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swarms/docs/swarms_cloud/cloudflare_workers.md

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# Deploy Autonomous Cron Agents with Swarms API on Cloudflare Workers
Deploy intelligent, self-executing AI agents powered by Swarms API on Cloudflare's global edge network. Build production-ready autonomous agents that run on automated schedules, fetch real-time data, perform sophisticated analysis using Swarms AI, and take automated actions across 330+ cities worldwide.
## What Are Autonomous Cron Agents?
Autonomous cron agents combine **Swarms API intelligence** with **Cloudflare Workers edge computing** to create AI-powered systems that:
- **Execute automatically** on predefined schedules without human intervention
- **Fetch real-time data** from external sources (APIs, databases, IoT sensors)
- **Perform intelligent analysis** using specialized Swarms AI agents
- **Take automated actions** based on analysis findings (alerts, reports, decisions)
- **Scale globally** on Cloudflare's edge network with sub-100ms response times worldwide
## Architecture Overview
```
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Cloudflare │ │ Data Sources │ │ Swarms API │
│ Workers Cron │ │ │ │ │
│ "0 */3 * * *" │───▶│ Yahoo Finance │───▶│ Multi-Agent │
│ │ │ Medical APIs │ │ Intelligence │
│ scheduled() │ │ News Feeds │ │ Autonomous │
│ Global Edge │ │ IoT Sensors │ │ Actions │
└─────────────────┘ └─────────────────┘ └─────────────────┘
```
**Key Benefits:**
- **24/7 Autonomous Operation**: Zero human intervention required
- **Global Edge Deployment**: Cloudflare's 330+ city network for ultra-low latency
- **Swarms AI Intelligence**: Live data analysis with specialized AI agents
- **Automated Decision Making**: Smart actions based on Swarms agent insights
- **Enterprise Reliability**: Production-grade error handling and monitoring
## Quick Start: Deploy Autonomous Stock Analysis Agent
Create your first autonomous financial intelligence agent powered by Swarms API and deployed on Cloudflare Workers edge network.
### 1. Cloudflare Workers Project Setup
```bash
# Create new Cloudflare Workers project
npm create cloudflare@latest autonomous-stock-agent
cd autonomous-stock-agent
# Install dependencies for Swarms API integration
npm run start
```
### 2. Configure Cloudflare Workers Cron Schedule
Edit `wrangler.jsonc` to set up autonomous execution:
```jsonc
{
"$schema": "node_modules/wrangler/config-schema.json",
"name": "autonomous-stock-agent",
"main": "src/index.js",
"compatibility_date": "2025-08-03",
"observability": {
"enabled": true
},
"triggers": {
"crons": [
"0 */3 * * *" // Cloudflare Workers cron: autonomous analysis every 3 hours
]
},
"vars": {
"SWARMS_API_KEY": "your-swarms-api-key" // Your Swarms API key
}
}
```
### 3. Cloudflare Workers + Swarms API Implementation
Create `src/index.js`:
```javascript
export default {
// Cloudflare Workers fetch handler - Web interface for monitoring
async fetch(request, env, ctx) {
const url = new URL(request.url);
if (url.pathname === '/') {
return new Response(`
<!DOCTYPE html>
<html>
<head>
<title>Autonomous Stock Intelligence Agent</title>
<style>
body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; max-width: 1000px; margin: 40px auto; padding: 30px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); min-height: 100vh; }
.container { background: white; padding: 40px; border-radius: 15px; box-shadow: 0 20px 40px rgba(0,0,0,0.2); }
.header { text-align: center; margin-bottom: 40px; color: #333; }
.btn { padding: 15px 30px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; border: none; border-radius: 8px; cursor: pointer; font-size: 16px; font-weight: 600; transition: all 0.3s ease; }
.btn:hover { transform: translateY(-2px); box-shadow: 0 10px 25px rgba(102, 126, 234, 0.3); }
.status { background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%); color: white; padding: 20px; border-radius: 10px; margin: 25px 0; text-align: center; font-weight: 600; }
.result { background: #f8f9fa; padding: 25px; border-radius: 10px; margin: 25px 0; white-space: pre-wrap; border-left: 5px solid #667eea; }
.loading { display: none; text-align: center; margin: 30px 0; }
.spinner { border: 4px solid #f3f3f3; border-top: 4px solid #667eea; border-radius: 50%; width: 40px; height: 40px; animation: spin 1s linear infinite; margin: 0 auto 15px; }
@keyframes spin { 0% { transform: rotate(0deg); } 100% { transform: rotate(360deg); } }
