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index.js

@@ -1,76 +1,180 @@
-import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.7.6';
-
-// Reference the elements that we will need
-const status = document.getElementById('status');
-const fileUpload = document.getElementById('upload');
-const imageContainer = document.getElementById('container');
-const example = document.getElementById('example');
+// Configuration
+const MODEL_ID = 'onnx-community/Supertonic-TTS-ONNX';
+const VOICE_BASE_URL = 'https://huggingface.co/onnx-community/Supertonic-TTS-ONNX/resolve/main/voices/';
+
+// DOM Elements
+const generateBtn = document.getElementById('generate-btn');
+const inputText = document.getElementById('input-text');
+const voiceSelect = document.getElementById('voice-select');
+const gpuToggle = document.getElementById('gpu-toggle');
+const deviceLabel = document.getElementById('device-label');
+const statusContainer = document.getElementById('status-container');
+const statusText = document.getElementById('status-text');
+const progressBar = document.getElementById('progress-bar');
+const outputCard = document.getElementById('output-card');
+const audioPlayer = document.getElementById('audio-player');
+const downloadLink = document.getElementById('download-link');
+const errorMsg = document.getElementById('error-msg');
+
+// State
+let ttsPipeline = null;
+let currentDevice = 'cpu';
+
+// Helper: Check WebGPU support
+async function checkWebGPU() {
+    if (!navigator.gpu) {
+        gpuToggle.disabled = true;
+        deviceLabel.innerText = "WebGPU not supported (CPU only)";
+        return false;
+    }
+    return true;
+}
 
-const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg';
+checkWebGPU();
 
-// Create a new object detection pipeline
-status.textContent = 'Loading model...';
-const detector = await pipeline('object-detection', 'Xenova/detr-resnet-50');
-status.textContent = 'Ready';
+// UI Event Listeners
+gpuToggle.addEventListener('change', (e) => {
+    const useGPU = e.target.checked;
+    currentDevice = useGPU ? 'webgpu' : 'cpu';
+    deviceLabel.innerText = useGPU ? 'Run on WebGPU' : 'Run on CPU';
+    
+    // Reset pipeline to force reload with new device setting next time
+    ttsPipeline = null; 
+});
 
-example.addEventListener('click', (e) => {
-    e.preventDefault();
-    detect(EXAMPLE_URL);
+inputText.addEventListener('input', () => {
+    document.querySelector('.char-count').innerText = `${inputText.value.length} / 500`;
 });
 
-fileUpload.addEventListener('change', function (e) {
-    const file = e.target.files[0];
-    if (!file) {
-        return;
+generateBtn.addEventListener('click', async () => {
+    const text = inputText.value.trim();
+    if (!text) return;
+
+    resetUI();
+    statusContainer.classList.remove('hidden');
+    generateBtn.disabled = true;
+
+    try {
+        // 1. Initialize Pipeline if needed
+        if (!ttsPipeline) {
+            updateStatus('Loading model... (this may take a moment)', 0);
+            
+            // Import pipeline from window (set in HTML)
+            const { pipeline } = window;
+
+            ttsPipeline = await pipeline('text-to-speech', MODEL_ID, {
+                device: currentDevice,
+                dtype: 'fp32', // Required for this specific model as per prompt
+                progress_callback: (data) => {
+                    if (data.status === 'progress') {
+                        updateStatus(`Downloading ${data.file}...`, data.progress);
+                    } else if (data.status === 'ready') {
+                        updateStatus('Model ready!', 100);
+                    }
+                }
+            });
+        }
+
+        // 2. Generate Audio
+        updateStatus('Generating audio...', 100);
+        progressBar.classList.add('pulsing'); // Add animation for inference time
+
+        const voiceFile = voiceSelect.value;
+        const speaker_embeddings = `${VOICE_BASE_URL}${voiceFile}`;
+
+        // Run inference
+        const output = await ttsPipeline(text, {
+            speaker_embeddings: speaker_embeddings
+        });
+
+        // 3. Process Output
+        // output.audio is a Float32Array, output.sampling_rate is a number
+        const wavUrl = createWavUrl(output.audio, output.sampling_rate);
+        
+        audioPlayer.src = wavUrl;
+        downloadLink.href = wavUrl;
+        
+        outputCard.classList.remove('hidden');
+        // Auto-play result
+        try {
+            await audioPlayer.play();
+        } catch (e) {
+            console.log("Auto-play blocked by browser policy");
+        }
+
+    } catch (err) {
+        console.error(err);
+        showError(err.message);
+    } finally {
+        generateBtn.disabled = false;
+        progressBar.classList.remove('pulsing');
+        statusContainer.classList.add('hidden');
     }
+});
 
