error) {
return {
error: prompt.error,
};
}
if (prompt?.choices[0]?.message?.content) {
const hfRequest = await inference.textToImage({
inputs: prompt.choices[0].message.content,
model: "Shakker-Labs/FLUX.1-dev-LoRA-Logo-Design",
parameters: {
num_inference_steps: 24,
guidance_scale: 3.5,
},
});
const buffer = await hfRequest.arrayBuffer();
const array = new Uint8Array(buffer);
const newImage = await prisma.logo.create({
data: {
name: prompt.choices[0].message.content,
},
});
const indexFile = newImage.id;
const dir = await fs
.opendir(process.env.PUBLIC_FILE_UPLOAD_DIR)
.catch(() => null);
if (!dir) await fs.mkdir(process.env.PUBLIC_FILE_UPLOAD_DIR);
await fs.writeFile(
`${process.env.PUBLIC_FILE_UPLOAD_DIR}/${indexFile}.png`,
array
);
return { data: indexFile };
}
return {
error: "Failed to generate logo",
};
}
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