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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Agent Training - Quantum Music Synthesizer</title>
<link rel="icon" type="image/x-icon" href="/static/favicon.ico">
<script src="https://cdn.tailwindcss.com"></script>
<script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/animejs/lib/anime.iife.min.js"></script>
<script src="https://unpkg.com/feather-icons"></script>
<style>
:root {
--quantum-purple: #6e45e2;
--quantum-teal: #88d3ce;
--quantum-pink: #ff2a6d;
--quantum-blue: #05d9e8;
--quantum-dark: #0c0f1f;
--quantum-darker: #080a1a;
}
.quantum-bg {
background: linear-gradient(135deg, var(--quantum-dark), var(--quantum-darker));
position: relative;
overflow: hidden;
}
.quantum-bg::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background:
radial-gradient(circle at 10% 20%, rgba(110, 69, 226, 0.1) 0%, transparent 20%),
radial-gradient(circle at 90% 80%, rgba(136, 211, 206, 0.1) 0%, transparent 20%),
radial-gradient(circle at 50% 50%, rgba(5, 217, 232, 0.05) 0%, transparent 30%);
z-index: 0;
}
.quantum-card {
background: rgba(255, 255, 255, 0.05);
backdrop-filter: blur(10px);
border: 1px solid rgba(255, 255, 255, 0.1);
border-radius: 16px;
transition: all 0.3s ease;
}
.quantum-card:hover {
transform: translateY(-5px);
box-shadow: 0 10px 30px rgba(110, 69, 226, 0.2);
border-color: rgba(110, 69, 226, 0.3);
}
.quantum-header {
background: rgba(12, 15, 31, 0.8);
backdrop-filter: blur(10px);
position: sticky;
top: 0;
z-index: 100;
border-bottom: 1px solid rgba(255, 255, 255, 0.05);
}
.quantum-nav a {
position: relative;
padding: 8px 0;
}
.quantum-nav a::after {
content: '';
position: absolute;
bottom: 0;
left: 0;
width: 0;
height: 2px;
background: var(--quantum-blue);
transition: width 0.3s ease;
}
.quantum-nav a:hover::after {
width: 100%;
}
.training-progress {
height: 12px;
background: rgba(255, 255, 255, 0.1);
border-radius: 6px;
overflow: hidden;
}
.progress-bar {
height: 100%;
background: linear-gradient(90deg, var(--quantum-purple), var(--quantum-teal));
border-radius: 6px;
width: 0%;
transition: width 0.5s ease;
}
.metric-card {
background: rgba(26, 30, 45, 0.7);
border: 1px solid rgba(110, 69, 226, 0.2);
border-radius: 12px;
padding: 1.5rem;
}
.neural-network {
position: relative;
height: 300px;
background: rgba(10, 12, 25, 0.7);
border-radius: 12px;
overflow: hidden;
border: 1px solid rgba(110, 69, 226, 0.2);
}
.neuron {
position: absolute;
width: 20px;
height: 20px;
border-radius: 50%;
background: var(--quantum-purple);
box-shadow: 0 0 10px rgba(110, 69, 226, 0.5);
}
.connection {
position: absolute;
height: 2px;
background: rgba(136, 211, 206, 0.3);
transform-origin: left;
}
.quantum-btn {
background: linear-gradient(45deg, var(--quantum-purple), var(--quantum-teal));
border: none;
border-radius: 30px;
padding: 12px 20px;
font-weight: 600;
transition: all 0.3s ease;
color: white;
}
.quantum-btn:hover {
transform: translateY(-3px);
box-shadow: 0 5px 20px rgba(110, 69, 226, 0.4);
}
.log-entry {
padding: 0.75rem;
border-bottom: 1px solid rgba(255, 255, 255, 0.05);
font-family: monospace;
font-size: 0.9rem;
}
.log-entry:last-child {
border-bottom: none;
}
.log-info { color: #05d9e8; }
.log-success { color: #88d3ce; }
.log-warning { color: #ffcc00; }
.log-error { color: #ff2a6d; }
</style>
</head>
<body class="bg-gray-900 text-white min-h-screen">
<div class="quantum-bg min-h-screen">
<!-- Header -->
<header class="quantum-header container mx-auto py-4 px-4">
<div class="flex justify-between items-center">
<h1 class="text-3xl font-bold">Quantum Music Synthesizer</h1>
<nav class="quantum-nav">
<ul class="flex space-x-8">
<li><a href="index.html" class="hover:text-purple-300 font-medium">Home</a></li>