.badge { display: inline-block; background: #667eea; color: white; padding: 5px 12px; border-radius: 20px; font-size: 12px; font-weight: 600; margin: 5px; }
</style>
</head>
<body>
<div class="container">
<div class="header">
<h1>🤖 Autonomous Stock Intelligence Agent</h1>
<p>Powered by Swarms API • Running on Cloudflare Workers</p>
<div>
<span class="badge">Swarms AI</span>
<span class="badge">Cloudflare Edge</span>
<span class="badge">Real-time</span>
<span class="badge">Autonomous</span>
</div>
</div>
<div class="status">
<strong>🚀 Status:</strong> Swarms AI agents active on Cloudflare edge, monitoring markets 24/7
</div>
<div style="text-align: center;">
<button class="btn" onclick="executeAnalysis()">⚡ Execute Analysis Now</button>
</div>
<div id="loading" class="loading">
<div class="spinner"></div>
<p><strong>Swarms AI agents analyzing live market data on Cloudflare edge...</strong></p>
</div>
<div id="result"></div>
</div>
<script>
async function executeAnalysis() {
const loadingDiv = document.getElementById('loading');
const resultDiv = document.getElementById('result');
loadingDiv.style.display = 'block';
resultDiv.innerHTML = '';
try {
const response = await fetch('/execute');
const data = await response.json();
loadingDiv.style.display = 'none';
if (data.result?.success) {
resultDiv.innerHTML = \`
<div style="background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%); color: white; padding: 20px; border-radius: 10px; margin-bottom: 25px;">
<h3>✅ Autonomous Analysis Completed</h3>
<p><strong>Symbols Analyzed:</strong> \${data.result.symbolsAnalyzed} | <strong>Execution Cost:</strong> $\${data.result.cost || 'N/A'}</p>
<p><strong>Next Autonomous Execution:</strong> \${data.result.nextExecution || 'Scheduled'}</p>
</div>
<div class="result">
<h3>🧠 Autonomous AI Intelligence Report:</h3>
<pre>\${data.result.analysis || 'No analysis available'}</pre>
</div>
\`;
} else {
resultDiv.innerHTML = \`
<div style="background: linear-gradient(135deg, #ff6b6b 0%, #feca57 100%); color: white; padding: 20px; border-radius: 10px;">
<h3>⚠️ Autonomous Execution Failed</h3>
<p>\${data.result?.error || data.error || 'Unknown error in autonomous system'}</p>
</div>
\`;
}
} catch (error) {
loadingDiv.style.display = 'none';
resultDiv.innerHTML = \`
<div style="background: #ff6b6b; color: white; padding: 20px; border-radius: 10px;">
<h3>❌ Autonomous System Error</h3>
<p>\${error.message}</p>
</div>
\`;
}
}
</script>
</body>
</html>
`, {
headers: { 'Content-Type': 'text/html' }
});
}
if (url.pathname === '/execute') {
try {
const result = await executeAutonomousAnalysis(null, env);
return new Response(JSON.stringify({
message: 'Autonomous analysis executed successfully',
timestamp: new Date().toISOString(),
result
}), {
headers: { 'Content-Type': 'application/json' }
});
} catch (error) {
return new Response(JSON.stringify({
error: error.message,
timestamp: new Date().toISOString(),
system: 'autonomous-agent'
}), {
status: 500,
headers: { 'Content-Type': 'application/json' }
});
}
}
return new Response('Autonomous Agent Endpoint Not Found', { status: 404 });
},
// Cloudflare Workers cron handler - triggered by scheduled events
async scheduled(event, env, ctx) {
console.log('🚀 Cloudflare Workers cron triggered - executing Swarms AI analysis');
ctx.waitUntil(executeAutonomousAnalysis(event, env));
}
};
// Core function combining Cloudflare Workers execution with Swarms API intelligence
async function executeAutonomousAnalysis(event, env) {
console.log('🤖 Cloudflare Workers executing Swarms AI stock intelligence analysis...');
try {
// Step 1: Autonomous data collection from multiple sources
console.log('📊 Executing autonomous data collection...');
const marketIntelligence = await collectMarketIntelligence();
const validData = Object.keys(marketIntelligence).filter(symbol => !marketIntelligence[symbol].error);
if (validData.length === 0) {
throw new Error('Autonomous data collection failed - no valid market intelligence gathered');
}
console.log(\`✅ Autonomous data collection successful: \${validData.length} sources\`);
// Step 2: Deploy Swarms AI agents for autonomous analysis
console.log('🧠 Deploying Swarms AI agents for autonomous intelligence generation...');
const swarmConfiguration = {
name: "Autonomous Market Intelligence Swarm",
description: "Self-executing financial analysis and decision support system",
agents: [
{
agent_name: "Autonomous Technical Intelligence Agent",
