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"use server"
import { BackgroundRemovalParams } from "@/types"
import { addBase64HeaderToPng } from "./addBase64HeaderToPng"
const gradioApi = `https://jbilcke-hf-background-removal-api.hf.space`
const microserviceApiKey = `${process.env.MICROSERVICE_API_SECRET_TOKEN || ""}`
export async function removeBackground({
imageAsBase64,
}: BackgroundRemovalParams): Promise<string> {
// remember: a space needs to be public for the classic fetch() to work
const res = await fetch(gradioApi + (gradioApi.endsWith("/") ? "" : "/") + "api/predict", {
method: "POST",
headers: {
"Content-Type": "application/json",
// Authorization: `Bearer ${hfApiToken}`,
},
body: JSON.stringify({
fn_index: 0, // <- is it 0 or 1?
data: [
microserviceApiKey,
imageAsBase64,
],
}),
cache: "no-store",
// we can also use this (see https://vercel.com/blog/vercel-cache-api-nextjs-cache)
// next: { revalidate: 1 }
})
const { data } = await res.json()
// console.log("data:", data)
// Recommendation: handle errors
if (res.status !== 200 || !Array.isArray(data)) {
// This will activate the closest `error.js` Error Boundary
throw new Error(`Failed to fetch data (status: ${res.status})`)
}
// console.log("data:", data.slice(0, 50))
const base64Content = (data?.[0] || "") as string
if (!base64Content) {
throw new Error(`invalid response (no content)`)
}
return addBase64HeaderToPng(base64Content)
} |