WeLe Agentic AI with Docker deployment

2026-08-28 09:19:05 +05:30
parent 6bb0ef25ca
commit 2fb6a0640c
6 changed files with 128 additions and 28 deletions
@@ -0,0 +1,46 @@
+/* English-only footprint: does it fit the 768 MB container cap on AWS?
+
+   Loads exactly what an English-only deployment needs and reports RSS after
+   each stage, so the answer is measured rather than estimated.
+*/
+const mb = () => Math.round(process.memoryUsage().rss / 1048576);
+const step = (label) => console.log(`  ${label.padEnd(34)} RSS ${String(mb()).padStart(4)} MB`);
+
+step('baseline (node + agent code)');
+
+const { synthesize, transcribe, Endpointer } = await import('../src/speech/index.js');
+step('after importing speech module');
+
+// VAD
+const ep = new Endpointer();
+await ep.push(new Float32Array(16000));
+step('+ Silero VAD');
+
+// TTS English
+const spoken = await synthesize('There are three thousand four hundred and twenty seven new leads.', 'en');
+step('+ MMS-TTS English');
+
+// STT
+const resample = (a, from, to) => {
+  const r = from / to, out = new Float32Array(Math.floor(a.length / r));
+  for (let i = 0; i < out.length; i++) { const p = i * r, k = Math.floor(p); out[i] = a[k] + (a[Math.min(k + 1, a.length - 1)] - a[k]) * (p - k); }
+  return out;
+};
+const audio = resample(spoken.audio, spoken.sampling_rate, 16000);
+const heard = await transcribe(audio, 'en', 'en');
+step('+ Whisper base (STT)');
+
+// Steady state: a few turns, to see whether it keeps growing.
+for (let i = 0; i < 3; i++) {
+  await synthesize('Checking the leads now.', 'en');
+  await transcribe(audio, 'en', 'en');
+}
+step('after 3 more turns');
+
+console.log(`\n  transcript: ${JSON.stringify(heard.text)}`);
+console.log(`  TTS rate  : ${spoken.sampling_rate} Hz`);
+
+const peak = mb();
+const CAP = 768;
+console.log(`\n  peak ${peak} MB vs ${CAP} MB container cap → ${peak < CAP * 0.8 ? 'FITS ✅' : peak < CAP ? 'TIGHT ⚠️' : 'EXCEEDS ❌'}`);
+process.exit(0);