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<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Adaptive Alert Triage — Live Dashboard</title>
<meta name="description" content="Real-time RL-powered incident response monitoring dashboard">
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800&display=swap" rel="stylesheet">
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.7/dist/chart.umd.min.js"></script>
<style>
:root {
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* { margin: 0; padding: 0; box-sizing: border-box; }
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.container { max-width: 1480px; margin: 0 auto; padding: 20px 24px; position: relative; z-index: 1; }
/* ── Header ─────────────────────────────────────────────── */
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@keyframes pulse { 0%,100%{opacity:1} 50%{opacity:0.3} }
/* ── Stat cards ─────────────────────────────────────────── */
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/* ── Panels ─────────────────────────────────────────────── */
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.panel-body { padding: 16px 18px; }
/* ── Reasoning box ──────────────────────────────────────── */
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.prob-fill { height: 3px; border-radius: 2px; margin-top: 4px; transition: width 0.3s; }
/* ── Alert cards ────────────────────────────────────────── */
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.severity-indicator {
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display: flex; align-items: center; justify-content: center;
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/* ── Action log ─────────────────────────────────────────── */
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.action-correct { color: var(--accent-green); }
.action-wrong { color: var(--accent-red); }
/* ── Controls ───────────────────────────────────────────── */
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.btn {
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select {
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select:focus { border-color: var(--accent-blue); }
/* ── Chart ──────────────────────────────────────────────── */
.chart-container { position: relative; height: 200px; }
/* ── Step bar ───────────────────────────────────────────── */
.step-bar { height: 4px; background: var(--bg-input); border-radius: 2px; overflow: hidden; margin-top: 10px; }
.step-bar-fill { height: 100%; background: var(--gradient-blue); border-radius: 2px; transition: width 0.3s; }
.step-label { font-size: 10px; color: var(--text-muted); margin-top: 3px; text-align: right; }
/* ── Empty state ────────────────────────────────────────── */
.empty-state { text-align: center; padding: 30px 16px; color: var(--text-muted); font-size: 12px; }
.empty-state .icon { font-size: 28px; margin-bottom: 8px; opacity: 0.4; }
/* ── Help section ───────────────────────────────────────── */
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/* ── Toast ──────────────────────────────────────────────── */
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z-index: 1000; animation: toastIn 0.25s ease-out; box-shadow: var(--shadow-lg);
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@keyframes toastIn { from{opacity:0;transform:translateY(16px)} to{opacity:1;transform:translateY(0)} }
/* ── Tabs & Training ────────────────────────────────────── */
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}
</style>
</head>
<body>
<div class="container">
<!-- ══════ Header ══════ -->
<div class="header">
<div class="header-left">
<div class="logo">🛡️</div>
<div>
<h1>Adaptive Alert Triage</h1>
<div class="header-subtitle">RL-Powered Incident Response Dashboard</div>
</div>
</div>
<div class="header-right">
<div id="agentSource" class="agent-source rule">Rule-Based</div>
<div id="statusBadge" class="status-badge offline">
<div class="status-dot"></div>
<span id="statusText">Connecting…</span>
