swarm-orchestration
@spencermarx · 收录于 1 周前
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
适合你,如果正在构建多智能体系统,需要协调并行任务和动态拓扑。
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怎么用
技能原文 SKILL.md
Swarm Orchestration
What This Skill Does
Orchestrates multi-agent swarms using agentic-flow's advanced coordination system. Supports mesh, hierarchical, and adaptive topologies with automatic task distribution, load balancing, and fault tolerance.
Prerequisites
- agentic-flow v3.0.0-alpha.1+
- Node.js 18+
- Understanding of distributed systems (helpful)
Quick Start
# Initialize swarm npx agentic-flow hooks swarm-init --topology mesh --max-agents 5 # Spawn agents npx agentic-flow hooks agent-spawn --type coder npx agentic-flow hooks agent-spawn --type tester npx agentic-flow hooks agent-spawn --type reviewer # Orchestrate task npx agentic-flow hooks task-orchestrate \ --task "Build REST API with tests" \ --mode parallel
Topology Patterns
1. Mesh (Peer-to-Peer)
// Equal peers, distributed decision-making
await swarm.init({
topology: 'mesh',
agents: ['coder', 'tester', 'reviewer'],
communication: 'broadcast'
});
2. Hierarchical (Queen-Worker)
// Centralized coordination, specialized workers
await swarm.init({
topology: 'hierarchical',
queen: 'architect',
workers: ['backend-dev', 'frontend-dev', 'db-designer']
});
3. Adaptive (Dynamic)
// Automatically switches topology based on task
await swarm.init({
topology: 'adaptive',
optimization: 'task-complexity'
});
Task Orchestration
Parallel Execution
// Execute tasks concurrently
const results = await swarm.execute({
tasks: [
{ agent: 'coder', task: 'Implement API endpoints' },
{ agent: 'frontend', task: 'Build UI components' },
{ agent: 'tester', task: 'Write test suite' }
],
mode: 'parallel',
timeout: 300000 // 5 minutes
});
Pipeline Execution
// Sequential pipeline with dependencies
await swarm.pipeline([
{ stage: 'design', agent: 'architect' },
{ stage: 'implement', agent: 'coder', after: 'design' },
{ stage: 'test', agent: 'tester', after: 'implement' },
{ stage: 'review', agent: 'reviewer', after: 'test' }
]);
Adaptive Execution
// Let swarm decide execution strategy
await swarm.autoOrchestrate({
goal: 'Build production-ready API',
constraints: {
maxTime: 3600,
maxAgents: 8,
quality: 'high'
}
});
Memory Coordination
// Share state across swarm
await swarm.memory.store('api-schema', {
endpoints: [...],
models: [...]
});
// Agents read shared memory
const schema = await swarm.memory.retrieve('api-schema');
Advanced Features
Load Balancing
// Automatic work distribution
await swarm.enableLoadBalancing({
strategy: 'dynamic',
metrics: ['cpu', 'memory', 'task-queue']
});
Fault Tolerance
// Handle agent failures
await swarm.setResiliency({
retry: { maxAttempts: 3, backoff: 'exponential' },
fallback: 'reassign-task'
});
Performance Monitoring
// Track swarm metrics
const metrics = await swarm.getMetrics();
// { throughput, latency, success_rate, agent_utilization }
Integration with Hooks
# Pre-task coordination npx agentic-flow hooks pre-task --description "Build API" # Post-task synchronization npx agentic-flow hooks post-task --task-id "task-123" # Session restore npx agentic-flow hooks session-restore --session-id "swarm-001"
Best Practices
- Start small: Begin with 2-3 agents, scale up
- Use memory: Share context through swarm memory
- Monitor metrics: Track performance and bottlenecks
- Enable hooks: Automatic coordination and sync
- Set timeouts: Prevent hung tasks
Troubleshooting
Issue: Agents not coordinating
Solution: Verify memory access and enable hooks
Issue: Poor performance
Solution: Check topology (use adaptive) and enable load balancing
Learn More
- Swarm Guide: docs/swarm/orchestration.md
- Topology Patterns: docs/swarm/topologies.md
- Hooks Integration: docs/hooks/coordination.md
按 Apache-2.0 许可原样转载,未经改动 · 在 GitHub 查看 →
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