d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
456 lines
19 KiB
JavaScript
456 lines
19 KiB
JavaScript
"use strict";
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/**
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* Multi-Agent System Coordination Examples
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*
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* Demonstrates agent communication patterns, task distribution,
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* consensus building, load balancing, and fault tolerance scenarios
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* for distributed agent systems.
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*
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* Integrates with:
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* - claude-flow: Swarm initialization and orchestration
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* - ruv-swarm: Enhanced coordination patterns
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* - flow-nexus: Cloud-based agent management
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*/
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.agentCommunicationPatterns = agentCommunicationPatterns;
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exports.taskDistributionScenarios = taskDistributionScenarios;
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exports.consensusBuildingData = consensusBuildingData;
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exports.loadBalancingPatterns = loadBalancingPatterns;
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exports.faultToleranceScenarios = faultToleranceScenarios;
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exports.hierarchicalCoordination = hierarchicalCoordination;
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exports.runAllCoordinationExamples = runAllCoordinationExamples;
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const index_js_1 = require("../../dist/index.js");
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// ============================================================================
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// Example 1: Agent Communication Patterns
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// ============================================================================
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/**
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* Generate communication patterns for multi-agent systems
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*/
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async function agentCommunicationPatterns() {
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console.log('\n🤖 Example 1: Agent Communication Patterns\n');
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const synth = (0, index_js_1.createSynth)({
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provider: 'gemini',
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apiKey: process.env.GEMINI_API_KEY || 'demo-key',
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cacheStrategy: 'memory',
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});
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// Generate message passing data
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const messages = await synth.generateEvents({
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count: 500,
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eventTypes: [
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'direct_message',
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'broadcast',
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'multicast',
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'request_reply',
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'publish_subscribe',
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],
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schema: {
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message_id: 'UUID',
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sender_agent_id: 'agent-{1-20}',
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receiver_agent_id: 'agent-{1-20} or "broadcast"',
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message_type: 'one of eventTypes',
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payload: {
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action: 'task_request | status_update | data_sync | error_report | ack',
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data: 'JSON object with task details',
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priority: 'high | medium | low',
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requires_response: 'boolean',
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},
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timestamp: 'ISO timestamp',
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latency_ms: 'number (1-500)',
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success: 'boolean (95% true)',
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},
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distribution: 'poisson',
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timeRange: {
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start: new Date(Date.now() - 3600000), // Last hour
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end: new Date(),
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},
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});
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console.log('Communication Patterns Generated:');
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console.log(`- Total messages: ${messages.data.length}`);
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console.log(`- Direct messages: ${messages.data.filter((m) => m.message_type === 'direct_message').length}`);
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console.log(`- Broadcasts: ${messages.data.filter((m) => m.message_type === 'broadcast').length}`);
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console.log(`- Average latency: ${(messages.data.reduce((sum, m) => sum + m.latency_ms, 0) / messages.data.length).toFixed(2)}ms`);
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// Integration with claude-flow hooks
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console.log('\nClaude-Flow Integration:');
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console.log('npx claude-flow@alpha hooks notify --message "Communication patterns generated"');
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console.log('npx claude-flow@alpha hooks post-edit --file "messages.json" --memory-key "swarm/coordinator/messages"');
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return messages;
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}
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// ============================================================================
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// Example 2: Task Distribution Scenarios
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// ============================================================================
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/**
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* Generate task distribution data for load balancing
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*/
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async function taskDistributionScenarios() {
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console.log('\n📋 Example 2: Task Distribution Scenarios\n');
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const synth = (0, index_js_1.createSynth)({
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provider: 'gemini',
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apiKey: process.env.GEMINI_API_KEY || 'demo-key',
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});
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// Generate task distribution events
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const tasks = await synth.generateStructured({
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count: 300,
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schema: {
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task_id: 'UUID',
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task_type: 'compute | data_processing | io_operation | ml_inference | api_call',
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assigned_agent: 'agent-{1-15}',
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estimated_duration_ms: 'number (100-10000)',
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actual_duration_ms: 'number (estimated_duration_ms * 0.8-1.2)',
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cpu_usage: 'number (0-100)',
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memory_mb: 'number (10-1000)',
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priority: 'number (1-10)',
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dependencies: ['array of 0-3 task_ids or empty'],
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status: 'pending | running | completed | failed',
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start_time: 'ISO timestamp',
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end_time: 'ISO timestamp or null',
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retry_count: 'number (0-3)',
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},
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constraints: [
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'Tasks should be distributed evenly across agents',
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'High priority tasks (8-10) should complete faster',
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'5% of tasks should have failed status',
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'Dependencies should form valid DAG (no cycles)',
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],