</div>
</div>
</div>
<!-- ══════ Tabs ══════ -->
<div class="tabs">
<div class="tab active" id="tabLive" onclick="switchTab('live')">Live Testing</div>
<div class="tab" id="tabTrain" onclick="switchTab('train')">Agent Training</div>
</div>
<!-- ══════ Training View ══════ -->
<div class="training-container" id="trainingView">
<h3>Train RL Agent (PPO)</h3>
<p style="color:var(--text-muted); font-size:12px; margin-top:8px; margin-bottom:16px;">Launch background training across varying difficulty tasks.</p>
<div class="controls">
<span style="font-size:12px">Easy Episodes:</span>
<input type="number" id="trainEpisodes" value="300" style="padding:6px; border-radius:6px; border:1px solid var(--border); background:var(--bg-input); color:var(--text-primary); width:100px;">
<button class="btn btn-primary" onclick="startTraining()" id="trainBtn">▶ Start Training</button>
</div>
<div class="terminal" id="trainTerminal">Ready to train. Run PPO to update weights.</div>
<div style="margin-top:12px; display:flex; gap:8px; align-items:center; flex-wrap:wrap;">
<span style="font-size:12px; color:var(--text-muted);">📥 Download Weights:</span>
<button class="btn" onclick="downloadWeights('easy')" style="font-size:11px; padding:4px 10px;">🟢 Easy</button>
<button class="btn" onclick="downloadWeights('medium')" style="font-size:11px; padding:4px 10px;">🟡 Medium</button>
<button class="btn" onclick="downloadWeights('hard')" style="font-size:11px; padding:4px 10px;">🔴 Hard</button>
</div>
</div>
<div class="testing-container active" id="testingView">
<!-- ══════ Action Guide ══════ -->
<div class="help-bar">
<div class="help-item">
<div class="help-icon">🔍</div>
<div class="help-label">Investigate</div>
<div class="help-desc">Deep-dive diagnosis. Uses 1 budget slot. For high-severity, high-confidence alerts.</div>
</div>
<div class="help-item">
<div class="help-icon">🚫</div>
<div class="help-label">Ignore</div>
<div class="help-desc">Dismiss as noise. For low-confidence or known false positives. Saves resources.</div>
</div>
<div class="help-item">
<div class="help-icon">⬆️</div>
<div class="help-label">Escalate</div>
<div class="help-desc">Route to specialist team. No budget cost. For uncertain but severe alerts.</div>
</div>
<div class="help-item">
<div class="help-icon">⏳</div>
<div class="help-label">Delay</div>
<div class="help-desc">Defer to next step. Wait for more info. Risky for critical alerts!</div>
</div>
</div>
<!-- ══════ Stat Cards ══════ -->
<div class="grid-stats">
<div class="stat-card">
<div class="stat-label">Active Alerts</div>
<div class="stat-value" id="statAlerts">—</div>
<div class="stat-sub" id="statQueue">Queue: 0</div>
</div>
<div class="stat-card">
<div class="stat-label">Accuracy</div>
<div class="stat-value" id="statAccuracy">—</div>
<div class="stat-sub" id="statCorrect">0 correct / 0 total</div>
</div>
<div class="stat-card">
<div class="stat-label">Total Reward</div>
<div class="stat-value" id="statReward">0.0</div>
<div class="stat-sub" id="statAvgReward">avg: —</div>
</div>
<div class="stat-card">
<div class="stat-label">Failures</div>
<div class="stat-value" id="statFailures">0</div>
<div class="stat-sub" id="statFailThresh">system crashes</div>
</div>
<div class="stat-card">
<div class="stat-label">Episode</div>
<div class="stat-value" id="statStep">—</div>
<div class="stat-sub" id="statTask">Select task →</div>
</div>
</div>
<!-- ══════ AI Reasoning ══════ -->
<div class="reasoning-box">
<div class="reasoning-card">
<div class="reasoning-header">
<span style="font-size:14px">🧠</span>
<span class="reasoning-label">AI Agent Reasoning</span>
<span id="reasoningSource" style="font-size:10px; color:var(--text-muted); margin-left:auto;">Waiting for episode…</span>
</div>
<div class="reasoning-text" id="reasoningText">
Start a new episode to see the agent's real-time decision explanations. The agent analyzes each alert's
severity, confidence, type, and age to determine the optimal triage action.
