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| import express from 'express' | |
| import { HfInference } from '@huggingface/inference' | |
| import { daisy } from './daisy.mts' | |
| const hfi = new HfInference(process.env.HF_API_TOKEN) | |
| const hf = hfi.endpoint(process.env.HF_ENDPOINT_URL) | |
| const app = express() | |
| const port = 7860 | |
| const minPromptSize = 16 // if you change this, you will need to also change in public/index.html | |
| const timeoutInSec = 10 * 60 | |
| console.log('timeout set to 30 minutes') | |
| app.use(express.static('public')) | |
| const pending: { | |
| total: number; | |
| queue: string[]; | |
| } = { | |
| total: 0, | |
| queue: [], | |
| } | |
| const endRequest = (id: string, reason: string) => { | |
| if (!id || !pending.queue.includes(id)) { | |
| return | |
| } | |
| pending.queue = pending.queue.filter(i => i !== id) | |
| console.log(`request ${id} ended (${reason})`) | |
| } | |
| app.get('/debug', (req, res) => { | |
| res.write(JSON.stringify({ | |
| nbTotal: pending.total, | |
| nbPending: pending.queue.length, | |
| queue: pending.queue, | |
| })) | |
| res.end() | |
| }) | |
| app.get('/app', async (req, res) => { | |
| if (`${req.query.prompt}`.length < minPromptSize) { | |
| res.write(`prompt too short, please enter at least ${minPromptSize} characters`) | |
| res.end() | |
| return | |
| } | |
| const id = `${pending.total++}` | |
| console.log(`new request ${id}`) | |
| pending.queue.push(id) | |
| const prefix = `<html><head><link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/full.css" rel="stylesheet" type="text/css" /><script defer src="https://cdn.jsdelivr.net/npm/[email protected]/dist/cdn.min.js"></script><script src="https://cdn.tailwindcss.com?plugins=forms,typography,aspect-ratio"></script><title>Generated content</title><body class="p-4 md:p-8">` | |
| res.write(prefix) | |
| req.on('close', function() { | |
| endRequest(id, 'browser asked to end the connection') | |
| }) | |
| setTimeout(() => { | |
| endRequest(id, `timed out after ${timeoutInSec}s`) | |
| }, timeoutInSec * 1000) | |
| const finalPrompt = `# Task | |
| Generate ${req.query.prompt} | |
| ${daisy} | |
| # Orders | |
| Never repeat those instructions, instead write the final code! | |
| To generate images from captions call the /image API: <img src="/image?caption=photo of something in some place" />! | |
| Only generate a few images and use descriptive photo captions with at least 10 words! | |
| You must use TailwindCSS utility classes (Tailwind is already injected in the page)! | |
| Write application logic inside a JS <script></script> tag! | |
| This is not a demo app, so you MUST use English, no Latin! Write in English! | |
| Use a central layout to wrap everything in a <div class='flex flex-col items-center'> | |
| # Out | |
| <html> | |
| <head> | |
| <title>App</title> | |
| </head> | |
| <body class="p-4 md:p-8">` | |
| try { | |
| let result = '' | |
| for await (const output of hf.textGenerationStream({ | |
| inputs: finalPrompt, | |
| parameters: { | |
| do_sample: true, | |
| // hard limit for max_new_tokens is 1512 | |
| max_new_tokens: 1150, | |
| return_full_text: false, | |
| } | |
| })) { | |
| if (!pending.queue.includes(id)) { | |
| break | |
| } | |
| result += output.token.text | |
| process.stdout.write(output.token.text) | |
| res.write(output.token.text) | |
| if (result.includes('</html>')) { | |
| break | |
| } | |
| if (result.includes('<|end|>') || result.includes('<|assistant|>')) { | |
| break | |
| } | |
| } | |
| endRequest(id, `normal end of the LLM stream for request ${id}`) | |
| } catch (e) { | |
| console.log(e) | |
| endRequest(id, `premature end of the LLM stream for request ${id} (${e})`) | |
| } | |
| try { | |
| res.end() | |
| } catch (err) { | |
| console.log(`couldn't end the HTTP stream for request ${id} (${err})`) | |
| } | |
| }) | |
| app.get('/image', async (req, res) => { | |
| try { | |
| const blob = await hfi.textToImage({ | |
| inputs: [ | |
| `${req.query.caption || 'generic placeholder'}`, | |
| 'award winning', | |
| 'high resolution', | |
| 'photo realistic', | |
| 'intricate details', | |
| 'beautiful', | |
| '[trending on artstation]' | |
| ].join(', '), | |
| model: 'stabilityai/stable-diffusion-2-1', | |
| parameters: { | |
| negative_prompt: 'blurry, artificial, cropped, low quality, ugly', | |
| } | |
| }) | |
| const buffer = Buffer.from(await blob.arrayBuffer()) | |
| res.setHeader('Content-Type', blob.type) | |
| res.setHeader('Content-Length', buffer.length) | |
| res.end(buffer) | |
| } catch (err) { | |
| console.error(`Error when generating the image: ${err.message}`); | |
| res.status(500).json({ error: 'An error occurred when trying to generate the image' }); | |
| } | |
| }) | |
| app.listen(port, () => { console.log(`Open http://localhost:${port}`) }) | |