/** * NEURAL NEXUS - Main Application Controller * Real-Time Conversational AI Agent */ class NeuralNexusApp { constructor() { // State Management this.state = { isListening: false, isSpeaking: false, isThinking: false, toolsActive: false, sessionStartTime: Date.now(), latency: 45, messages: [], currentTranscript: '', sessionTimer: null }; // DOM Elements this.elements = { // Main UI messageInput: document.getElementById('message-input'), sendBtn: document.getElementById('send-btn'), voiceBtn: document.getElementById('voice-btn'), transcriptContainer: document.getElementById('transcript-container'), latencyDisplay: document.getElementById('latency-display'), sessionTimer: document.getElementById('session-timer'), // Avatar and Visualizers avatar: document.getElementById('ai-avatar'), agentVisualizer: document.getElementById('agent-visualizer'), userVisualizer: document.getElementById('user-visualizer'), statusIndicator: document.getElementById('main-status'), // Tool Status toolStatus: document.getElementById('tool-status'), toolStatusText: document.getElementById('tool-status-text'), // Neural Network Canvas neuralCanvas: document.getElementById('neural-network-canvas'), // Settings settingsModal: document.getElementById('settings-modal'), settingsBtn: document.getElementById('settings-btn'), closeSettings: document.getElementById('close-settings'), // FABs pdfUploadBtn: document.getElementById('pdf-upload-btn'), pdfFileInput: document.getElementById('pdf-file-input'), webSearchBtn: document.getElementById('web-search-btn'), connectTwitterBtn: document.getElementById('connect-twitter-btn'), // Chat controls clearChatBtn: document.getElementById('clear-chat'), exportChatBtn: document.getElementById('export-chat'), fullscreenBtn: document.getElementById('fullscreen-btn') }; // Initialize subsystems this.initializeNeuralNetworkCanvas(); this.initializeEventListeners(); this.initializeSessionTimer(); this.simulateLatency(); } /** * Initialize neural network background animation */ initializeNeuralNetworkCanvas() { const canvas = this.elements.neuralCanvas; const ctx = canvas.getContext('2d'); const resizeCanvas = () => { canvas.width = canvas.offsetWidth * window.devicePixelRatio; canvas.height = canvas.offsetHeight * window.devicePixelRatio; ctx.scale(window.devicePixelRatio, window.devicePixelRatio); }; resizeCanvas(); window.addEventListener('resize', resizeCanvas); // Neural network nodes and connections const nodes = []; const connections = []; // Create nodes for (let i = 0; i < 50; i++) { nodes.push({ x: Math.random() * canvas.offsetWidth, y: Math.random() * canvas.offsetHeight, vx: (Math.random() - 0.5) * 0.5, vy: (Math.random() - 0.5) * 0.5, size: Math.random() * 2 + 1 }); } // Create connections for (let i = 0; i < nodes.length; i++) { for (let j = i + 1; j < nodes.length; j++) { const dist = Math.hypot(nodes[i].x - nodes[j].x, nodes[i].y - nodes[j].y); if (dist < 150) { connections.push({ from: i, to: j, alpha: Math.random() }); } } } let animationFrame; const animate = () => { ctx.clearRect(0, 0, canvas.offsetWidth, canvas.offsetHeight); // Update and draw nodes nodes.forEach(node => { node.x += node.vx; node.y += node.vy; // Bounce off edges if (node.x < 0 || node.x > canvas.offsetWidth) node.vx *= -1; if (node.y < 0 || node.y > canvas.offsetHeight) node.vy *= -1; // Draw node ctx.beginPath(); ctx.arc(node.x, node.y, node.size, 0, Math.PI * 2); ctx.fillStyle = '#8b5cf6'; ctx.fill(); }); // Draw connections connections.forEach(conn => { const from = nodes[conn.from]; const to = nodes[conn.to]; const dist = Math.hypot(from.x - to.x, from.y - to.y); if (dist < 150) { ctx.beginPath(); ctx.moveTo(from.x, from.y); ctx.lineTo(to.x, to.y); const alpha = (1 - dist / 150) * 0.3; ctx.strokeStyle = `rgba(139, 92, 246, ${alpha})`; ctx.stroke(); } }); animationFrame = requestAnimationFrame(animate); }; animate(); } /** * Initialize all event listeners */ initializeEventListeners() { // Message input this.elements.messageInput.addEventListener('input', (e) => { const hasValue = e.target.value.trim().length > 0; this.elements.sendBtn.disabled = !hasValue; this.elements.sendBtn.classList.toggle('opacity-50', !hasValue); }); this.elements.messageInput.addEventListener('keypress', (e) => { if (e.key === 'Enter' && !e.shiftKey) { e.preventDefault(); this.sendMessage(); } }); // Send button this.elements.sendBtn.addEventListener('click', () => this.sendMessage()); // Voice button this.elements.voiceBtn.addEventListener('click', () => this.toggleVoice()); // Settings modal this.elements.settingsBtn.addEventListener('click', () => { this.elements.settingsModal.classList.remove('hidden'); this.elements.settingsModal.classList.add('flex'); }); this.elements.closeSettings.addEventListener('click', () => { this.elements.settingsModal.classList.add('hidden'); this.elements.settingsModal.classList.remove('flex'); }); // FABs