#!/usr/bin/env node
// ear.js — the NPU-accelerated trained ear. Embeddings come from FLM's
// embed-gemma:300m running on the NPU (/v1/embeddings); the voice head is a
// 111KB JSON applied right here in JS. No python, no extra runtimes.
//
//   node bin/ear.js "some text to identify"            (one-shot)
//   node bin/ear.js --server-check                     (is an embed-capable flm up?)
//
// Programmatic: const { identify } = require('./ear'); await identify(text)
'use strict';
const fs = require('fs');
const path = require('path');
const http = require('http');

const HEAD = JSON.parse(fs.readFileSync(path.join(__dirname, '..', 'ear', 'head.json'), 'utf8'));
const BASE = process.env.FLM_BASE || 'http://localhost:52625';

function post(urlStr, body) {
  return new Promise((resolve, reject) => {
    const u = new URL(urlStr);
    const data = JSON.stringify(body);
    const req = http.request({ hostname: u.hostname, port: u.port, path: u.pathname, method: 'POST',
      headers: { 'Content-Type': 'application/json', 'Content-Length': Buffer.byteLength(data) }, timeout: 60000 },
      res => { let b = ''; res.on('data', c => b += c); res.on('end', () => { try { resolve(JSON.parse(b)); } catch (e) { reject(new Error('bad json: ' + b.slice(0, 200))); } }); });
    req.on('error', reject);
    req.on('timeout', () => { req.destroy(); reject(new Error('timeout')); });
    req.write(data); req.end();
  });
}

async function embed(text) {
  let r;
  try {
    r = await post(BASE + '/v1/embeddings', { model: 'embed-gemma:300m', input: text });
  } catch (e) {
    if (/ECONNRESET|socket hang up/i.test(e.message)) {           // FLM closes TCP per request; back off once
      await new Promise(res => setTimeout(res, 400));
      r = await post(BASE + '/v1/embeddings', { model: 'embed-gemma:300m', input: text });
    } else throw e;
  }
  const v = r.data && r.data[0] && r.data[0].embedding;
  if (!v) throw new Error('no embedding in response: ' + JSON.stringify(r).slice(0, 200));
  // normalize (head was trained on normalized embeddings)
  const n = Math.sqrt(v.reduce((s, x) => s + x * x, 0)) || 1;
  return v.map(x => x / n);
}

function applyHead(v) {
  const { W, b, labels } = HEAD;
  const logits = b.slice();
  for (let i = 0; i < v.length; i++) {
    const wi = W[i];
    for (let j = 0; j < logits.length; j++) logits[j] += v[i] * wi[j];
  }
  const m = Math.max(...logits);
  const exps = logits.map(x => Math.exp(x - m));
  const Z = exps.reduce((a, x) => a + x, 0);
  const probs = exps.map(x => x / Z);
  const top = probs.indexOf(Math.max(...probs));
  return { label: labels[top], confidence: +probs[top].toFixed(3),
    all: Object.fromEntries(labels.map((l, j) => [l, +probs[j].toFixed(3)])) };
}

async function identify(text) {
  const t0 = Date.now();
  const v = await embed(text);
  const out = applyHead(v);
  out.ms = Date.now() - t0;
  return out;
}

module.exports = { identify, applyHead, embed };

if (require.main === module) {
  (async () => {
    const arg = process.argv.slice(2).join(' ');
    if (arg === '--server-check') {
      try { await embed('hello'); console.log('embed endpoint OK at ' + BASE); }
      catch (e) { console.log('embed endpoint unavailable: ' + e.message.slice(0, 120)); console.log('start one with: flm serve embed-gemma:300m --embed 1   (or flm serve <chat-model> --embed 1)'); }
      return;
    }
    if (!arg) { console.error('usage: node bin/ear.js "text"  |  --server-check'); process.exit(1); }
    try {
      console.log(JSON.stringify(await identify(arg), null, 2));
    } catch (e) {
      console.error('ear error: ' + e.message);
      process.exit(1);
    }
  })();
}