<li><a href="synthesizer.html" class="hover:text-purple-300 font-medium">Synthesizer</a></li>
<li><a href="quantum.html" class="hover:text-purple-300 font-medium">Quantum</a></li>
<li><a href="visualization.html" class="hover:text-purple-300 font-medium">Visualization</a></li>
<li><a href="about.html" class="hover:text-purple-300 font-medium">About</a></li>
<li><a href="api.html" class="hover:text-purple-300 font-medium">API</a></li>
<li><a href="agent.html" class="hover:text-purple-300 font-medium">Agent</a></li>
</ul>
</nav>
</div>
</header>
<!-- Agent Training Section -->
<section class="container mx-auto py-16 px-4">
<h1 class="text-4xl font-bold text-center mb-4">Agent Training Dashboard</h1>
<p class="text-xl text-center mb-12 text-gray-300">Monitor and control AI agent training for quantum music composition</p>
<div class="max-w-6xl mx-auto">
<!-- Training Controls -->
<div class="quantum-card p-8 mb-8">
<div class="grid grid-cols-1 md:grid-cols-2 gap-8">
<div>
<h2 class="text-2xl font-bold mb-4">Training Controls</h2>
<div class="space-y-4">
<div>
<label class="block mb-2">Epochs</label>
<input type="range" min="1" max="1000" value="100" class="w-full slider">
<div class="flex justify-between text-sm mt-1">
<span>1</span>
<span id="epoch-value">100</span>
<span>1000</span>
</div>
</div>
<div>
<label class="block mb-2">Learning Rate</label>
<input type="range" min="0.0001" max="0.1" step="0.0001" value="0.001" class="w-full slider">
<div class="flex justify-between text-sm mt-1">
<span>0.0001</span>
<span id="lr-value">0.001</span>
<span>0.1</span>
</div>
</div>
<div class="flex space-x-4 pt-4">
<button id="start-training" class="quantum-btn flex-1">
<i data-feather="play" class="inline mr-2"></i>Start Training
</button>
<button id="pause-training" class="quantum-btn flex-1" disabled>
<i data-feather="pause" class="inline mr-2"></i>Pause
</button>
<button id="stop-training" class="quantum-btn flex-1" disabled>
<i data-feather="square" class="inline mr-2"></i>Stop
</button>
</div>
</div>
</div>
<div>
<h2 class="text-2xl font-bold mb-4">Training Progress</h2>
<div class="space-y-6">
<div>
<div class="flex justify-between mb-2">
<span>Overall Progress</span>
<span id="progress-percent">0%</span>
</div>
<div class="training-progress">
<div class="progress-bar" id="overall-progress"></div>
</div>
</div>
<div>
<div class="flex justify-between mb-2">
<span>Current Epoch</span>
<span id="current-epoch">0/100</span>
</div>
<div class="training-progress">
<div class="progress-bar" id="epoch-progress"></div>
</div>
</div>
<div class="grid grid-cols-2 gap-4">
<div class="metric-card">
<h3 class="font-bold text-lg mb-2">Loss</h3>
<div class="text-2xl font-bold" id="loss-value">0.0000</div>
</div>
<div class="metric-card">
<h3 class="font-bold text-lg mb-2">Accuracy</h3>
<div class="text-2xl font-bold" id="accuracy-value">0.00%</div>
</div>
</div>
</div>
</div>
</div>
</div>
<!-- Neural Network Visualization -->
<div class="quantum-card p-8 mb-8">
<h2 class="text-2xl font-bold mb-6">Neural Network Architecture</h2>
<div class="neural-network" id="network-viz">
<!-- Neurons and connections will be generated by JavaScript -->
</div>
</div>
<!-- Training Logs -->
<div class="quantum-card p-8">
<h2 class="text-2xl font-bold mb-6">Training Logs</h2>
<div class="bg-gray-800/50 rounded-lg p-4 h-64 overflow-y-auto font-mono text-sm" id="training-logs">
<div class="log-entry log-info">[INFO] Initializing quantum music composition agent...</div>
<div class="log-entry log-info">[INFO] Loading dataset: Quantum harmonic sequences</div>
<div class="log-entry log-info">[INFO] Model architecture: LSTM-Transformer hybrid</div>
<div class="log-entry log-info">[INFO] Ready for training. Adjust parameters and click Start.</div>
</div>