system_prompt: \`You are an autonomous technical analysis AI agent operating 24/7. Provide:
- Real-time trend identification and momentum analysis
- Dynamic support/resistance level calculations
- Technical indicator signals (RSI, MACD, moving averages)
- Autonomous price targets and risk assessments
- Self-executing trading signal recommendations
Format your analysis as a professional autonomous intelligence briefing for automated systems.\`,
model_name: "gpt-4o-mini",
max_tokens: 2500,
temperature: 0.2
},
{
agent_name: "Autonomous Market Sentiment Agent",
system_prompt: \`You are an autonomous market sentiment analysis AI agent. Continuously evaluate:
- Real-time market psychology and investor behavior patterns
- Volume analysis and institutional activity detection
- Risk-on vs risk-off sentiment shifts
- Autonomous sector rotation and leadership identification
- Self-executing market timing recommendations
Provide actionable intelligence for autonomous decision-making systems.\`,
model_name: "gpt-4o-mini",
max_tokens: 2500,
temperature: 0.3
}
],
swarm_type: "ConcurrentWorkflow",
task: \`Execute autonomous analysis of real-time market intelligence:
LIVE MARKET INTELLIGENCE:
\${JSON.stringify(marketIntelligence, null, 2)}
Generate comprehensive autonomous intelligence report including:
1. Technical analysis with specific autonomous entry/exit recommendations
2. Market sentiment assessment with timing signals for automated systems
3. Risk management protocols for autonomous execution
4. Self-executing action recommendations
5. Key monitoring parameters for next autonomous cycle
Focus on actionable intelligence for autonomous trading systems and automated decision making.\`,
max_loops: 1
};
// Execute Swarms API call from Cloudflare Workers edge
const response = await fetch('https://api.swarms.world/v1/swarm/completions', {
method: 'POST',
headers: {
'x-api-key': env.SWARMS_API_KEY,
'Content-Type': 'application/json'
},
body: JSON.stringify(swarmConfiguration)
});
if (!response.ok) {
const errorText = await response.text();
throw new Error(\`Swarms API autonomous execution failed: \${response.status} - \${errorText}\`);
}
const analysisResult = await response.json();
const intelligenceReport = analysisResult.output;
console.log('✅ Autonomous Swarms AI analysis completed successfully');
console.log(\`💰 Autonomous execution cost: \${analysisResult.usage?.billing_info?.total_cost || 'N/A'}\`);
// Step 3: Execute autonomous actions based on intelligence
if (env.AUTONOMOUS_ALERTS_EMAIL) {
console.log('📧 Executing autonomous alert system...');
await executeAutonomousAlerts(env, intelligenceReport, marketIntelligence);
}
return {
success: true,
analysis: intelligenceReport,
symbolsAnalyzed: validData.length,
cost: analysisResult.usage?.billing_info?.total_cost || analysisResult.metadata?.billing_info?.total_cost,
executionTime: new Date().toISOString(),
nextExecution: 'Scheduled for next autonomous cron trigger',
autonomousSystem: 'Swarms AI Agents'
};
} catch (error) {
console.error('❌ Autonomous analysis execution failed:', error.message);
return {
success: false,
error: error.message,
executionTime: new Date().toISOString(),
autonomousSystem: 'Error in autonomous pipeline'
};
}
}
// Autonomous market intelligence collection
async function collectMarketIntelligence() {
const targetSymbols = ['SPY', 'QQQ', 'AAPL', 'MSFT', 'NVDA', 'TSLA'];
const marketIntelligence = {};
console.log('🎯 Executing autonomous multi-source data collection...');
const dataCollectionPromises = targetSymbols.map(async (symbol) => {
try {
const controller = new AbortController();
const timeout = setTimeout(() => controller.abort(), 10000);
// Autonomous data collection from Yahoo Finance API
const response = await fetch(
\`https://query1.finance.yahoo.com/v8/finance/chart/\${symbol}\`,
{
signal: controller.signal,
headers: {
'User-Agent': 'Mozilla/5.0 (autonomous-swarms-agent) AppleWebKit/537.36'
}
}
);
clearTimeout(timeout);
if (!response.ok) {
throw new Error(\`Autonomous data collection failed: HTTP \${response.status}\`);
}
const data = await response.json();
const chartResult = data.chart.result[0];
const meta = chartResult.meta;
if (!meta) {
throw new Error('Invalid market intelligence structure received');
}
const currentPrice = meta.regularMarketPrice;
const previousClose = meta.previousClose;
const dayChange = currentPrice - previousClose;
const changePercent = ((dayChange / previousClose) * 100).toFixed(2);