</div>
<div class="reasoning-probs" id="reasoningProbs" style="display:none">
<div class="prob-bar">
<div class="prob-label">Investigate</div>
<div class="prob-fill" id="probInv" style="background:var(--accent-blue);width:0%"></div>
<span id="probInvVal" style="font-size:10px;color:var(--text-muted)">—</span>
</div>
<div class="prob-bar">
<div class="prob-label">Ignore</div>
<div class="prob-fill" id="probIgn" style="background:var(--text-muted);width:0%"></div>
<span id="probIgnVal" style="font-size:10px;color:var(--text-muted)">—</span>
</div>
<div class="prob-bar">
<div class="prob-label">Escalate</div>
<div class="prob-fill" id="probEsc" style="background:var(--accent-yellow);width:0%"></div>
<span id="probEscVal" style="font-size:10px;color:var(--text-muted)">—</span>
</div>
<div class="prob-bar">
<div class="prob-label">Delay</div>
<div class="prob-fill" id="probDel" style="background:var(--accent-purple);width:0%"></div>
<span id="probDelVal" style="font-size:10px;color:var(--text-muted)">—</span>
</div>
</div>
</div>
</div>
<!-- ══════ Main Grid ══════ -->
<div class="grid-main">
<!-- Active Alerts -->
<div class="panel">
<div class="panel-header">
<div class="panel-title">📋 Active Alerts</div>
<div class="controls">
<select id="taskSelect">
<option value="easy">🟢 Easy</option>
<option value="medium">🟡 Medium</option>
<option value="hard" selected>🔴 Hard</option>
</select>
<button class="btn btn-primary" onclick="resetEpisode()" id="resetBtn">▶ New Episode</button>
<button class="btn" onclick="stepOnce()" id="stepBtn" disabled>⏭ Step</button>
<button class="btn" onclick="autoPlay()" id="autoBtn" disabled>⚡ Auto</button>
</div>
</div>
<div class="panel-body">
<div id="alertList" class="alert-list">
<div class="empty-state">
<div class="icon">📭</div>
<div>No alerts — click <strong>▶ New Episode</strong> to begin</div>
</div>
</div>
<div class="step-bar"><div class="step-bar-fill" id="stepBar" style="width:0%"></div></div>
<div class="step-label" id="stepLabel">Step 0 / 0</div>
</div>
</div>
<!-- Action Log -->
<div class="panel">
<div class="panel-header">
<div class="panel-title">⚡ Decision Log</div>
<div class="controls">
<span id="logCount" style="font-size:11px;color:var(--text-muted)">0 actions</span>
<button class="btn btn-danger" onclick="clearLog()">Clear</button>
</div>
</div>
<div class="panel-body">
<div id="actionLog" class="action-log">
<div class="empty-state">
<div class="icon">📝</div>
<div>Agent decisions appear here with reasoning</div>
</div>
</div>
</div>
</div>
</div>
<!-- ══════ Bottom Charts ══════ -->
<div class="grid-bottom">
<div class="panel">
<div class="panel-header">
<div class="panel-title">📊 Episode Scores</div>
<span id="avgScore" style="font-size:11px;color:var(--text-muted)">avg: —</span>
</div>
<div class="panel-body">
<div class="chart-container"><canvas id="scoreChart"></canvas></div>
</div>
</div>
<div class="panel">
<div class="panel-header">
<div class="panel-title">📈 Reward Trend</div>
<span id="avgRewardLabel" style="font-size:11px;color:var(--text-muted)">cumulative</span>
</div>
<div class="panel-body">
<div class="chart-container"><canvas id="rewardChart"></canvas></div>
</div>
</div>
<div class="panel">
<div class="panel-header">
<div class="panel-title">🎯 Action Distribution</div>
</div>
<div class="panel-body">
<div class="chart-container"><canvas id="actionChart"></canvas></div>
</div>
</div>
</div>
</div> <!-- end testing-container -->
</div>
<script>
// ═══════════════════════════════════════════════════════════════════
// State
// ═══════════════════════════════════════════════════════════════════
const SERVER = 'https://tusharp2006-scaler-deployment.hf.space';
let currentAlerts = [];
let episodeScores = [];
let episodeRewards = [];
let rewardTimeline = []; // per-step cumulative
let actionCounts = { INVESTIGATE:0, IGNORE:0, ESCALATE:0, DELAY:0 };
let episodeDone = true;
let autoPlaying = false;
let currentStep = 0, maxSteps = 50;
let correctCount = 0, totalSteps = 0, totalReward = 0;
let currentTask = 'hard';