</div>
</div>
</section>
<!-- Footer -->
<footer class="container mx-auto py-8 px-4 text-center border-t border-gray-800">
<p class="text-gray-400">Powered by QuantumToolbox.jl, Amazon Braket, and Lindblad Solvers</p>
</footer>
</div>
<script>
feather.replace();
// DOM Elements
const epochValue = document.getElementById('epoch-value');
const lrValue = document.getElementById('lr-value');
const overallProgress = document.getElementById('overall-progress');
const epochProgress = document.getElementById('epoch-progress');
const progressPercent = document.getElementById('progress-percent');
const currentEpoch = document.getElementById('current-epoch');
const lossValue = document.getElementById('loss-value');
const accuracyValue = document.getElementById('accuracy-value');
const trainingLogs = document.getElementById('training-logs');
const startBtn = document.getElementById('start-training');
const pauseBtn = document.getElementById('pause-training');
const stopBtn = document.getElementById('stop-training');
// Slider event listeners
document.querySelectorAll('input[type="range"]')[0].addEventListener('input', function() {
epochValue.textContent = this.value;
});
document.querySelectorAll('input[type="range"]')[1].addEventListener('input', function() {
lrValue.textContent = parseFloat(this.value).toFixed(4);
});
// Training simulation variables
let trainingInterval;
let isTraining = false;
let isPaused = false;
let currentEpochNum = 0;
let totalEpochs = parseInt(document.querySelectorAll('input[type="range"]')[0].value);
let logCounter = 0;
// Log messages for simulation
const logMessages = [
"[INFO] Starting epoch {epoch}...",
"[INFO] Processing quantum harmonic sequences...",
"[INFO] Updating weights with learning rate {lr}",
"[INFO] Loss decreased to {loss}",
"[WARNING] Gradient norm approaching threshold",
"[INFO] Completed epoch {epoch} in {time}ms",
"[INFO] Validation accuracy: {acc}%",
"[INFO] Saving checkpoint..."
];
// Start training
startBtn.addEventListener('click', function() {
if (!isTraining) {
isTraining = true;
isPaused = false;
startBtn.disabled = true;
pauseBtn.disabled = false;
stopBtn.disabled = false;
// Reset values
currentEpochNum = 0;
totalEpochs = parseInt(document.querySelectorAll('input[type="range"]')[0].value);
updateProgress();
// Add log entry
addLogEntry("[INFO] Starting training session...", "log-info");
// Start training interval
trainingInterval = setInterval(runTrainingStep, 500);
} else if (isPaused) {
isPaused = false;
pauseBtn.innerHTML = '<i data-feather="pause" class="inline mr-2"></i>Pause';
feather.replace();
trainingInterval = setInterval(runTrainingStep, 500);
}
});
// Pause training
pauseBtn.addEventListener('click', function() {
if (!isPaused) {
isPaused = true;
clearInterval(trainingInterval);
pauseBtn.innerHTML = '<i data-feather="play" class="inline mr-2"></i>Resume';
feather.replace();
addLogEntry("[INFO] Training paused", "log-info");
} else {
isPaused = false;
pauseBtn.innerHTML = '<i data-feather="pause" class="inline mr-2"></i>Pause';
feather.replace();
trainingInterval = setInterval(runTrainingStep, 500);
addLogEntry("[INFO] Training resumed", "log-info");
}
});
// Stop training
stopBtn.addEventListener('click', function() {
isTraining = false;
isPaused = false;
clearInterval(trainingInterval);
startBtn.disabled = false;
pauseBtn.disabled = true;
stopBtn.disabled = true;
pauseBtn.innerHTML = '<i data-feather="pause" class="inline mr-2"></i>Pause';
feather.replace();
addLogEntry("[INFO] Training stopped by user", "log-info");
});
// Run a single training step
function runTrainingStep() {
if (currentEpochNum >= totalEpochs) {
clearInterval(trainingInterval);
isTraining = false;
startBtn.disabled = false;
pauseBtn.disabled = true;