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});
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// Analyze distribution
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const agentLoad = new Map();
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tasks.data.forEach((task) => {
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agentLoad.set(task.assigned_agent, (agentLoad.get(task.assigned_agent) || 0) + 1);
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});
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console.log('Task Distribution Analysis:');
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console.log(`- Total tasks: ${tasks.data.length}`);
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console.log(`- Agents utilized: ${agentLoad.size}`);
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console.log(`- Tasks per agent (avg): ${(tasks.data.length / agentLoad.size).toFixed(1)}`);
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console.log(`- Failed tasks: ${tasks.data.filter((t) => t.status === 'failed').length}`);
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console.log(`- Completed tasks: ${tasks.data.filter((t) => t.status === 'completed').length}`);
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// Ruv-Swarm coordination pattern
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console.log('\nRuv-Swarm Coordination:');
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console.log('npx ruv-swarm mcp start');
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console.log('// Use MCP tools: swarm_init, task_orchestrate, agent_metrics');
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return tasks;
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}
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// ============================================================================
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// Example 3: Consensus Building Data
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// ============================================================================
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/**
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* Generate consensus protocol data for distributed decision making
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*/
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async function consensusBuildingData() {
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console.log('\n🤝 Example 3: Consensus Building Scenarios\n');
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const synth = (0, index_js_1.createSynth)({
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provider: 'gemini',
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apiKey: process.env.GEMINI_API_KEY || 'demo-key',
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});
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// Generate consensus rounds
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const consensusRounds = await synth.generateStructured({
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count: 50,
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schema: {
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round_id: 'UUID',
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proposal_id: 'UUID',
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protocol: 'raft | paxos | byzantine | quorum',
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participants: ['array of 5-15 agent ids'],
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proposer: 'agent id from participants',
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proposal: {
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type: 'leader_election | config_change | state_update | task_assignment',
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value: 'JSON object with proposal details',
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},
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votes: [
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{
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agent_id: 'agent id from participants',
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vote: 'accept | reject | abstain',
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timestamp: 'ISO timestamp',
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reasoning: 'short explanation',
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},
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],
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status: 'proposing | voting | committed | rejected | timeout',
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quorum_required: 'number (majority of participants)',
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quorum_reached: 'boolean',
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decision: 'accepted | rejected | timeout',
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round_duration_ms: 'number (100-5000)',
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timestamp: 'ISO timestamp',
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},
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constraints: [
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'Votes array should have one entry per participant',
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'70% of rounds should reach quorum',
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'80% of committed rounds should be accepted',
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'Byzantine protocol should have 3f+1 participants (f failures)',
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],
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});
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// Analyze consensus
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const successRate = consensusRounds.data.filter((r) => r.decision === 'accepted').length / consensusRounds.data.length;
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console.log('Consensus Analysis:');
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console.log(`- Total rounds: ${consensusRounds.data.length}`);
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console.log(`- Success rate: ${(successRate * 100).toFixed(1)}%`);
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console.log(`- Average duration: ${(consensusRounds.data.reduce((sum, r) => sum + r.round_duration_ms, 0) / consensusRounds.data.length).toFixed(0)}ms`);
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console.log(`- Quorum reached: ${consensusRounds.data.filter((r) => r.quorum_reached).length} rounds`);
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// Protocol distribution
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const protocolCount = new Map();
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consensusRounds.data.forEach((r) => {
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protocolCount.set(r.protocol, (protocolCount.get(r.protocol) || 0) + 1);
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});
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console.log('\nProtocol Usage:');
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protocolCount.forEach((count, protocol) => {
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console.log(`- ${protocol}: ${count} rounds`);
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});
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return consensusRounds;
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}
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// ============================================================================
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// Example 4: Load Balancing Patterns
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// ============================================================================
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/**
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* Generate load balancing metrics and patterns
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*/
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async function loadBalancingPatterns() {
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console.log('\n⚖️ Example 4: Load Balancing Patterns\n');
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const synth = (0, index_js_1.createSynth)({
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provider: 'gemini',
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apiKey: process.env.GEMINI_API_KEY || 'demo-key',
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});
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// Generate time-series load balancing metrics
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const metrics = await synth.generateTimeSeries({
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count: 200,
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interval: '30s',
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metrics: [
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'agent_count',
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'total_requests',
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'avg_response_time_ms',
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'cpu_utilization',
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'memory_utilization',
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'queue_depth',
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],
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trend: 'mixed',
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seasonality: true,
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});
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// Generate agent-specific metrics
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const agentMetrics = await synth.generateStructured({
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count: 100,
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schema: {