this.elements.pdfUploadBtn.addEventListener('click', () => { this.elements.pdfFileInput.click(); }); this.elements.pdfFileInput.addEventListener('change', (e) => this.handlePDFUpload(e)); this.elements.webSearchBtn.addEventListener('click', () => this.toggleWebSearch()); this.elements.connectTwitterBtn.addEventListener('click', () => this.connectTwitterSpaces()); // Chat controls this.elements.clearChatBtn.addEventListener('click', () => this.clearChat()); this.elements.exportChatBtn.addEventListener('click', () => this.exportChat()); this.elements.fullscreenBtn.addEventListener('click', () => this.toggleFullscreen()); } /** * Session timer */ initializeSessionTimer() { const updateTimer = () => { const elapsed = Date.now() - this.state.sessionStartTime; const hours = Math.floor(elapsed / 3600000).toString().padStart(2, '0'); const minutes = Math.floor((elapsed % 3600000) / 60000).toString().padStart(2, '0'); const seconds = Math.floor((elapsed % 60000) / 1000).toString().padStart(2, '0'); this.elements.sessionTimer.textContent = `${hours}:${minutes}:${seconds}`; }; updateTimer(); this.state.sessionTimer = setInterval(updateTimer, 1000); } /** * Simulate latency variation */ simulateLatency() { setInterval(() => { // Simulate network latency between 30-70ms this.state.latency = Math.floor(Math.random() * 40) + 30; this.elements.latencyDisplay.textContent = `${this.state.latency}ms`; }, 3000); } /** * Send message handler */ async sendMessage() { const message = this.elements.messageInput.value.trim(); if (!message || this.state.isThinking) return; // Add user message to transcript this.addMessageToTranscript({ speaker: 'user', text: message, timestamp: new Date() }); this.elements.messageInput.value = ''; this.elements.sendBtn.disabled = true; this.elements.sendBtn.classList.add('opacity-50'); // Show user waveform briefly this.elements.userVisualizer.style.opacity = '1'; setTimeout(() => { this.elements.userVisualizer.style.opacity = '0'; }, 1000); // Process message through AI pipeline await this.processAIMessage(message); } /** * Add message to transcript UI */ addMessageToTranscript(message) { const messageEl = document.createElement('div'); messageEl.className = 'flex items-start space-x-3 animate-slide-up'; const isUser = message.speaker === 'user'; const timeStr = message.timestamp.toLocaleTimeString('en-US', { hour12: false, hour: '2-digit', minute: '2-digit', second: '2-digit' }); messageEl.innerHTML = `

${message.text}

${timeStr}
`; this.elements.transcriptContainer.appendChild(messageEl); this.elements.transcriptContainer.scrollTop = this.elements.transcriptContainer.scrollHeight; // Re-render feather icons feather.replace(); } /** * Process AI message with simulated pipeline */ async processAIMessage(userMessage) { // Set thinking state this.state.isThinking = true; this.elements.statusIndicator.setStatus('thinking'); // Simulate LLM processing time (target: <800ms) const thinkingTime = Math.random() * 400 + 300; // 300-700ms await this.delay(thinkingTime); // Simulate tool usage for certain queries if (userMessage.toLowerCase().includes('search') || userMessage.toLowerCase().includes('what is')) { await this.executeTool('web-search', 'Searching web for information...'); } // Generate AI response (simulated) const responses = [ "I've analyzed your query. Based on real-time data processing, I can confirm that the latency metrics are well within acceptable parameters. The system is operating at optimal performance.", "Processing complete. I've integrated the information into my context window. The neural pathways are firing at peak efficiency, with sub-50ms audio processing latency maintained.", "Interesting question! Let me search my knowledge base... Ah yes, I found relevant information. The vector embeddings show high similarity scores for this topic.", "I'm detecting a knowledge gap in my training data. Initiating web search protocol... Stand by for real-time information retrieval.", "Analysis complete. The PDF document has been successfully processed and indexed. You can now query its contents naturally in our conversation." ]; const response = responses[Math.floor(Math.random() * responses.length)]; // Update status to speaking this.state.isThinking = false; this.elements.statusIndicator.setStatus('speaking'); this.elements.avatar.startSpeaking(); // Add AI message to transcript with typing effect await this.typeMessage({ speaker: 'agent', text: response, timestamp: new Date() }); // Show agent waveform this.elements.agentVisualizer.style.opacity = '1'; // Simulate speaking duration const speakingTime = response.length * 50; // ~50ms per character setTimeout(() => { this.elements.avatar.stopSpeaking(); this.elements.statusIndicator.setStatus('idle'); this.elements.agentVisualizer.style.opacity = '0'; }, speakingTime); } /** * Typewriter effect for AI messages */ async typeMessage(message) { const messageEl = document.createElement('div'); messageEl.className = 'flex items-start space-x-3 animate-slide-up'; const timeStr = message.timestamp.toLocaleTimeString('en-US', { hour12: false, hour: '2-digit', minute: '2-digit', second: '2-digit' }); messageEl.innerHTML = `