console.log(\`📈 \${symbol}: $\${currentPrice} (\${changePercent}%) - Autonomous collection successful\`);
return [symbol, {
price: currentPrice,
change: dayChange,
change_percent: changePercent,
volume: meta.regularMarketVolume || 0,
market_cap: meta.marketCap || 0,
pe_ratio: meta.trailingPE || 0,
day_high: meta.regularMarketDayHigh,
day_low: meta.regularMarketDayLow,
fifty_two_week_high: meta.fiftyTwoWeekHigh,
fifty_two_week_low: meta.fiftyTwoWeekLow,
currency: meta.currency || 'USD',
market_state: meta.marketState,
autonomous_collection_time: new Date().toISOString(),
data_quality: 'high'
}];
} catch (error) {
console.error(\`❌ Autonomous collection failed for \${symbol}:\`, error.message);
return [symbol, {
error: \`Autonomous collection failed: \${error.message}\`,
autonomous_collection_time: new Date().toISOString(),
data_quality: 'failed'
}];
}
});
const results = await Promise.allSettled(dataCollectionPromises);
results.forEach((result) => {
if (result.status === 'fulfilled' && result.value) {
const [symbol, data] = result.value;
marketIntelligence[symbol] = data;
}
});
const successfulCollections = Object.keys(marketIntelligence).filter(k => !marketIntelligence[k]?.error).length;
console.log(\`📊 Autonomous intelligence collection completed: \${successfulCollections}/\${targetSymbols.length} successful\`);
return marketIntelligence;
}
// Autonomous alert and notification system
async function executeAutonomousAlerts(env, intelligenceReport, marketIntelligence) {
if (!env.MAILGUN_API_KEY || !env.MAILGUN_DOMAIN || !env.AUTONOMOUS_ALERTS_EMAIL) {
console.log('⚠️ Autonomous alert system not configured - skipping notifications');
return;
}
try {
// Autonomous detection of significant market movements
const significantMovements = Object.entries(marketIntelligence)
.filter(([symbol, data]) => data.change_percent && Math.abs(parseFloat(data.change_percent)) > 3)
.map(([symbol, data]) => \`\${symbol}: \${data.change_percent}%\`)
.join(', ');
const alertSubject = \`🤖 Autonomous Market Intelligence Alert - \${new Date().toLocaleDateString()}\`;
const alertBody = \`
<!DOCTYPE html>
<html>
<head>
<style>
body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; line-height: 1.6; color: #333; max-width: 1000px; margin: 0 auto; background: #f8f9fa; }
.container { background: white; margin: 20px; border-radius: 15px; overflow: hidden; box-shadow: 0 15px 35px rgba(0,0,0,0.1); }
.header { background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 40px; text-align: center; }
.content { padding: 40px; }
.autonomous-badge { background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%); color: white; padding: 20px; border-radius: 10px; margin: 25px 0; text-align: center; }
.intelligence-section { background: #f8f9fa; padding: 30px; border-radius: 10px; margin: 25px 0; border-left: 5px solid #667eea; }
.market-data { margin: 25px 0; }
table { width: 100%; border-collapse: collapse; margin: 20px 0; }
th, td { padding: 15px; text-align: left; border-bottom: 1px solid #eee; }
th { background: #f8f9fa; font-weight: 600; color: #333; }
.positive { color: #28a745; font-weight: bold; }
.negative { color: #dc3545; font-weight: bold; }
.footer { background: #f8f9fa; padding: 25px; text-align: center; color: #666; font-size: 14px; }
.badge { display: inline-block; background: #667eea; color: white; padding: 5px 12px; border-radius: 15px; font-size: 12px; font-weight: 600; margin: 3px; }
</style>
</head>
<body>
<div class="container">
<div class="header">
<h1>🤖 Autonomous Market Intelligence</h1>
<p>AI-Powered Autonomous Financial Analysis • Swarms API</p>
<div>
<span class="badge">Autonomous</span>
<span class="badge">Real-time</span>
<span class="badge">AI-Powered</span>
<span class="badge">Global Edge</span>
</div>
<p><strong>Generated:</strong> \${new Date().toLocaleString()}</p>
</div>
<div class="content">
<div class="autonomous-badge">
<h3>🚀 Autonomous Analysis Execution Complete</h3>
<p><strong>Significant Market Movements Detected:</strong> \${significantMovements || 'Market within normal volatility parameters'}</p>
<p><strong>Next Autonomous Cycle:</strong> Scheduled automatically</p>
</div>
<div class="intelligence-section">
<h2>🧠 Autonomous AI Intelligence Report</h2>
<p><em>Generated by autonomous Swarms AI agents with real-time market intelligence:</em></p>
<pre style="white-space: pre-wrap; font-family: 'Courier New', monospace; background: white; padding: 25px; border-radius: 8px; font-size: 13px; line-height: 1.6; border: 1px solid #eee;">\${intelligenceReport}</pre>
