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<!DOCTYPE html>
<html lang="en">
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width,initial-scale=1" />
<title>Local AI (JS only)</title>
<style>
  body { font-family: system-ui, sans-serif; max-width: 820px; margin: 24px auto; padding: 0 12px; }
  textarea { width: 100%; min-height: 140px; }
  button, select { padding: 10px 14px; margin: 6px 6px 0 0; }
  .row { margin: 16px 0; }
  #log { white-space: pre-wrap; font: 13px/1.4 monospace; background:#f6f6f6; padding:12px; border-radius:8px; }
  #out { min-height: 48px; }
</style>

<h2>Local AI on your device (JS only)</h2>

<div class="row">
  <label>Task:
    <select id="task">
      <option value="sentiment">Sentiment (DistilBERT)</option>
      <option value="summarize">Summarize (T5-small)</option>
      <option value="whisper">Transcribe (Whisper tiny.en)</option>
    </select>
  </label>
  <button id="initBtn">Load model</button>
</div>

<div class="row" id="textRow">
  <textarea id="text" placeholder="Type or paste text…"></textarea>
  <button id="runBtn" disabled>Run</button>
</div>

<div class="row" id="audioRow" style="display:none">
  <button id="recBtn" disabled>🎙️ Start / Stop Recording</button>
  <button id="transcribeBtn" disabled>Transcribe</button>
</div>

<h3>Output</h3>
<div id="out"></div>

<h3>Log</h3>
<div id="log"></div>

<script type="module">
  import { pipeline, read_audio } from "https://cdn.jsdelivr.net/npm/@xenova/transformers";

  const $ = (id) => document.getElementById(id);
  const log = (s) => $('log').textContent += s + "\n";
  const out = (html) => $('out').innerHTML = html;

  let runner = null;

  // --- Recording state ---
  let audioCtx = null, processor = null, inputNode = null, stream = null;
  let pcmChunks = []; // Float32 chunks
  let wavBlob = null; // built on stop

  function enableTextUI(en) { $('runBtn').disabled = !en; }
  function enableAudioUI(en) { $('recBtn').disabled = !en; $('transcribeBtn').disabled = true; }
  function toggleTaskUI() {
    const isWhisper = ($('task').value === 'whisper');
    $('textRow').style.display = isWhisper ? 'none' : '';
    $('audioRow').style.display = isWhisper ? '' : 'none';
    $('log').textContent = ''; out('');
    enableTextUI(false); enableAudioUI(false);
  }
  $('task').addEventListener('change', toggleTaskUI);
  toggleTaskUI();

  // --- Robust progress (0–1 or 0–100) ---
  let lastPct = -1, lastTime = 0;
  function progressLogger(p) {
    let pct = null;
    if (p && typeof p.progress === 'number') pct = (p.progress <= 1 ? p.progress * 100 : p.progress);
    else if (p && p.loaded && p.total) pct = (p.loaded / p.total) * 100;
    if (pct == null) return;
    pct = Math.max(0, Math.min(100, Math.round(pct)));
    const now = performance.now();
    if (pct !== lastPct && (now - lastTime > 120)) { log(`Download: ${pct}%`); lastPct = pct; lastTime = now; }
  }

  // --- Load model ---
  $('initBtn').onclick = async () => {
    try {
      $('log').textContent = ''; out('');
      runner = null; enableTextUI(false); enableAudioUI(false);
      lastPct = -1; lastTime = 0;

      const task = $('task').value;
      log('Loading… (first time may download model to cache)');

      if (task === 'sentiment') {
        runner = await pipeline("text-classification",
          "Xenova/distilbert-base-uncased-finetuned-sst-2-english",
          { progress_callback: progressLogger });
        log('Model ready ✅'); enableTextUI(true);

      } else if (task === 'summarize') {
        runner = await pipeline("summarization", "Xenova/t5-small",
          { progress_callback: progressLogger });
        log('Model ready ✅'); enableTextUI(true);

      } else {
        runner = await pipeline("automatic-speech-recognition",
          "Xenova/whisper-tiny.en",
          { progress_callback: progressLogger, chunk_length_s: 15, stride_length_s: 2 });
        log('Model ready ✅'); enableAudioUI(true);
      }
    } catch (e) {
      log('Error loading model: ' + (e?.message ?? e));
    }
  };