let agentSource = 'rule_based';
// ═══════════════════════════════════════════════════════════════════
// Charts
// ═══════════════════════════════════════════════════════════════════
const chartFont = { family: 'Inter', size: 11 };
const gridColor = 'rgba(255,255,255,0.04)';
const tickColor = '#64748b';
const scoreChart = new Chart(document.getElementById('scoreChart'), {
type: 'line',
data: {
labels: [],
datasets: [
{ label: 'Score', data: [], borderColor: '#3b82f6', backgroundColor: 'rgba(59,130,246,0.08)',
fill: true, tension: 0.4, pointRadius: 4, pointBackgroundColor: '#3b82f6', borderWidth: 2 },
{ label: 'Threshold', data: [], borderColor: 'rgba(239,68,68,0.5)',
borderDash: [6,3], borderWidth: 1.5, pointRadius: 0, fill: false }
]
},
options: {
responsive: true, maintainAspectRatio: false,
scales: { y: { min:0, max:1, grid:{color:gridColor}, ticks:{color:tickColor,font:chartFont} }, x: { grid:{display:false}, ticks:{color:tickColor,font:chartFont} } },
plugins: { legend: { labels: { color:'#94a3b8', font:chartFont } } }
}
});
const rewardChart = new Chart(document.getElementById('rewardChart'), {
type: 'line',
data: {
labels: [],
datasets: [
{ label: 'Cumulative Reward', data: [], borderColor: '#10b981', backgroundColor: 'rgba(16,185,129,0.08)',
fill: true, tension: 0.3, pointRadius: 0, borderWidth: 2 }
]
},
options: {
responsive: true, maintainAspectRatio: false,
scales: { y: { grid:{color:gridColor}, ticks:{color:tickColor,font:chartFont} }, x: { grid:{display:false}, ticks:{color:tickColor,font:chartFont,maxTicksLimit:10} } },
plugins: { legend: { labels: { color:'#94a3b8', font:chartFont } } }
}
});
const actionChart = new Chart(document.getElementById('actionChart'), {
type: 'doughnut',
data: {
labels: ['Investigate', 'Ignore', 'Escalate', 'Delay'],
datasets: [{ data: [1,1,1,1], backgroundColor: ['rgba(59,130,246,0.8)','rgba(100,116,139,0.5)','rgba(245,158,11,0.8)','rgba(139,92,246,0.8)'], borderColor: '#111827', borderWidth: 3 }]
},
options: {
responsive: true, maintainAspectRatio: false, cutout: '62%',
plugins: { legend: { position:'bottom', labels: { color:'#94a3b8', font:chartFont, padding:10 } } }
}
});
// ═══════════════════════════════════════════════════════════════════
// API
// ═══════════════════════════════════════════════════════════════════
async function api(method, path, body=null) {
const opts = { method, headers: {'Content-Type':'application/json'} };
if (body) opts.body = JSON.stringify(body);
const r = await fetch(`${SERVER}${path}`, opts);
return r.json();
}
// ═══════════════════════════════════════════════════════════════════
// Polling
// ═══════════════════════════════════════════════════════════════════
async function pollHealth() {
try {
const h = await api('GET', '/health');
const badge = document.getElementById('statusBadge');
const text = document.getElementById('statusText');
if (h.status === 'ok') { badge.className = 'status-badge'; text.textContent = 'Server Online'; }
else throw 0;
} catch { document.getElementById('statusBadge').className = 'status-badge offline'; document.getElementById('statusText').textContent = 'Offline'; }
}
// ═══════════════════════════════════════════════════════════════════
// Episode
// ═══════════════════════════════════════════════════════════════════
async function resetEpisode() {
currentTask = document.getElementById('taskSelect').value;
try {
const data = await api('POST', `/env/reset/${currentTask}`);
if (data.error) { showToast(data.error, 'error'); return; }
const obs = data.obs;
currentAlerts = obs.alerts || [];
currentStep = obs.episode_step || 0;
maxSteps = (obs.time_remaining || 50) + currentStep;
episodeDone = false;
correctCount = 0; totalSteps = 0; totalReward = 0;
rewardTimeline = [];
actionCounts = { INVESTIGATE:0, IGNORE:0, ESCALATE:0, DELAY:0 };
renderAlerts();
updateUI();
document.getElementById('stepBtn').disabled = false;
document.getElementById('autoBtn').disabled = false;
document.getElementById('statTask').textContent = `Task: ${currentTask.toUpperCase()}`;
