Spaces:
Runtime error
Runtime error
images formats
#1
by
victor
HF staff
- opened
- routes/generate/index.js +39 -35
routes/generate/index.js
CHANGED
@@ -1,40 +1,40 @@
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const dotenv = require(
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const fs = require(
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const HfInference = require(
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dotenv.config();
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const inference = new HfInference(process.env.HF_TOKEN);
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const REPO_NAME = "black-forest-labs/FLUX.1-schnell"
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const IMAGE_SIZES = {
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},
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"portrait-3_4": {
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},
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"portrait-9_16": {
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},
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"landscape-4_3": {
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},
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"landscape-16_9": {
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}
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}
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module.exports = async function (fastify, opts) {
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fastify.get(
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let { inputs } = request.params;
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const { format } = request.query;
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if (format) {
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@@ -43,33 +43,37 @@ module.exports = async function (fastify, opts) {
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const slug = inputs.replace(/[^a-zA-Z0-9-_ ]/g, "").replace(/ /g, "-");
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const file = await fs
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if (file) {
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return reply
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.header('Content-Type', 'image/jpeg')
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.send(file);
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}
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const { height, width } =
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const hfRequest = await inference.textToImage({
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inputs,
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model: REPO_NAME,
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parameters: {
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height,
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width
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}
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})
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const buffer = await hfRequest.arrayBuffer();
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const array = new Uint8Array(buffer);
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const dir = await fs
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return reply
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})
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}
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"use strict";
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const dotenv = require("dotenv");
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const fs = require("fs").promises;
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const HfInference = require("@huggingface/inference").HfInference;
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dotenv.config();
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const inference = new HfInference(process.env.HF_TOKEN);
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const REPO_NAME = "black-forest-labs/FLUX.1-schnell";
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const IMAGE_SIZES = {
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square: {
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width: 1024,
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height: 1024,
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},
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"portrait-3_4": {
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width: 768,
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height: 1024,
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},
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"portrait-9_16": {
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width: 576,
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height: 1024,
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},
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"landscape-4_3": {
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width: 1024,
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height: 768,
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},
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"landscape-16_9": {
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width: 1024,
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height: 576,
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},
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};
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module.exports = async function (fastify, opts) {
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fastify.get("/:inputs", async function (request, reply) {
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let { inputs } = request.params;
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const { format } = request.query;
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if (format) {
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const slug = inputs.replace(/[^a-zA-Z0-9-_ ]/g, "").replace(/ /g, "-");
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const file = await fs
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.readFile(process.env.PUBLIC_FILE_UPLOAD_DIR + "/" + slug + ".png")
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?.catch(() => null);
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if (file) {
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return reply.header("Content-Type", "image/jpeg").send(file);
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}
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const { height, width } =
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IMAGE_SIZES[format ?? "square"] ?? IMAGE_SIZES["square"];
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const hfRequest = await inference.textToImage({
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inputs,
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model: REPO_NAME,
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parameters: {
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height,
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width,
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},
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});
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const buffer = await hfRequest.arrayBuffer();
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const array = new Uint8Array(buffer);
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const dir = await fs
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.opendir(process.env.PUBLIC_FILE_UPLOAD_DIR)
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.catch(() => null);
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if (!dir) await fs.mkdir(process.env.PUBLIC_FILE_UPLOAD_DIR);
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await fs.writeFile(
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process.env.PUBLIC_FILE_UPLOAD_DIR + "/" + slug + ".png",
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array
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);
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return reply.header("Content-Type", "image/jpeg").send(array);
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});
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};
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