|
import express from "express" |
|
import { HfInference } from '@huggingface/inference' |
|
|
|
import { daisy } from "./daisy.mts" |
|
|
|
const hf = new HfInference(process.env.HF_API_TOKEN) |
|
|
|
const app = express() |
|
const port = 7860 |
|
|
|
const minPromptSize = 16 |
|
const timeoutInSec = 15 * 60 |
|
|
|
console.log("timeout set to 15 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) => { |
|
|
|
const model = `${req.query.model || 'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5'}` |
|
|
|
console.log('model:', model) |
|
|
|
const endpoint = `${req.query.endpoint || ''}` |
|
|
|
console.log('endpoint:', endpoint) |
|
|
|
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,line-clamp"></script><title>Generated content</title><body` |
|
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 the following: ${req.query.prompt} |
|
# Guidelines |
|
- Never repeat the instruction, instead directly write the final code |
|
- Use a color scheme consistent with the brief and theme |
|
- You need to use Tailwind CSS |
|
- All the JS code will be written directly inside the page, using <script type="text/javascript">...</script> |
|
- You MUST use English, not Latin! (I repeat: do NOT write lorem ipsum!) |
|
- No need to write code comments, so please make the code compact (short function names etc) |
|
- Use a central layout by wrapping everything in a \`<div class="flex flex-col items-center">\` |
|
# HTML output |
|
<html><head></head><body` |
|
|
|
try { |
|
let result = '' |
|
for await (const output of hf.textGenerationStream({ |
|
model, |
|
inputs: finalPrompt, |
|
parameters: { max_new_tokens: 1024 } |
|
})) { |
|
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 |
|
} |
|
} |
|
|
|
endRequest(id, `normal end of the LLM stream for request ${id}`) |
|
} catch (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.listen(port, () => { console.log(`Open http://localhost:${port}/`) }) |
|
|
|
|
