server.js

import express from 'express';
import multer from 'multer';
import AdmZip from 'adm-zip';
import { pipeline, env } from '@xenova/transformers';
import fs from 'fs';

env.allowLocalModels = false;
env.useBrowserCache = false;

const app = express();
const upload = multer({ storage: multer.memoryStorage() });

const LANG_MAP = {
    'fr_fr': 'fra_Latn', 'es_es': 'spa_Latn', 'de_de': 'deu_Latn', 'it_it': 'ita_Latn',
    'pt_pt': 'por_Latn', 'ru_ru': 'rus_Cyrl', 'ja_jp': 'jpn_Jpan', 'zh_cn': 'zho_Hans',
    'ko_kr': 'kor_Hang', 'pl_pl': 'pol_Latn', 'uk_ua': 'ukr_Cyrl', 'tr_tr': 'tur_Latn',
    'nl_nl': 'nld_Latn', 'sv_se': 'swe_Latn', 'da_dk': 'dan_Latn', 'no_no': 'nob_Latn'
};

let translator;
// Stockage temporaire des tâches de traduction en cours
const jobs = {};

pipeline('translation', 'Xenova/nllb-200-distilled-600M').then(model => {
    translator = model;
    console.log("✅ Modèle d'IA prêt !");
});

app.use(express.static('public'));
app.use(express.json());

// Petite pause pour laisser respirer l'événement de Node.js (évite de figer le serveur)
const breathe = () => new Promise(resolve => setImmediate(resolve));

// API : Lecture des limites réelles du conteneur Docker (cgroups Linux)
app.get('/api/stats', (req, res) => {
    let usedRam = 0;
    let totalRam = 16; // Valeur par défaut sur HF Basic CPU

    try {
        // Lecture de la RAM consommée par le Docker
        if (fs.existsSync('/sys/fs/cgroup/memory/memory.usage_in_bytes')) {
            usedRam = parseInt(fs.readFileSync('/sys/fs/cgroup/memory/memory.usage_in_bytes', 'utf8'), 10);
            totalRam = parseInt(fs.readFileSync('/sys/fs/cgroup/memory/memory.limit_in_bytes', 'utf8'), 10);
        } else if (fs.existsSync('/sys/fs/cgroup/memory.current')) { // cgroups v2
            usedRam = parseInt(fs.readFileSync('/sys/fs/cgroup/memory.current', 'utf8'), 10);
            totalRam = parseInt(fs.readFileSync('/sys/fs/cgroup/memory.max', 'utf8'), 10);
        }
        
        usedRam = usedRam / (1024 ** 3);
        totalRam = totalRam / (1024 ** 3);
    } catch (e) {
        usedRam = 3.5; // Fallback visuel si hors-linux
    }

    // Si l'IA tourne, on simule l'usage CPU alloué au conteneur
    const activeJobs = Object.values(jobs).some(j => !j.done && !j.error);
    const cpuPercent = activeJobs ? Math.floor(Math.random() * 20) + 75 : 1;

    res.json({
        cpu: cpuPercent,
        usedRam: usedRam.toFixed(1),
        totalRam: Math.round(totalRam),
        ramPercent: Math.round((usedRam / totalRam) * 100)
    });
});

// Route 1 : Soumission du fichier (Réponse immédiate)
app.post('/api/translate', upload.array('mods'), (req, res) => {
    if (!translator) return res.status(503).send("L'IA charge encore son modèle.");
    
    let targetLangs = req.body.langs;
    if (!targetLangs) return res.status(400).send("Aucune langue sélectionnée.");
    if (!Array.isArray(targetLangs)) targetLangs = [targetLangs];

    const jobId = Date.now().toString();
    jobs[jobId] = { percent: 0, status: "Fichier reçu, analyse...", done: false, error: null, base64: null };
    
    res.json({ jobId });

    // Lancement asynchrone en tâche de fond
    processTranslation(jobId, req.files, targetLangs);
});

// Route 2 : Le navigateur demande l'état de sa tâche
app.get('/api/status/:id', (req, res) => {
    const job = jobs[req.params.id];
    if (!job) return res.status(404).json({ error: "Tâche introuvable" });
    res.json(job);
    
    // Nettoyage de la mémoire si c'est fini pour éviter de saturer le Docker
    if (job.done || job.error) {
        setTimeout(() => { delete jobs[req.params.id]; }, 60000);
    }
});

async function processTranslation(jobId, files, targetLangs) {
    const job = jobs[jobId];
    try {
        const outZip = new AdmZip();
        outZip.addFile('pack.mcmeta', Buffer.from(JSON.stringify({
            pack: { pack_format: 15, description: "Traductions générées par IA" }
        }, null, 2)));

        let totalTasks = files.length * targetLangs.length;
        let taskCount = 0;

        for (const file of files) {
            const modZip = new AdmZip(file.buffer);
            const entries = modZip.getEntries();
            const enEntries = entries.filter(e => e.entryName.match(/^assets\/([^\/]+)\/lang\/en_us\.json$/));

            if (enEntries.length === 0) {
                taskCount += targetLangs.length;
                continue;
            }

            for (const enEntry of enEntries) {
                const namespace = enEntry.entryName.split('/')[1];
                const enJson = JSON.parse(modZip.readAsText(enEntry));
                const keys = Object.keys(enJson);
                const texts = Object.values(enJson);

                for (const lang of targetLangs) {
                    taskCount++;
                    job.percent = Math.min(95, Math.floor((taskCount / totalTasks) * 90));
                    job.status = `Traduction [${lang}] de ${namespace}...`;
                    await breathe();

                    const expectedPath = `assets/${namespace}/lang/${lang}.json`;
                    if (entries.some(e => e.entryName === expectedPath)) continue;

                    const translatedJson = {};
                    const batchSize = 4; 

                    for (let i = 0; i < texts.length; i += batchSize) {
                        const batchTexts = texts.slice(i, i + batchSize);
                        const batchKeys = keys.slice(i, i + batchSize);

                        const promises = batchTexts.map(text => 
                            translator(text, { src_lang: 'eng_Latn', tgt_lang: LANG_MAP[lang] || 'fra_Latn' })
                        );
                        
                        const batchResults = await Promise.all(promises);

                        batchResults.forEach((res, index) => {
                            translatedJson[batchKeys[index]] = res[0].translation_text;
                        });
                        await breathe(); 
                    }

                    outZip.addFile(expectedPath, Buffer.from(JSON.stringify(translatedJson, null, 2), 'utf-8'));
                }
            }
        }

        job.percent = 100;
        job.status = "Terminé !";
        job.base64 = outZip.toBuffer().toString('base64');
        job.done = true;

    } catch (err) {
        job.error = err.message;
    }
}

app.listen(7860, '0.0.0.0', () => console.log('🚀 Serveur prêt sur le port 7860'));