document.getElementById('reasoningText').textContent = 'Episode started. Agent is analyzing the first set of alerts…';
document.getElementById('reasoningProbs').style.display = 'none';
// Fetch initial recommendation
fetchRecommendation();
showToast(`New ${currentTask} episode started`, 'info');
} catch(e) { showToast('Cannot connect to server', 'error'); }
}
async function fetchRecommendation() {
try {
const rec = await api('GET', '/agent/recommend');
if (rec.error) return;
agentSource = rec.source || 'rule_based';
// Update source badge
const badge = document.getElementById('agentSource');
if (agentSource === 'trained_ppo') {
badge.className = 'agent-source ppo'; badge.textContent = '🧠 Trained PPO';
} else {
badge.className = 'agent-source rule'; badge.textContent = '📏 Rule-Based';
}
// Update reasoning
document.getElementById('reasoningText').textContent = rec.reasoning || '';
document.getElementById('reasoningSource').textContent =
agentSource === 'trained_ppo'
? `PPO Model • Value: ${rec.value_estimate ?? '—'}`
: 'Rule-Based Policy';
// Update probability bars if available
const probsDiv = document.getElementById('reasoningProbs');
if (rec.probabilities) {
probsDiv.style.display = 'flex';
for (const [key, id, colorVar] of [['INVESTIGATE','Inv','--accent-blue'],['IGNORE','Ign','--text-muted'],['ESCALATE','Esc','--accent-yellow'],['DELAY','Del','--accent-purple']]) {
const val = rec.probabilities[key] || 0;
const pct = (val * 100).toFixed(1);
document.getElementById(`prob${id}`).style.width = `${val * 100}%`;
document.getElementById(`prob${id}Val`).textContent = `${pct}%`;
}
} else { probsDiv.style.display = 'none'; }
return rec;
} catch { return null; }
}
async function stepOnce() {
if (episodeDone) return false;
if (!currentAlerts.length) return 'wait'; // Queue temporarily empty, wait for environmental spawn
// Get recommendation from server (uses trained weights or rule-based)
const rec = await fetchRecommendation();
if (!rec || rec.error) {
if (!currentAlerts.length) return 'wait';
showToast('No recommendation available', 'error');
return false;
}
return await executeAction(rec.alert_id, rec.action_type, rec.reasoning);
}
async function executeAction(alertId, actionType, reasoning) {
if (episodeDone) return false;
const alert = currentAlerts.find(a => a.id === alertId);
try {
const data = await api('POST', '/env/step', { alert_id: alertId, action_type: actionType });
if (data.error) { showToast(data.error, 'error'); return false; }
const info = data.info || {};
totalSteps++;
const isCorrect = info.action_correct || false;
if (isCorrect) correctCount++;
const reward = typeof data.reward === 'number' ? data.reward : 0;
totalReward += reward;
rewardTimeline.push(totalReward);
actionCounts[actionType]++;
// Log
addActionEntry(alertId, actionType, reward, isCorrect, alert, reasoning);
// Update state
currentAlerts = (data.obs && data.obs.alerts) || [];
currentStep = (data.obs && data.obs.episode_step) || currentStep + 1;
document.getElementById('statFailures').textContent = info.failures_count ?? 0;
renderAlerts();
updateUI();
updateRewardChart();
updateActionChart();
if (data.done) {
episodeDone = true;
const score = totalSteps > 0 ? correctCount / totalSteps : 0;
episodeScores.push(score);
episodeRewards.push(totalReward);
updateScoreChart();
document.getElementById('stepBtn').disabled = true;
document.getElementById('autoBtn').disabled = true;
document.getElementById('reasoningText').textContent =
`Episode complete! Final accuracy: ${(score*100).toFixed(1)}% (${correctCount}/${totalSteps} correct). `+
`Total reward: ${totalReward.toFixed(1)}. ${score >= 0.5 ? '✅ Good performance!' : '⚠️ Below threshold — agent needs more training.'}`;
showToast(`Episode done — accuracy: ${(score*100).toFixed(1)}%`, score >= 0.5 ? 'success' : 'error');
return false;
}
// Fetch next recommendation
fetchRecommendation();
return true;
} catch(e) { showToast('Step failed: '+e.message, 'error'); return false; }
}
async function autoPlay() {
if (autoPlaying) { autoPlaying = false; document.getElementById('autoBtn').textContent = '⚡ Auto'; return; }