</div>
<div class="market-data">
<h2>📊 Real-Time Market Intelligence</h2>
<table>
<thead>
<tr>
<th>Symbol</th>
<th>Price</th>
<th>Change</th>
<th>Volume</th>
<th>Market State</th>
<th>Data Quality</th>
</tr>
</thead>
<tbody>
\${Object.entries(marketIntelligence)
.filter(([symbol, data]) => !data.error)
.map(([symbol, data]) => \`
<tr>
<td><strong>\${symbol}</strong></td>
<td>$\${data.price?.toFixed(2) || 'N/A'}</td>
<td class="\${parseFloat(data.change_percent) >= 0 ? 'positive' : 'negative'}">
\${parseFloat(data.change_percent) >= 0 ? '+' : ''}\${data.change_percent}%
</td>
<td>\${data.volume?.toLocaleString() || 'N/A'}</td>
<td>\${data.market_state || 'N/A'}</td>
<td>\${data.data_quality || 'N/A'}</td>
</tr>
\`).join('')}
</tbody>
</table>
</div>
</div>
<div class="footer">
<p><strong>🤖 Powered by Autonomous Swarms AI Agents</strong></p>
<p>This intelligence report was generated automatically by our autonomous market analysis system</p>
<p><em>Next autonomous analysis will execute automatically on schedule</em></p>
<p>Swarms API • Autonomous Intelligence • Edge Computing</p>
</div>
</div>
</body>
</html>
\`;
const formData = new FormData();
formData.append('from', \`Autonomous Market Intelligence <intelligence@\${env.MAILGUN_DOMAIN}>\`);
formData.append('to', env.AUTONOMOUS_ALERTS_EMAIL);
formData.append('subject', alertSubject);
formData.append('html', alertBody);
const response = await fetch(\`https://api.mailgun.net/v3/\${env.MAILGUN_DOMAIN}/messages\`, {
method: 'POST',
headers: {
'Authorization': \`Basic \${btoa(\`api:\${env.MAILGUN_API_KEY}\`)}\`
},
body: formData
});
if (response.ok) {
console.log('✅ Autonomous alert system executed successfully');
} else {
console.error('❌ Autonomous alert system execution failed:', await response.text());
}
} catch (error) {
console.error('❌ Autonomous alert system error:', error.message);
}
}
```
## Autonomous Healthcare Intelligence Agent
Deploy autonomous healthcare agents that provide 24/7 patient monitoring with intelligent analysis:
```javascript
export default {
async fetch(request, env, ctx) {
const url = new URL(request.url);
if (url.pathname === '/') {
return new Response(`
<!DOCTYPE html>
<html>
<head>
<title>Autonomous Healthcare Intelligence</title>
<style>
body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; max-width: 1200px; margin: 30px auto; padding: 30px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); min-height: 100vh; }
.container { background: white; padding: 50px; border-radius: 20px; box-shadow: 0 25px 50px rgba(0,0,0,0.2); }
.header { text-align: center; margin-bottom: 50px; }
.status-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); gap: 25px; margin: 40px 0; }
.status-card { padding: 25px; border-radius: 15px; text-align: center; color: white; box-shadow: 0 8px 25px rgba(0,0,0,0.15); }
.normal { background: linear-gradient(135deg, #11998e 0%, #38ef7d 100%); }
.warning { background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%); }
.critical { background: linear-gradient(135deg, #ff416c 0%, #ff4b2b 100%); }
.btn { padding: 18px 35px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; border: none; border-radius: 10px; cursor: pointer; font-size: 16px; font-weight: 600; margin: 15px; transition: all 0.3s ease; }
.btn:hover { transform: translateY(-3px); box-shadow: 0 12px 30px rgba(102, 126, 234, 0.4); }
.result { background: #f8f9fa; padding: 30px; border-radius: 12px; margin: 30px 0; border-left: 6px solid #667eea; }
.badge { display: inline-block; background: #667eea; color: white; padding: 6px 15px; border-radius: 20px; font-size: 12px; font-weight: 600; margin: 3px; }
</style>
</head>
<body>
<div class="container">
<div class="header">
<h1>🏥 Autonomous Healthcare Intelligence</h1>
<p>AI-Powered 24/7 Patient Monitoring • Autonomous Medical Analysis</p>
<div>
<span class="badge">Autonomous</span>
<span class="badge">24/7 Monitoring</span>
<span class="badge">AI-Powered</span>
<span class="badge">Real-time</span>
</div>
</div>
<div class="status-grid">
<div class="status-card normal">
<h3>✅ Normal Status</h3>
<p><strong>Patients: 15</strong></p>
<p>Stable vital signs</p>
<p>Autonomous monitoring active</p>
</div>
<div class="status-card warning">
<h3>⚠️ Monitoring Required</h3>
<p><strong>Patients: 3</strong></p>
<p>Elevated parameters</p>
<p>Enhanced surveillance</p>
</div>
<div class="status-card critical">
<h3>🚨 Critical Alert</h3>