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timestamp: 'ISO timestamp',
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agent_id: 'agent-{1-10}',
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algorithm: 'round_robin | least_connections | weighted | ip_hash | consistent_hash',
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requests_handled: 'number (0-100)',
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active_connections: 'number (0-50)',
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cpu_percent: 'number (0-100)',
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memory_mb: 'number (100-2000)',
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response_time_p50: 'number (10-500)',
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response_time_p99: 'number (50-2000)',
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error_rate: 'number (0-0.05)',
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health_score: 'number (0-100)',
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},
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constraints: [
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'Load should be relatively balanced across agents',
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'High CPU should correlate with high request count',
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'Error rate should increase with overload',
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'Health score should decrease with high utilization',
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],
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});
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console.log('Load Balancing Analysis:');
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console.log(`- Time series points: ${metrics.data.length}`);
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console.log(`- Agent metrics: ${agentMetrics.data.length}`);
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// Calculate balance score
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const requestsByAgent = new Map();
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agentMetrics.data.forEach((m) => {
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requestsByAgent.set(m.agent_id, (requestsByAgent.get(m.agent_id) || 0) + m.requests_handled);
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});
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const avgRequests = Array.from(requestsByAgent.values()).reduce((a, b) => a + b, 0) / requestsByAgent.size;
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const variance = Array.from(requestsByAgent.values()).reduce((sum, val) => sum + Math.pow(val - avgRequests, 2), 0) / requestsByAgent.size;
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console.log(`- Average requests per agent: ${avgRequests.toFixed(1)}`);
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console.log(`- Load variance: ${variance.toFixed(2)} (lower is better)`);
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// Flow-Nexus integration for cloud load balancing
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console.log('\nFlow-Nexus Cloud Integration:');
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console.log('npx flow-nexus@latest login');
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console.log('// Use MCP tools: swarm_scale, agent_spawn, sandbox_create');
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return { metrics, agentMetrics };
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}
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// ============================================================================
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// Example 5: Fault Tolerance Scenarios
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// ============================================================================
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/**
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* Generate fault tolerance and failure recovery scenarios
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*/
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async function faultToleranceScenarios() {
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console.log('\n🛡️ Example 5: Fault Tolerance Scenarios\n');
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const synth = (0, index_js_1.createSynth)({
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provider: 'gemini',
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apiKey: process.env.GEMINI_API_KEY || 'demo-key',
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});
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// Generate failure events
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const failures = await synth.generateEvents({
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count: 100,
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eventTypes: [
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'agent_crash',
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'network_partition',
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'timeout',
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'out_of_memory',
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'resource_exhaustion',
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'byzantine_fault',
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],
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schema: {
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incident_id: 'UUID',
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event_type: 'one of eventTypes',
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affected_agents: ['array of 1-5 agent ids'],
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severity: 'critical | high | medium | low',
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detection_time: 'ISO timestamp',
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recovery_initiated: 'ISO timestamp',
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recovery_completed: 'ISO timestamp or null',
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recovery_strategy: 'restart | failover | rollback | isolation | replication',
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data_lost: 'boolean',
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service_degraded: 'boolean',
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mttr_seconds: 'number (10-600)',
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root_cause: 'short description of root cause',
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},
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distribution: 'uniform',
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timeRange: {
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start: new Date(Date.now() - 86400000), // Last 24 hours
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end: new Date(),
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},
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});
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// Generate recovery actions
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const recoveryActions = await synth.generateStructured({
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count: failures.data.length,
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schema: {
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incident_id: 'UUID (from failures)',
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action_id: 'UUID',
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action_type: 'health_check | restart_agent | promote_backup | restore_state | load_balance',
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executor: 'coordinator | agent-{id} | auto_healer',
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success: 'boolean (90% true)',
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duration_ms: 'number (100-10000)',
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retries: 'number (0-3)',
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compensating_actions: ['array of 0-2 action types or empty'],
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timestamp: 'ISO timestamp',
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},
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});
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// Analyze fault tolerance
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const mttrAvg = failures.data.reduce((sum, f) => sum + f.mttr_seconds, 0) / failures.data.length;
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const recoveryRate = recoveryActions.data.filter((a) => a.success).length / recoveryActions.data.length;
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console.log('Fault Tolerance Analysis:');
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console.log(`- Total incidents: ${failures.data.length}`);
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console.log(`- Average MTTR: ${mttrAvg.toFixed(1)} seconds`);
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console.log(`- Recovery success rate: ${(recoveryRate * 100).toFixed(1)}%`);
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console.log(`- Data loss incidents: ${failures.data.filter((f) => f.data_lost).length}`);
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console.log(`- Service degraded: ${failures.data.filter((f) => f.service_degraded).length}`);
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// Failure type distribution
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const failureTypes = new Map();
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failures.data.forEach((f) => {
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failureTypes.set(f.event_type, (failureTypes.get(f.event_type) || 0) + 1);
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});
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console.log('\nFailure Type Distribution:');
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failureTypes.forEach((count, type) => {