  // --- Run text tasks ---
  $('runBtn').onclick = async () => {
    if (!runner) return log('Load a model first.');
    const task = $('task').value, txt = $('text').value.trim();
    if (!txt) return out('<i>Enter some text.</i>');
    out('Running…');
    try {
      if (task === 'sentiment') {
        const res = await runner(txt);
        out(`<pre>${JSON.stringify(res, null, 2)}</pre>`);
      } else {
        // T5: "summarize: " + chunking
        const MAX = 2000; const chunks = [];
        for (let i = 0; i < txt.length; i += MAX) chunks.push(txt.slice(i, i + MAX));
        const parts = [];
        for (const c of chunks) {
          const r = await runner(`summarize: ${c}`, { max_new_tokens: 120 });
          parts.push(Array.isArray(r) ? r[0]?.summary_text : r?.summary_text);
        }
        out(`<div><b>Summary:</b><br>${parts.join(' ')}</div>`);
      }
    } catch (e) { out(''); log('Run error: ' + (e?.message ?? e)); }
  };

  // --- Record PCM, then encode WAV (so read_audio can decode) ---
  $('recBtn').onclick = async () => {
    try {
      if (processor) {
        // Stop recording
        processor.disconnect(); inputNode.disconnect();
        if (stream) stream.getTracks().forEach(t => t.stop());
        const rate = audioCtx.sampleRate;
        wavBlob = encodeWAV(pcmChunks, rate); // audio/wav
        // reset
        pcmChunks = [];
        if (audioCtx) { try { await audioCtx.close(); } catch(_){} }
        audioCtx = null; processor = null; inputNode = null; stream = null;

        $('recBtn').textContent = '🎙️ Start / Stop Recording';
        $('transcribeBtn').disabled = false;
        out('Recording stopped. Tap Transcribe.');
        return;
      }

      // Start
      stream = await navigator.mediaDevices.getUserMedia({ audio: true });
      audioCtx = new (window.AudioContext || window.webkitAudioContext)();
      inputNode = audioCtx.createMediaStreamSource(stream);
      processor = audioCtx.createScriptProcessor(4096, 1, 1);
      processor.onaudioprocess = e => {
        const ch = e.inputBuffer.getChannelData(0);
        pcmChunks.push(new Float32Array(ch)); // copy
      };
      inputNode.connect(processor);
      processor.connect(audioCtx.destination);

      $('recBtn').textContent = '⏹️ Stop';
      $('transcribeBtn').disabled = true;
      out('Recording… speak now.');
    } catch (e) {
      log('Mic error (use http://localhost & allow mic): ' + e.name + ' - ' + e.message);
    }
  };

  function encodeWAV(chunks, sampleRate) {
    const length = chunks.reduce((a, b) => a + b.length, 0);
    const buffer = new ArrayBuffer(44 + length * 2);
    const view = new DataView(buffer);
    const write = (o, s) => { for (let i = 0; i < s.length; i++) view.setUint8(o+i, s.charCodeAt(i)); };
    write(0, 'RIFF'); view.setUint32(4, 36 + length * 2, true); write(8, 'WAVE'); write(12, 'fmt ');
    view.setUint32(16, 16, true); view.setUint16(20, 1, true); view.setUint16(22, 1, true);
    view.setUint32(24, sampleRate, true); view.setUint32(28, sampleRate * 2, true);
    view.setUint16(32, 2, true); view.setUint16(34, 16, true); write(36, 'data'); view.setUint32(40, length * 2, true);
    let offset = 44;
    for (const chunk of chunks) for (let i = 0; i < chunk.length; i++, offset += 2) {
      const s = Math.max(-1, Math.min(1, chunk[i]));
      view.setInt16(offset, s < 0 ? s * 0x8000 : s * 0x7FFF, true);
    }
    return new Blob([buffer], { type: 'audio/wav' });
  }

  // --- Transcribe (read_audio(URL, 16000) → Float32Array → pipeline) ---
  $('transcribeBtn').onclick = async () => {
    if (!runner) return log('Load Whisper tiny.en first.');
    if (!wavBlob) return log('No audio recorded.');
    out('Transcribing…');
    try {
      const url = URL.createObjectURL(wavBlob);
      const audio = await read_audio(url, 16000); // returns Float32Array at 16kHz
      URL.revokeObjectURL(url);
      const result = await runner(audio);
      out(`<div><b>Transcript:</b><br>${result.text}</div>`);
    } catch (e) {
      out(''); log('ASR error: ' + (e?.message ?? e));
    } finally {
      wavBlob = null; $('transcribeBtn').disabled = true;
    }
  };

  // Env info
  log('Secure origin required for mic: use http://localhost');
  log('WebGPU available: ' + (!!navigator.gpu));
  if ('deviceMemory' in navigator) log('deviceMemory (GB bucket): ' + navigator.deviceMemory);
</script>
</html>