import { client } from "@gradio/client" import { generateSeed } from "../../utils/misc/generateSeed.mts" import { getValidNumber } from "../../utils/validators/getValidNumber.mts" import { convertToWebp } from "../../utils/image/convertToWebp.mts" // TODO add a system to mark failed instances as "unavailable" for a couple of minutes // console.log("process.env:", process.env) // note: to reduce costs I use the small A10s (not the large) // anyway, we will soon not need to use this cloud anymore // since we will be able to leverage the Inference API const instance = `${process.env.VC_SDXL_SPACE_API_URL || ""}` const secretToken = `${process.env.VC_MICROSERVICE_SECRET_TOKEN || ""}` // console.log("DEBUG:", JSON.stringify({ instances, secretToken }, null, 2)) export async function generateImageSDXLAsBase64(options: { positivePrompt: string; negativePrompt?: string; seed?: number; width?: number; height?: number; nbSteps?: number; }): Promise { const positivePrompt = options?.positivePrompt || "" if (!positivePrompt) { throw new Error("missing prompt") } // the negative prompt CAN be missing, since we use a trick // where we make the interface mandatory in the TS doc, // but browsers might send something partial const negativePrompt = options?.negativePrompt || "" // we treat 0 as meaning "random seed" const seed = (options?.seed ? options.seed : 0) || generateSeed() const width = getValidNumber(options?.width, 256, 1024, 512) const height = getValidNumber(options?.height, 256, 1024, 512) const nbSteps = getValidNumber(options?.nbSteps, 5, 100, 20) // console.log("SEED:", seed) const positive = [ // oh well.. is it too late to move this to the bottom? "beautiful", // "intricate details", positivePrompt, "award winning", "high resolution" ].filter(word => word) .join(", ") const negative = [ negativePrompt, "watermark", "copyright", "blurry", // "artificial", // "cropped", "low quality", "ugly" ].filter(word => word) .join(", ") const api = await client(instance, { hf_token: `${process.env.VC_HF_API_TOKEN}` as any }) const rawResponse = (await api.predict("/run", [ positive, // string in 'Prompt' Textbox component negative, // string in 'Negative prompt' Textbox component positive, // string in 'Prompt 2' Textbox component negative, // string in 'Negative prompt 2' Textbox component true, // boolean in 'Use negative prompt' Checkbox component false, // boolean in 'Use prompt 2' Checkbox component false, // boolean in 'Use negative prompt 2' Checkbox component seed, // number (numeric value between 0 and 2147483647) in 'Seed' Slider component width, // number (numeric value between 256 and 1024) in 'Width' Slider component height, // number (numeric value between 256 and 1024) in 'Height' Slider component 8, // number (numeric value between 1 and 20) in 'Guidance scale for base' Slider component 8, // number (numeric value between 1 and 20) in 'Guidance scale for refiner' Slider component nbSteps, // number (numeric value between 10 and 100) in 'Number of inference steps for base' Slider component nbSteps, // number (numeric value between 10 and 100) in 'Number of inference steps for refiner' Slider component true, // boolean in 'Apply refiner' Checkbox component, secretToken ])) as any const result = rawResponse?.data?.[0] as string if (!result?.length) { throw new Error(`the returned image was empty`) } try { const finalImage = await convertToWebp(result) return finalImage } catch (err) { // console.log("err:", err) throw new Error(err) } }