|
import express from "express" |
|
import { python } from 'pythonia' |
|
|
|
import { daisy } from "./daisy.mts" |
|
import { alpine } from "./alpine.mts" |
|
|
|
|
|
const { AutoModelForCausalLM } = await python('ctransformers') |
|
|
|
|
|
const css = [ |
|
"/css/[email protected]", |
|
].map(item => `<link href="${item}" rel="stylesheet" type="text/css"/>`) |
|
.join("") |
|
|
|
const script = [ |
|
"/js/[email protected]", |
|
"/js/[email protected]" |
|
].map(item => `<script src="${item}"></script>`) |
|
.join("") |
|
|
|
|
|
const llm = await AutoModelForCausalLM.from_pretrained$( |
|
"TheBloke/WizardCoder-15B-1.0-GGML", { |
|
model_file: "WizardCoder-15B-1.0.ggmlv3.q4_0.bin", |
|
model_type: "starcoder" |
|
}) |
|
|
|
const app = express() |
|
const port = 7860 |
|
|
|
const timeoutInSec = 60 * 60 |
|
|
|
console.log("timeout set to 60 minutes") |
|
|
|
app.use(express.static("public")) |
|
|
|
const maxParallelRequests = 1 |
|
|
|
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})`) |
|
} |
|
|
|
|
|
process.on('SIGINT', () => { |
|
try { |
|
(python as any).exit() |
|
} catch (err) { |
|
|
|
|
|
} |
|
process.exit(0) |
|
}) |
|
|
|
app.get("/debug", (req, res) => { |
|
res.write(JSON.stringify({ |
|
nbTotal: pending.total, |
|
nbPending: pending.queue.length, |
|
queue: pending.queue, |
|
})) |
|
res.end() |
|
}) |
|
|
|
app.get("/", async (req, res) => { |
|
|
|
if (pending.queue.length >= maxParallelRequests) { |
|
res.write("sorry, max nb of parallel requests reached") |
|
res.end() |
|
return |
|
} |
|
|
|
|
|
|
|
|
|
|
|
const id = `${pending.total++}` |
|
console.log(`new request ${id}`) |
|
|
|
pending.queue.push(id) |
|
|
|
const prefix = `<html><head>${css}${script}` |
|
res.write(prefix) |
|
|
|
req.on("close", function() { |
|
endRequest(id, "browser ended the connection") |
|
}) |
|
|
|
|
|
setTimeout(() => { |
|
endRequest(id, `timed out after ${timeoutInSec}s`) |
|
}, timeoutInSec * 1000) |
|
|
|
|
|
const finalPrompt = `# Context |
|
Generate a webpage written in English about: ${req.query.prompt}. |
|
# Documentation |
|
${daisy} |
|
# Guidelines |
|
- Do not write a tutorial or repeat the instruction, but directly write the final code within a script tag |
|
- Use a color scheme consistent with the brief and theme |
|
- You need to use Tailwind CSS and DaisyUI for the UI, pure vanilla JS and AlpineJS for the JS. |
|
- You vanilla 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, and try to make the code compact (short function names etc) |
|
- Use a central layout by wrapping everything in a \`<div class="flex flex-col justify-center">\` |
|
# Result output |
|
${prefix}` |
|
|
|
|
|
try { |
|
|
|
const inputTokens = await llm.tokenize(finalPrompt) |
|
console.log("initializing the generator (may take 30s or more)") |
|
const generator = await llm.generate(inputTokens) |
|
console.log("generator initialized, beginning token streaming..") |
|
for await (const token of generator) { |
|
if (!pending.queue.includes(id)) { |
|
break |
|
} |
|
const tmp = await llm.detokenize(token) |
|
process.stdout.write(tmp) |
|
res.write(tmp) |
|
} |
|
|
|
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}/?prompt=a%20landing%20page%20for%20a%20company%20called%20Hugging%20Face`) }) |
|
|
|
|
