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import { RenderedScene, RenderRequest } from "../../types.mts" | |
import { generateSeed } from "../../utils/misc/generateSeed.mts" | |
import { tryApiCalls } from "../../utils/misc/tryApiCall.mts" | |
import { getValidNumber } from "../../utils/validators/getValidNumber.mts" | |
const accessToken = `${process.env.VC_MICROSERVICE_SECRET_TOKEN || ""}` | |
// @deprecated This endpoint has been decommissioned. Please use the AiTube API instead (check aitube.at/api/v1/render) | |
export const generateVideoWithAnimateDiffLightning = async ( | |
request: RenderRequest, | |
response: RenderedScene, | |
): Promise<RenderedScene> => { | |
throw new Error(`This endpoint has been decommissioned. Please use the AiTube API instead (check aitube.at/api/v1/render)`) | |
const debug = true | |
const actualFunction = async (): Promise<RenderedScene> => { | |
const prompt = request.prompt || "" | |
if (!prompt) { | |
response.error = "prompt is empty" | |
return response | |
} | |
// seed = seed || generateSeed() | |
request.seed = request.seed || generateSeed() | |
// see https://huggingface.co/spaces/jbilcke-hf/ai-tube-model-animatediff-lightning/blob/main/app.py#L15-L18 | |
const baseModel = "epiCRealism" | |
// the motion LoRA - could be useful one day | |
const motion = "" | |
// can be 1, 2, 4 or 8 | |
// but values below 4 look bad | |
const nbSteps = 4// getValidNumber(request.nbSteps, 1, 8, 4) | |
const width = 512 // getValidNumber(request.width, 256, 1024, 512) | |
const height = 288 // getValidNumber(request.height, 256, 1024, 256) | |
const nbFrames = 16 // getValidNumber(request.nbFrames, 10, 60, 10) | |
const nbFPS = 10 // getValidNumber(request.nbFPS, 10, 60, 10) | |
// by default AnimateDiff generates about 2 seconds of video at 10 fps | |
// the Gradio API now has some code to optional fix that using FFmpeg, | |
// but this will add some delay overhead, so use with care! | |
const durationInSec = nbFrames / nbFPS | |
// no, we need decimals | |
// const durationInSec = Math.round(nbFrames / nbFPS) | |
const framesPerSec = nbFPS | |
try { | |
if (debug) { | |
console.log(`calling AnimateDiff Lightning API with params (some are hidden):`, { | |
baseModel, | |
motion, | |
nbSteps, | |
width, | |
height, | |
nbFrames, | |
nbFPS, | |
durationInSec, | |
framesPerSec, | |
}) | |
} | |
const res = await fetch(`https://jbilcke-hf-ai-tube-model-animatediff.hf.space/api/predict`, { | |
method: "POST", | |
headers: { | |
"Content-Type": "application/json", | |
// Authorization: `Bearer ${token}`, | |
}, | |
body: JSON.stringify({ | |
fn_index: 0, // <- important! it is currently 4, not 1! | |
data: [ | |
accessToken, | |
prompt, | |
baseModel, | |
width, | |
height, | |
motion, | |
nbSteps, | |
durationInSec, | |
framesPerSec, | |
], | |
}), | |
cache: "no-store", | |
// we can also use this (see https://vercel.com/blog/vercel-cache-api-nextjs-cache) | |
// next: { revalidate: 1 } | |
}) | |
// console.log("res:", res) | |
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)`) | |
} | |
response.assetUrl = base64Content | |
// this API already emits a data-uri with a content type | |
return response // addBase64HeaderToMp4(base64Content) | |
} catch (err) { | |
if (debug) { | |
console.error(`failed to call the AnimateDiff Lightning API:`) | |
console.error(err) | |
} | |
throw err | |
} | |
} | |
return tryApiCalls({ | |
func: actualFunction, | |
debug, | |
failureMessage: "failed to call the AnimateDiff Lightning API" | |
}) | |
} |