<p><strong>Patients: 1</strong></p>
<p>Immediate intervention</p>
<p>Emergency protocols active</p>
</div>
</div>
<div style="text-align: center;">
<button class="btn" onclick="executeHealthIntelligence()">🔍 Execute Health Intelligence Analysis</button>
</div>
<div id="result"></div>
</div>
<script>
async function executeHealthIntelligence() {
document.getElementById('result').innerHTML = '<div style="text-align: center; padding: 30px;"><div style="border: 4px solid #f3f3f3; border-top: 4px solid #667eea; border-radius: 50%; width: 50px; height: 50px; animation: spin 1s linear infinite; margin: 0 auto;"></div><p><strong>Autonomous health intelligence agents analyzing patient data...</strong></p></div>';
try {
const response = await fetch('/health-intelligence');
const data = await response.json();
const severity = data.result?.severity || 'normal';
const severityColors = {
critical: '#ff416c',
warning: '#f093fb',
normal: '#11998e'
};
document.getElementById('result').innerHTML = \`
<div class="result" style="border-left-color: \${severityColors[severity]};">
<h3 style="color: \${severityColors[severity]};">
\${severity === 'critical' ? '🚨 CRITICAL AUTONOMOUS ALERT' : severity === 'warning' ? '⚠️ AUTONOMOUS MONITORING REQUIRED' : '✅ AUTONOMOUS SYSTEMS NORMAL'}
</h3>
<p><strong>Autonomous Analysis Time:</strong> \${new Date(data.timestamp).toLocaleString()}</p>
<p><strong>Patients Under Surveillance:</strong> \${data.result?.patientsAnalyzed || 'N/A'}</p>
<p><strong>Next Autonomous Cycle:</strong> Scheduled automatically</p>
<h4>🤖 Autonomous Health Intelligence Report:</h4>
<pre style="background: white; padding: 25px; border-radius: 10px; white-space: pre-wrap; border: 1px solid #eee;">\${data.result?.analysis || data.error}</pre>
</div>
\`;
} catch (error) {
document.getElementById('result').innerHTML = \`<div class="result" style="border-left-color: #ff416c;"><h3 style="color: #ff416c;">❌ Autonomous System Error</h3><p>\${error.message}</p></div>\`;
}
}
</script>
</body>
</html>
`, {
headers: { 'Content-Type': 'text/html' }
});
}
if (url.pathname === '/health-intelligence') {
try {
const result = await executeAutonomousHealthIntelligence(null, env);
return new Response(JSON.stringify({
message: 'Autonomous health intelligence analysis executed',
timestamp: new Date().toISOString(),
result
}), {
headers: { 'Content-Type': 'application/json' }
});
} catch (error) {
return new Response(JSON.stringify({
error: error.message,
system: 'autonomous-healthcare-intelligence'
}), {
status: 500,
headers: { 'Content-Type': 'application/json' }
});
}
}
return new Response('Autonomous Healthcare Intelligence Endpoint Not Found', { status: 404 });
},
// Autonomous healthcare monitoring - every 30 minutes
async scheduled(event, env, ctx) {
console.log('🏥 Autonomous healthcare intelligence system triggered');
ctx.waitUntil(executeAutonomousHealthIntelligence(event, env));
}
};
async function executeAutonomousHealthIntelligence(event, env) {
console.log('🏥 Autonomous healthcare intelligence system executing...');
try {
// Autonomous patient data collection
const patientIntelligence = await collectPatientIntelligence();
// Deploy autonomous Swarms healthcare AI agents
const healthIntelligenceConfig = {
name: "Autonomous Healthcare Intelligence Swarm",
description: "24/7 autonomous patient monitoring and medical analysis system",
agents: [
{
agent_name: "Autonomous Vital Signs Intelligence Agent",
system_prompt: \`You are an autonomous healthcare AI agent providing 24/7 patient monitoring. Analyze:
- Continuous heart rate monitoring and arrhythmia detection (Normal: 60-100 bpm)
- Autonomous blood pressure trend analysis (Normal: <140/90 mmHg)
- Real-time oxygen saturation monitoring (Normal: >95%)
- Continuous temperature surveillance (Normal: 97-99°F)
Classify each patient autonomously as: NORMAL_MONITORING, ENHANCED_SURVEILLANCE, or CRITICAL_INTERVENTION
For critical findings, trigger autonomous emergency protocols.\`,
model_name: "gpt-4o-mini",
max_tokens: 2500,
temperature: 0.05
},
{
agent_name: "Autonomous Medical Risk Assessment Agent",
system_prompt: \`You are an autonomous medical AI providing continuous risk assessment. Monitor:
- Autonomous drug interaction analysis and medication safety
- Real-time disease progression and complication detection
- Continuous fall risk and mobility assessment
- Autonomous emergency intervention requirements
Provide autonomous risk stratification and intervention priorities.
