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import { addBase64Header } from "@/lib/data/addBase64Header"
import { tryApiCalls } from "../../utils/tryApiCall"
const gradioSpaceApiUrl = `https://jbilcke-hf-ai-tube-model-parler-tts-mini.hf.space`
const huggingFaceSpace = "jbilcke-hf/ai-tube-model-parler-tts-mini"
const apiKey = `${process.env.MICROSERVICE_API_SECRET_TOKEN || ""}`
/**
* Note: this generates a MP3 file
*
* @param param0
* @returns
*/
export async function generateSpeechWithParlerTTS({
text,
audioId,
debug = false,
neverThrow = false,
}: {
text: string
audioId: string
debug?: boolean
neverThrow?: boolean
}): Promise<string> {
const actualFunction = async () => {
const res = await fetch(gradioSpaceApiUrl + (gradioSpaceApiUrl.endsWith("/") ? "" : "/") + "api/predict", {
method: "POST",
headers: {
"Content-Type": "application/json",
// Authorization: `Bearer ${token}`,
},
body: JSON.stringify({
fn_index: 0, // <- important!
data: [
apiKey,
text,
audioId,
],
}),
cache: "no-store",
// we can also use this (see https://vercel.com/blog/vercel-cache-api-nextjs-cache)
// next: { revalidate: 1 }
})
if (res.status !== 200) {
throw new Error('Failed to fetch data')
}
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))
if (!data[0]) {
throw new Error(`the returned audio was empty`)
}
return addBase64Header(data[0] as string, "mp3")
}
try {
if (!text?.length) {
throw new Error(`text is too short!`)
}
const result = await tryApiCalls({
func: actualFunction,
huggingFaceSpace,
debug,
failureMessage: "failed to generate the audio"
})
return result
} catch (err) {
if (neverThrow) {
console.error(`generateVoiceWithParlerTTS():`, err)
return ""
} else {
throw err
}
}
} |