if (episodeDone) await resetEpisode();
autoPlaying = true;
document.getElementById('autoBtn').textContent = '⏸ Pause';
while (autoPlaying && !episodeDone) {
const ok = await stepOnce();
if (ok === 'wait') {
await new Promise(r => setTimeout(r, 1500)); // Queue empty, wait for environmental spawn
continue;
}
if (ok === false) break;
await new Promise(r => setTimeout(r, 300));
}
autoPlaying = false;
document.getElementById('autoBtn').textContent = '⚡ Auto';
}
async function manualAction(alertId, actionType) {
if (episodeDone) return;
await executeAction(alertId, actionType, `Manual: ${actionType} on ${alertId}`);
}
// ═══════════════════════════════════════════════════════════════════
// Rendering
// ═══════════════════════════════════════════════════════════════════
function sevClass(s) { return s >= 0.75 ? 'sev-critical' : s >= 0.55 ? 'sev-high' : s >= 0.30 ? 'sev-medium' : 'sev-low'; }
function sevLabel(s) { return s >= 0.75 ? 'CRIT' : s >= 0.55 ? 'HIGH' : s >= 0.30 ? 'MED' : 'LOW'; }
function renderAlerts() {
const list = document.getElementById('alertList');
document.getElementById('statAlerts').textContent = currentAlerts.length;
if (!currentAlerts.length) {
list.innerHTML = '<div class="empty-state"><div class="icon">📭</div><div>No active alerts</div></div>';
return;
}
list.innerHTML = currentAlerts.map(a => {
const s = a.visible_severity, c = a.confidence;
return `<div class="alert-card">
<div class="severity-indicator ${sevClass(s)}" title="Severity: ${s.toFixed(2)}">
${sevLabel(s)}
</div>
<div class="alert-info">
<div class="alert-id">${a.id}</div>
<div class="alert-meta">sev: ${s.toFixed(2)} · conf: ${c.toFixed(2)} · age: ${a.age}</div>
</div>
<div class="alert-type-badge">${a.alert_type || a.type || '?'}</div>
<div class="alert-actions">
<button class="btn" onclick="manualAction('${a.id}','INVESTIGATE')" title="Investigate this alert">🔍</button>
<button class="btn" onclick="manualAction('${a.id}','IGNORE')" title="Dismiss as noise">🚫</button>
<button class="btn" onclick="manualAction('${a.id}','ESCALATE')" title="Escalate to specialists">⬆️</button>
<button class="btn" onclick="manualAction('${a.id}','DELAY')" title="Defer decision">⏳</button>
</div>
</div>`;
}).join('');
}
function addActionEntry(alertId, actionType, reward, correct, alert, reasoning) {
const log = document.getElementById('actionLog');
if (log.querySelector('.empty-state')) log.innerHTML = '';
const el = document.createElement('div');
el.className = 'action-entry';
const sev = alert ? alert.visible_severity?.toFixed(2) : '?';
const r = typeof reward === 'number' ? reward.toFixed(1) : '?';
el.innerHTML = `
<span class="action-badge action-${actionType}">${actionType}</span>
<span style="color:var(--text-secondary);flex-shrink:0">${alertId}</span>
<span style="color:var(--text-muted);font-size:10px">sev:${sev}</span>
<span style="color:${reward >= 0 ? 'var(--accent-green)' : 'var(--accent-red)'};font-size:10px;font-weight:600">r:${r}</span>
<span class="action-result ${correct ? 'action-correct' : 'action-wrong'}" style="margin-left:auto;font-weight:600">${correct ? '✓ correct' : '✗ wrong'}</span>
`;
log.prepend(el);
while (log.children.length > 80) log.removeChild(log.lastChild);
document.getElementById('logCount').textContent = `${totalSteps} actions`;
}
function clearLog() {
document.getElementById('actionLog').innerHTML = '<div class="empty-state"><div class="icon">📝</div><div>Cleared</div></div>';
}
function updateUI() {
// Step bar
const pct = maxSteps > 0 ? (currentStep / maxSteps) * 100 : 0;
document.getElementById('stepBar').style.width = pct + '%';
document.getElementById('stepLabel').textContent = `Step ${currentStep} / ${maxSteps}`;
document.getElementById('statStep').textContent = `${currentStep}/${maxSteps}`;
// Accuracy
const acc = totalSteps > 0 ? (correctCount / totalSteps * 100) : 0;
document.getElementById('statAccuracy').textContent = totalSteps > 0 ? `${acc.toFixed(1)}%` : '—';
document.getElementById('statCorrect').textContent = `${correctCount} correct / ${totalSteps} total`;