Focus on predictive analytics and early autonomous warning systems.\`,
model_name: "gpt-4o-mini",
max_tokens: 2500,
temperature: 0.05
}
],
swarm_type: "ConcurrentWorkflow",
task: \`Execute autonomous 24/7 healthcare intelligence analysis:
PATIENT INTELLIGENCE DATA:
\${JSON.stringify(patientIntelligence, null, 2)}
Generate autonomous healthcare intelligence including:
1. Individual patient autonomous risk assessment and monitoring status
2. Critical autonomous intervention requirements and emergency protocols
3. Autonomous alert recommendations and escalation procedures
4. Predictive health analytics and preventive care suggestions
5. Next autonomous monitoring cycle parameters and priorities
Focus on autonomous decision support for medical staff and emergency response systems.\`,
max_loops: 1
};
const response = await fetch('https://api.swarms.world/v1/swarm/completions', {
method: 'POST',
headers: {
'x-api-key': env.SWARMS_API_KEY,
'Content-Type': 'application/json'
},
body: JSON.stringify(healthIntelligenceConfig)
});
if (!response.ok) {
throw new Error(\`Autonomous healthcare intelligence failed: \${response.status}\`);
}
const result = await response.json();
const healthIntelligence = result.output;
// Autonomous severity assessment
const severity = assessAutonomousHealthSeverity(healthIntelligence);
console.log(\`✅ Autonomous healthcare intelligence completed - Severity: \${severity}\`);
// Autonomous emergency response system
if (severity === 'critical' && env.HEALTHCARE_EMERGENCY_EMAIL) {
console.log('🚨 Executing autonomous emergency response protocol...');
await executeAutonomousEmergencyResponse(env, healthIntelligence, patientIntelligence);
}
return {
success: true,
analysis: healthIntelligence,
severity: severity,
patientsAnalyzed: Object.keys(patientIntelligence).length,
executionTime: new Date().toISOString(),
nextAutonomousMonitoring: 'Scheduled for next autonomous cycle',
autonomousSystem: 'Swarms Healthcare AI'
};
} catch (error) {
console.error('❌ Autonomous healthcare intelligence failed:', error.message);
return {
success: false,
error: error.message,
severity: 'autonomous_system_error',
executionTime: new Date().toISOString()
};
}
}
// Autonomous patient intelligence collection
async function collectPatientIntelligence() {
// In production, connect to EMR systems, IoT devices, and medical databases
return {
"ICU_Autonomous_001": {
name: "Sarah Johnson",
age: 68,
room: "ICU-205",
condition: "Post-cardiac surgery - autonomous monitoring",
vitals: {
heart_rate: 95,
blood_pressure_systolic: 135,
blood_pressure_diastolic: 88,
oxygen_saturation: 97,
temperature: 98.8,
respiratory_rate: 16
},
medications: ["Metoprolol", "Warfarin", "Furosemide"],
risk_factors: ["Diabetes", "Hypertension", "Previous MI"],
autonomous_monitoring_level: "enhanced",
last_updated: new Date().toISOString()
},
"Ward_Autonomous_002": {
name: "Michael Chen",
age: 45,
room: "Ward-301",
condition: "Pneumonia recovery - autonomous surveillance",
vitals: {
heart_rate: 88,
blood_pressure_systolic: 128,
blood_pressure_diastolic: 82,
oxygen_saturation: 94, // Slightly low - autonomous flag
temperature: 100.1, // Mild fever - autonomous flag
respiratory_rate: 20
},
medications: ["Azithromycin", "Albuterol"],
risk_factors: ["Asthma", "Smoking history"],
autonomous_monitoring_level: "standard",
last_updated: new Date().toISOString()
},
"Critical_Autonomous_003": {
name: "Elena Rodriguez",
age: 72,
room: "ICU-208",
condition: "Sepsis - autonomous critical monitoring",
vitals: {
heart_rate: 115, // Elevated - autonomous critical flag
blood_pressure_systolic: 85, // Low - autonomous critical flag
blood_pressure_diastolic: 55, // Low - autonomous critical flag
oxygen_saturation: 89, // Critical - autonomous emergency flag