-    const reader = new FileReader();
-
-    // Set up a callback when the file is loaded
-    reader.onload = e2 => detect(e2.target.result);
+// Helper: Update Progress UI
+function updateStatus(text, progressPercent) {
+    statusText.innerText = text;
+    progressBar.style.width = `${progressPercent}%`;
+}
 
-    reader.readAsDataURL(file);
-});
+function resetUI() {
+    outputCard.classList.add('hidden');
+    errorMsg.classList.add('hidden');
+    progressBar.style.width = '0%';
+}
 
+function showError(msg) {
+    errorMsg.innerText = `Error: ${msg}`;
+    errorMsg.classList.remove('hidden');
+}
 
-// Detect objects in the image
-async function detect(img) {
-    imageContainer.innerHTML = '';
-    imageContainer.style.backgroundImage = `url(${img})`;
+// Audio Utility: Convert Float32Array to WAV Blob URL
+function createWavUrl(audioData, sampleRate) {
+    const buffer = encodeWAV(audioData, sampleRate);
+    const blob = new Blob([buffer], { type: 'audio/wav' });
+    return URL.createObjectURL(blob);
+}
 
-    status.textContent = 'Analysing...';
-    const output = await detector(img, {
-        threshold: 0.5,
-        percentage: true,
-    });
-    status.textContent = '';
-    output.forEach(renderBox);
+function encodeWAV(samples, sampleRate) {
+    const buffer = new ArrayBuffer(44 + samples.length * 2);
+    const view = new DataView(buffer);
+
+    // RIFF chunk descriptor
+    writeString(view, 0, 'RIFF');
+    view.setUint32(4, 36 + samples.length * 2, true);
+    writeString(view, 8, 'WAVE');
+
+    // fmt sub-chunk
+    writeString(view, 12, 'fmt ');
+    view.setUint32(16, 16, true);
+    view.setUint16(20, 1, true); // PCM format
+    view.setUint16(22, 1, true); // Mono
+    view.setUint32(24, sampleRate, true);
+    view.setUint32(28, sampleRate * 2, true);
+    view.setUint16(32, 2, true);
+    view.setUint16(34, 16, true); // 16-bit
+
+    // data sub-chunk
+    writeString(view, 36, 'data');
+    view.setUint32(40, samples.length * 2, true);
+
+    // Write PCM samples
+    floatTo16BitPCM(view, 44, samples);
+
+    return buffer;
 }
 
-// Render a bounding box and label on the image
-function renderBox({ box, label }) {
-    const { xmax, xmin, ymax, ymin } = box;
-
-    // Generate a random color for the box
-    const color = '#' + Math.floor(Math.random() * 0xFFFFFF).toString(16).padStart(6, 0);
-
-    // Draw the box
-    const boxElement = document.createElement('div');
-    boxElement.className = 'bounding-box';
-    Object.assign(boxElement.style, {
-        borderColor: color,
-        left: 100 * xmin + '%',
-        top: 100 * ymin + '%',
-        width: 100 * (xmax - xmin) + '%',
-        height: 100 * (ymax - ymin) + '%',
-    })
-
-    // Draw label
-    const labelElement = document.createElement('span');
-    labelElement.textContent = label;
-    labelElement.className = 'bounding-box-label';
-    labelElement.style.backgroundColor = color;
-
-    boxElement.appendChild(labelElement);
-    imageContainer.appendChild(boxElement);
+function writeString(view, offset, string) {
+    for (let i = 0; i < string.length; i++) {
+        view.setUint8(offset + i, string.charCodeAt(i));
+    }
 }
+
+function floatTo16BitPCM(view, offset, input) {
+    for (let i = 0; i < input.length; i++, offset += 2) {
+        let s = Math.max(-1, Math.min(1, input[i]));
+        s = s < 0 ? s * 0x8000 : s * 0x7FFF;
+        view.setInt16(offset, s, true);
+    }
+}