stopBtn.disabled = true;
addLogEntry("[INFO] Training completed successfully!", "log-success");
return;
}
currentEpochNum++;
// Simulate progress
const epochProgressValue = Math.min(100, Math.floor(Math.random() * 30) + 70);
epochProgress.style.width = epochProgressValue + '%';
// Simulate metrics
const loss = Math.max(0, (1 - currentEpochNum/totalEpochs) * (0.5 + Math.random() * 0.5)).toFixed(4);
const accuracy = Math.min(100, (currentEpochNum/totalEpochs) * (80 + Math.random() * 20)).toFixed(2);
// Update UI
lossValue.textContent = loss;
accuracyValue.textContent = accuracy + '%';
currentEpoch.textContent = `${currentEpochNum}/${totalEpochs}`;
updateProgress();
// Add log entry
if (logCounter % 3 === 0) {
const randomLog = logMessages[Math.floor(Math.random() * logMessages.length)];
const formattedLog = randomLog
.replace('{epoch}', currentEpochNum)
.replace('{lr}', lrValue.textContent)
.replace('{loss}', loss)
.replace('{acc}', accuracy)
.replace('{time}', Math.floor(Math.random() * 2000) + 500);
const logTypes = ['log-info', 'log-success', 'log-warning'];
const logType = logTypes[Math.floor(Math.random() * logTypes.length)];
addLogEntry(formattedLog, logType);
}
logCounter++;
}
// Update overall progress
function updateProgress() {
const progress = (currentEpochNum / totalEpochs) * 100;
overallProgress.style.width = progress + '%';
progressPercent.textContent = Math.round(progress) + '%';
}
// Add log entry
function addLogEntry(message, type) {
const logEntry = document.createElement('div');
logEntry.className = `log-entry ${type}`;
logEntry.textContent = `${new Date().toLocaleTimeString()} ${message}`;
trainingLogs.appendChild(logEntry);
trainingLogs.scrollTop = trainingLogs.scrollHeight;
}
// Create neural network visualization
function createNetworkVisualization() {
const container = document.getElementById('network-viz');
container.innerHTML = '';
// Create layers
const layers = [
{ neurons: 8, x: 50 },
{ neurons: 12, x: 150 },
{ neurons: 16, x: 250 },
{ neurons: 12, x: 350 },
{ neurons: 8, x: 450 }
];
// Store neuron positions
const neuronPositions = [];
// Create neurons
layers.forEach((layer, layerIndex) => {
const layerNeurons = [];
for (let i = 0; i < layer.neurons; i++) {
const neuron = document.createElement('div');
neuron.className = 'neuron';
// Position neurons vertically
const y = 30 + (i * (240 / Math.max(1, layer.neurons - 1)));
neuron.style.left = (layer.x - 10) + 'px';
neuron.style.top = (y - 10) + 'px';
container.appendChild(neuron);
layerNeurons.push({ x: layer.x, y: y });
}
neuronPositions.push(layerNeurons);
});
// Create connections
for (let l = 0; l < neuronPositions.length - 1; l++) {
const currentLayer = neuronPositions[l];
const nextLayer = neuronPositions[l + 1];
currentLayer.forEach(neuron => {
nextLayer.forEach(nextNeuron => {
const connection = document.createElement('div');
connection.className = 'connection';
// Calculate distance and angle
const dx = nextNeuron.x - neuron.x;
const dy = nextNeuron.y - neuron.y;
const length = Math.sqrt(dx * dx + dy * dy);
const angle = Math.atan2(dy, dx) * 180 / Math.PI;
connection.style.width = length + 'px';
connection.style.left = neuron.x + 'px';
connection.style.top = neuron.y + 'px';
connection.style.transform = `rotate(${angle}deg)`;
container.appendChild(connection);
});
});
}
// Animate neurons
animateNeurons();
}
// Animate neurons
function animateNeurons() {
const neurons = document.querySelectorAll('.neuron');
setInterval(() => {
neurons.forEach(neuron => {
if (Math.random() > 0.7) {
neuron.style.opacity = '0.5';
setTimeout(() => {
neuron.style.opacity = '1';
}, 200);
}
});
}, 500);
}
// Initialize when page loads
window.addEventListener('load', function() {
createNetworkVisualization();
});
</script>
</body>
</html> |