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index.js

@@ -1,76 +1,199 @@
-import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.7.6';
+import { pipeline, TextStreamer } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.8.0';
+
+// DOM Elements
+const chatMessages = document.getElementById('chatMessages');
+const userInput = document.getElementById('userInput');
+const sendButton = document.getElementById('sendButton');
+const modelStatus = document.getElementById('modelStatus');
+const statusText = document.getElementById('statusText');
+const progressFill = document.getElementById('progressFill');
+
+// State
+let generator = null;
+let conversationHistory = [
+{ role: "system", content: "You are a helpful, friendly AI assistant. Provide clear, concise, and accurate responses." }
+];
+let isGenerating = false;
+
+// Initialize the application
+async function init() {
+try {
+updateStatus('Loading AI model...', 0);
+
+// Create text generation pipeline with progress tracking
+generator = await pipeline(
+"text-generation",
+"onnx-community/Llama-3.2-1B-Instruct-q4f16",
+{
+dtype: "q4f16",
+device: "webgpu",
+progress_callback: (progress) => {
+if (progress.status === 'progress') {
+const percentage = Math.round((progress.loaded / progress.total) * 100);
+updateStatus(`Loading model: ${progress.file}`, percentage);
+}
+}
+}
+);
+
+updateStatus('Model ready!', 100);
+
+// Enable input after model is loaded
+setTimeout(() => {
+modelStatus.classList.add('ready');
+userInput.disabled = false;
+sendButton.disabled = false;
+userInput.focus();
+}, 500);
+
+} catch (error) {
+console.error('Error initializing model:', error);
+updateStatus('Error loading model. Please refresh the page.', 0);
+statusText.style.color = '#FF3B30';
+}
+}
 
-// 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');
+// Update status display
+function updateStatus(message, progress) {
+statusText.textContent = message;
+progressFill.style.width = `${progress}%`;
+}
 
-const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg';
+// Add message to chat
+function addMessage(role, content, isStreaming = false) {
+const messageDiv = document.createElement('div');
+messageDiv.className = `message ${role}`;
+
+const avatar = document.createElement('div');
+avatar.className = 'message-avatar';
+avatar.textContent = role === 'user' ? '👤' : '🤖';
+
+const contentDiv = document.createElement('div');
+contentDiv.className = 'message-content';
+
+if (isStreaming) {
+contentDiv.innerHTML = `
+<div class="typing-indicator">
+  <div class="typing-dot"></div>
+  <div class="typing-dot"></div>
+  <div class="typing-dot"></div>
+</div>
+`;
+} else {
+contentDiv.innerHTML = formatMessage(content);
+}
 
-// Create a new object detection pipeline
-status.textContent = 'Loading model...';
-const detector = await pipeline('object-detection', 'Xenova/detr-resnet-50');
-status.textContent = 'Ready';
+messageDiv.appendChild(avatar);
+messageDiv.appendChild(contentDiv);
 
-example.addEventListener('click', (e) => {
-    e.preventDefault();
-    detect(EXAMPLE_URL);
-});
+// Remove welcome message if it exists
+const welcomeMessage = chatMessages.querySelector('.welcome-message');
+if (welcomeMessage) {
+welcomeMessage.remove();
+}
 
-fileUpload.addEventListener('change', function (e) {
-    const file = e.target.files[0];
-    if (!file) {
-        return;
-    }
+chatMessages.appendChild(messageDiv);
+chatMessages.scrollTop = chatMessages.scrollHeight;
 
-    const reader = new FileReader();
+return contentDiv;
+}
 
-    // Set up a callback when the file is loaded
-    reader.onload = e2 => detect(e2.target.result);
+// Format message content
+function formatMessage(text) {
+// Simple formatting for line breaks
+return text
+.split('\n')
+.map(line => line.trim() ? `<p>${escapeHtml(line)}</p>` : '')
+.join('');
+}
 
-    reader.readAsDataURL(file);
+// Escape HTML to prevent XSS
+function escapeHtml(text) {
+const div = document.createElement('div');
+div.textContent = text;
+return div.innerHTML;
+}
+
+// Handle message sending
+async function sendMessage() {
+const message = userInput.value.trim();
+if (!message || isGenerating || !generator) return;
+
+// Add user message
+addMessage('user', message);
+conversationHistory.push({ role: "user", content: message });
+
+// Clear input
+userInput.value = '';
+userInput.style.height = 'auto';
+
+// Disable input while generating
+isGenerating = true;
+userInput.disabled = true;
+sendButton.disabled = true;
+
+try {
+// Add assistant message placeholder with typing indicator
+const assistantContentDiv = addMessage('assistant', '', true);
+let fullResponse = '';
+
+// Create streamer for real-time output
+const streamer = new TextStreamer(generator.tokenizer, {
+skip_prompt: true,
+skip_special_tokens: true,
+callback_function: (text) => {
+fullResponse += text;
+assistantContentDiv.innerHTML = formatMessage(fullResponse);
+chatMessages.scrollTop = chatMessages.scrollHeight;
+}
+});
+
+// Generate response
+const output = await generator(conversationHistory, {
+max_new_tokens: 512,
+do_sample: true,
+temperature: 0.7,
+top_p: 0.9,
+streamer: streamer
 });
 
+// Get the final generated text
+const finalResponse = output[0].generated_text.at(-1).content;
+
+// Update conversation history
+conversationHistory.push({ role: "assistant", content: finalResponse });
 
-// Detect objects in the image
-async function detect(img) {
-    imageContainer.innerHTML = '';
-    imageContainer.style.backgroundImage = `url(${img})`;
+// Ensure final response is displayed
+assistantContentDiv.innerHTML = formatMessage(finalResponse);
 
-    status.textContent = 'Analysing...';
-    const output = await detector(img, {
-        threshold: 0.5,
-        percentage: true,
-    });
-    status.textContent = '';
-    output.forEach(renderBox);
+} catch (error) {
+console.error('Error generating response:', error);
+addMessage('assistant', 'Sorry, I encountered an error. Please try again.');
+} finally {
+// Re-enable input
+isGenerating = false;
+userInput.disabled = false;
+sendButton.disabled = false;
+userInput.focus();
+}
 }
 
-// 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);
+// Auto-resize textarea
+userInput.addEventListener('input', function() {
+this.style.height = 'auto';
+this.style.height = Math.min(this.scrollHeight, 120) + 'px';
+});
+
+// Handle Enter key
+userInput.addEventListener('keydown', (e) => {
+if (e.key === 'Enter' && !e.shiftKey) {
+e.preventDefault();
+sendMessage();
 }
+});
+
+// Send button click
+sendButton.addEventListener('click', sendMessage);
+
+// Initialize app when page loads
+init();