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console.log(`- ${type}: ${count} (${((count / failures.data.length) * 100).toFixed(1)}%)`);
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});
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// Self-healing integration
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console.log('\nSelf-Healing Integration:');
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console.log('// Enable auto-recovery hooks');
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console.log('npx claude-flow@alpha hooks enable --type "error-recovery"');
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return { failures, recoveryActions };
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}
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// ============================================================================
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// Example 6: Hierarchical Coordination
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// ============================================================================
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/**
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* Generate hierarchical swarm coordination data
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*/
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async function hierarchicalCoordination() {
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console.log('\n🏗️ Example 6: Hierarchical Swarm Coordination\n');
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const synth = (0, index_js_1.createSynth)({
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provider: 'gemini',
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apiKey: process.env.GEMINI_API_KEY || 'demo-key',
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});
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// Generate hierarchical structure
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const swarmTopology = await synth.generateStructured({
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count: 1,
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schema: {
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topology_id: 'UUID',
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type: 'hierarchical',
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coordinator: {
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agent_id: 'coordinator-main',
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role: 'master_coordinator',
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responsibilities: ['task_distribution', 'health_monitoring', 'consensus_leader'],
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},
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sub_coordinators: [
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{
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agent_id: 'sub-coordinator-{1-5}',
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role: 'regional_coordinator',
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manages_agents: ['array of 5-10 worker agent ids'],
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region: 'zone-{A-E}',
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},
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],
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workers: [
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{
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agent_id: 'worker-{1-50}',
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coordinator_id: 'sub-coordinator id',
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capabilities: ['array of 2-4 capabilities'],
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status: 'active | idle | busy | offline',
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},
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],
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communication_patterns: {
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coordinator_to_sub: 'direct',
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sub_to_workers: 'multicast',
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worker_to_coordinator: 'via_sub_coordinator',
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peer_to_peer: 'disabled',
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},
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},
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});
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// Generate coordination events
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const coordinationEvents = await synth.generateEvents({
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count: 200,
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eventTypes: [
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'task_delegation',
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'status_report',
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'resource_request',
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'coordination_sync',
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'topology_update',
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],
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schema: {
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event_id: 'UUID',
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event_type: 'one of eventTypes',
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from_agent: 'agent id from topology',
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to_agent: 'agent id from topology',
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hierarchy_level: 'coordinator | sub_coordinator | worker',
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payload: 'JSON object',
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timestamp: 'ISO timestamp',
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},
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});
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console.log('Hierarchical Coordination:');
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console.log(`- Total agents: ${swarmTopology.data[0].workers.length + swarmTopology.data[0].sub_coordinators.length + 1}`);
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console.log(`- Sub-coordinators: ${swarmTopology.data[0].sub_coordinators.length}`);
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console.log(`- Workers: ${swarmTopology.data[0].workers.length}`);
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console.log(`- Coordination events: ${coordinationEvents.data.length}`);
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// Claude-Flow hierarchical setup
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console.log('\nClaude-Flow Hierarchical Setup:');
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console.log('npx claude-flow@alpha mcp start');
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console.log('// MCP: swarm_init with topology: "hierarchical"');
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console.log('// MCP: agent_spawn with role assignments');
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return { topology: swarmTopology, events: coordinationEvents };
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}
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// ============================================================================
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// Run All Examples
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// ============================================================================
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async function runAllCoordinationExamples() {
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console.log('🚀 Running All Agent Coordination Examples\n');
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console.log('='.repeat(70));
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try {
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await agentCommunicationPatterns();
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console.log('='.repeat(70));
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await taskDistributionScenarios();
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console.log('='.repeat(70));
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await consensusBuildingData();
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console.log('='.repeat(70));
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await loadBalancingPatterns();
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console.log('='.repeat(70));
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await faultToleranceScenarios();
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console.log('='.repeat(70));
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await hierarchicalCoordination();
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console.log('='.repeat(70));
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console.log('\n✅ All agent coordination examples completed!\n');
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}
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catch (error) {
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console.error('❌ Error running examples:', error.message);
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throw error;
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}
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}
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// Run if executed directly
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if (import.meta.url === `file://${process.argv[1]}`) {
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runAllCoordinationExamples().catch(console.error);
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}
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//# sourceMappingURL=agent-coordination.js.map
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