// Reward
document.getElementById('statReward').textContent = totalReward.toFixed(1);
document.getElementById('statAvgReward').textContent = totalSteps > 0 ? `avg: ${(totalReward/totalSteps).toFixed(2)}/step` : 'avg: —';
}
function updateScoreChart() {
const thresholds = { easy: 0.70, medium: 0.55, hard: 0.50 };
const thresh = thresholds[currentTask] || 0.50;
scoreChart.data.labels = episodeScores.map((_,i) => `Ep ${i+1}`);
scoreChart.data.datasets[0].data = episodeScores;
scoreChart.data.datasets[1].data = episodeScores.map(() => thresh);
scoreChart.update('none');
const avg = episodeScores.length ? (episodeScores.reduce((a,b)=>a+b,0)/episodeScores.length) : 0;
document.getElementById('avgScore').textContent = `avg: ${avg.toFixed(3)} over ${episodeScores.length} episodes`;
}
function updateRewardChart() {
rewardChart.data.labels = rewardTimeline.map((_,i) => i+1);
rewardChart.data.datasets[0].data = rewardTimeline;
rewardChart.update('none');
}
function updateActionChart() {
const vals = [actionCounts.INVESTIGATE, actionCounts.IGNORE, actionCounts.ESCALATE, actionCounts.DELAY];
const total = vals.reduce((a,b)=>a+b,0);
actionChart.data.datasets[0].data = total > 0 ? vals : [1,1,1,1];
actionChart.update('none');
}
function showToast(msg, type='success') {
const el = document.createElement('div');
el.className = `toast toast-${type}`;
el.textContent = msg;
document.body.appendChild(el);
setTimeout(() => el.remove(), 3500);
}
// ═══════════════════════════════════════════════════════════════════
// UI & Tabs
// ═══════════════════════════════════════════════════════════════════
function switchTab(tab) {
document.getElementById('tabLive').className = tab === 'live' ? 'tab active' : 'tab';
document.getElementById('tabTrain').className = tab === 'train' ? 'tab active' : 'tab';
document.getElementById('testingView').className = tab === 'live' ? 'testing-container active' : 'testing-container';
document.getElementById('trainingView').className = tab === 'train' ? 'training-container active' : 'training-container';
}
// ═══════════════════════════════════════════════════════════════════
// Training Webhooks
// ═══════════════════════════════════════════════════════════════════
let trainingInterval = null;
async function startTraining() {
const ep = document.getElementById('trainEpisodes').value || 300;
try {
const r = await api('POST', `/train?episodes=${ep}`);
if(r.error) showToast(r.error, 'error');
else {
showToast('Training started in background!', 'success');
if(!trainingInterval) trainingInterval = setInterval(pollTraining, 2000);
document.getElementById('trainBtn').disabled = true;
}
} catch(e) { showToast('Trainer error', 'error'); }
}
async function pollTraining() {
try {
const r = await api('GET', '/train/status');
if (r.error) return;
const term = document.getElementById('trainTerminal');
if (r.logs && r.logs.length) {
term.textContent = r.logs.join('\n');
term.scrollTop = term.scrollHeight; // Auto-scroll
}
if (!r.is_running) {
if(trainingInterval) { clearInterval(trainingInterval); trainingInterval = null; }
document.getElementById('trainBtn').disabled = false;
} else {
document.getElementById('trainBtn').disabled = true;
}
} catch(e) {}
}
// ═══════════════════════════════════════════════════════════════════
// Weight Downloads
// ═══════════════════════════════════════════════════════════════════
function downloadWeights(taskId) {
const url = `${SERVER}/agent/weights/${taskId}`;
const a = document.createElement('a');
a.href = url;
a.download = `ppo_${taskId}.json`;
document.body.appendChild(a);
a.click();
document.body.removeChild(a);
showToast(`Downloading ${taskId} weights…`, 'info');
}
// ═══════════════════════════════════════════════════════════════════
// Init
// ═══════════════════════════════════════════════════════════════════
pollHealth();
pollTraining();
setInterval(pollHealth, 5000);
if(document.getElementById('tabTrain').className.includes('active')) setInterval(pollTraining, 2000);
</script>
</body>
</html> |