temperature: 103.2, // High fever - autonomous critical flag
respiratory_rate: 28 // Elevated - autonomous critical flag
},
medications: ["Vancomycin", "Norepinephrine", "Hydrocortisone"],
risk_factors: ["Sepsis", "Multi-organ dysfunction", "Advanced age"],
autonomous_monitoring_level: "critical",
last_updated: new Date().toISOString()
}
};
}
function assessAutonomousHealthSeverity(intelligenceReport) {
const reportText = typeof intelligenceReport === 'string' ? intelligenceReport : JSON.stringify(intelligenceReport);
if (reportText.includes('CRITICAL_INTERVENTION') ||
reportText.includes('EMERGENCY') ||
reportText.includes('IMMEDIATE_ACTION') ||
reportText.includes('SEPSIS') ||
reportText.includes('CARDIAC_ARREST') ||
reportText.includes('RESPIRATORY_FAILURE')) {
return 'critical';
} else if (reportText.includes('ENHANCED_SURVEILLANCE') ||
reportText.includes('ELEVATED') ||
reportText.includes('CONCERNING') ||
reportText.includes('ABNORMAL') ||
reportText.includes('MONITORING_REQUIRED')) {
return 'warning';
}
return 'normal';
}
async function executeAutonomousEmergencyResponse(env, intelligenceReport, patientIntelligence) {
console.log('🚨 Autonomous emergency response protocol executing...');
// Autonomous emergency response would include:
// - Immediate medical team notifications
// - Automated equipment preparation alerts
// - Emergency response coordination
// - Real-time escalation to on-call physicians
// - Integration with hospital emergency systems
}
```
## Deployment & Configuration
### Environment Variables
Configure your Cloudflare Workers deployment with Swarms API:
```jsonc
{
"vars": {
"SWARMS_API_KEY": "your-swarms-api-key",
"AUTONOMOUS_ALERTS_EMAIL": "intelligence@yourcompany.com",
"HEALTHCARE_EMERGENCY_EMAIL": "emergency@hospital.com",
"MAILGUN_API_KEY": "your-mailgun-key",
"MAILGUN_DOMAIN": "intelligence.yourcompany.com"
}
}
```
### Cloudflare Workers Cron Scheduling Patterns
```jsonc
{
"triggers": {
"crons": [
"0 */3 * * *", // Financial Swarms agents every 3 hours
"*/30 * * * *", // Healthcare Swarms monitoring every 30 minutes
"0 9,15,21 * * *", // Daily Swarms intelligence briefings
"*/5 * * * *" // Critical Swarms systems every 5 minutes
]
}
}
```
### Cloudflare Workers Deployment Commands
```bash
# Deploy Swarms AI agents to Cloudflare Workers
wrangler deploy
# Monitor Cloudflare Workers execution logs
wrangler tail
# Test Cloudflare Workers cron triggers manually
wrangler triggers cron "0 */3 * * *"
```
## Production Best Practices
### 1. **Cloudflare Workers + Swarms API Integration**
- Implement comprehensive error handling for both platforms
- Use Cloudflare Workers KV for caching Swarms API responses
- Leverage Cloudflare Workers analytics for monitoring
### 2. **Cost Optimization**
- Monitor Swarms API usage and costs
- Use Cloudflare Workers free tier (100K requests/day)
- Implement intelligent batching for Swarms API efficiency
- Use cost-effective Swarms models (gpt-4o-mini recommended)
### 3. **Security & Compliance**
- Secure Swarms API keys in Cloudflare Workers environment variables
- Use Cloudflare Workers secrets for sensitive data
- Audit AI decisions and maintain compliance logs
- HIPAA compliance for healthcare applications
### 4. **Monitoring & Observability**
- Track Cloudflare Workers performance metrics
- Monitor Swarms API response times and success rates
- Use Cloudflare Workers analytics dashboard
- Set up alerts for system failures and anomalies
This deployment architecture combines **Swarms API's advanced multi-agent intelligence** with **Cloudflare Workers' global edge infrastructure**, enabling truly intelligent, self-executing AI agents that operate continuously across 330+ cities worldwide, providing real-time intelligence and automated decision-making capabilities with ultra-low latency.