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swarm coordination for Cogitator","maintainers":[{"name":"el1fe","email":"piuro.pavel@gmail.com"}],"readme":"# @cogitator-ai/swarms\n\nMulti-agent swarm coordination for Cogitator. Orchestrate teams of AI agents with various collaboration strategies, automatic model selection, built-in communication primitives, and workflow integration.\n\n## Installation\n\n```bash\npnpm add @cogitator-ai/swarms\n```\n\n## Quick Start\n\n```typescript\nimport { Cogitator, Agent } from '@cogitator-ai/core';\nimport { SwarmBuilder } from '@cogitator-ai/swarms';\n\nconst cogitator = new Cogitator({ defaultModel: 'gpt-4o' });\n\nconst swarm = new SwarmBuilder('dev-team')\n .strategy('hierarchical')\n .supervisor(new Agent({ name: 'lead', instructions: 'Coordinate the team' }))\n .workers([\n new Agent({ name: 'coder', instructions: 'Write code' }),\n new Agent({ name: 'tester', instructions: 'Test code' }),\n ])\n .build(cogitator);\n\nconst result = await swarm.run({\n input: 'Build a REST API for user management',\n});\n\nconsole.log(result.output);\n```\n\n## Features\n\n- **7 Coordination Strategies** - Hierarchical, round-robin, consensus, pipeline, debate, auction, negotiation\n- **Automatic Model Selection** - SwarmAssessor matches optimal models to agent roles\n- **Agent Communication** - Message bus and shared blackboard\n- **Built-in Tools** - Messaging, delegation, voting, and blackboard tools for agents\n- **Workflow Integration** - Use swarms as nodes in DAG workflows\n- **Resource Tracking** - Monitor tokens, costs, and time budgets\n- **Circuit Breaker** - Prevent cascading failures in swarm execution\n\n---\n\n## Strategies\n\n### Hierarchical\n\nSupervisor delegates tasks to workers:\n\n```typescript\nimport { SwarmBuilder, Swarm } from '@cogitator-ai/swarms';\n\nconst swarm = new SwarmBuilder('dev-team')\n .strategy('hierarchical')\n .supervisor(\n new Agent({\n name: 'tech-lead',\n instructions: 'Break down tasks and delegate to workers',\n })\n )\n .workers([\n new Agent({ name: 'frontend-dev', instructions: 'Build UI components' }),\n new Agent({ name: 'backend-dev', instructions: 'Build API endpoints' }),\n new Agent({ name: 'tester', instructions: 'Write and run tests' }),\n ])\n .hierarchical({\n maxDelegations: 5,\n requireApproval: false,\n parallelExecution: true,\n })\n .build(cogitator);\n\nconst result = await swarm.run({\n input: 'Build a user authentication system',\n});\n```\n\n### Round-Robin\n\nLoad-balanced rotation across agents:\n\n```typescript\nconst swarm = new SwarmBuilder('support-team')\n .strategy('round-robin')\n .agents([\n new Agent({ name: 'support-1', instructions: 'Handle customer queries' }),\n new Agent({ name: 'support-2', instructions: 'Handle customer queries' }),\n new Agent({ name: 'support-3', instructions: 'Handle customer queries' }),\n ])\n .roundRobin({\n maxRounds: 10,\n skipUnavailable: true,\n })\n .build(cogitator);\n```\n\n### Consensus\n\nVoting-based decisions with multiple agents:\n\n```typescript\nconst swarm = new SwarmBuilder('review-board')\n .strategy('consensus')\n .agents([\n new Agent({ name: 'reviewer-1', instructions: 'Review from security perspective' }),\n new Agent({ name: 'reviewer-2', instructions: 'Review from performance perspective' }),\n new Agent({ name: 'reviewer-3', instructions: 'Review from UX perspective' }),\n ])\n .consensus({\n votingMethod: 'majority',\n minVotes: 2,\n timeout: 30000,\n tieBreaker: 'random',\n })\n .build(cogitator);\n```\n\n### Pipeline\n\nSequential processing stages:\n\n```typescript\nconst swarm = new SwarmBuilder('content-pipeline')\n .strategy('pipeline')\n .pipeline({\n stages: [\n { agent: new Agent({ name: 'researcher', instructions: 'Research the topic' }) },\n { agent: new Agent({ name: 'writer', instructions: 'Write the content' }) },\n { agent: new Agent({ name: 'editor', instructions: 'Edit and refine' }) },\n { agent: new Agent({ name: 'reviewer', instructions: 'Final review' }) },\n ],\n stopOnError: true,\n passContext: true,\n })\n .build(cogitator);\n```\n\n### Debate\n\nMultiple perspectives with synthesis:\n\n```typescript\nconst swarm = new SwarmBuilder('analysis-team')\n .strategy('debate')\n .agents([\n new Agent({ name: 'optimist', instructions: 'Present positive aspects' }),\n new Agent({ name: 'skeptic', instructions: 'Challenge assumptions' }),\n new Agent({ name: 'pragmatist', instructions: 'Focus on practicality' }),\n ])\n .moderator(\n new Agent({\n name: 'moderator',\n instructions: 'Guide discussion and synthesize conclusions',\n })\n )\n .debate({\n rounds: 3,\n requireSynthesis: true,\n maxTurnsPerRound: 2,\n })\n .build(cogitator);\n```\n\n### Auction\n\nBidding-based task assignment:\n\n```typescript\nconst swarm = new SwarmBuilder('contractor-pool')\n .strategy('auction')\n .agents([\n new Agent({ name: 'contractor-1', instructions: 'Bid based on expertise' }),\n new Agent({ name: 'contractor-2', instructions: 'Bid based on expertise' }),\n new Agent({ name: 'contractor-3', instructions: 'Bid based on expertise' }),\n ])\n .auction({\n biddingRounds: 2,\n selectionCriteria: 'lowest',\n allowNegotiation: true,\n })\n .build(cogitator);\n```\n\n### Negotiation\n\nMulti-party negotiation with offers, counter-offers, and coalitions:\n\n```typescript\nconst swarm = new SwarmBuilder('deal-makers')\n .strategy('negotiation')\n .agents([\n new Agent({ name: 'buyer', instructions: 'Negotiate best purchase terms' }),\n new Agent({ name: 'seller', instructions: 'Maximize sale value' }),\n new Agent({ name: 'mediator', instructions: 'Facilitate fair agreement' }),\n ])\n .negotiation({\n maxRounds: 10,\n convergenceThreshold: 0.8,\n allowCoalitions: true,\n timeoutPerRound: 30000,\n })\n .build(cogitator);\n```\n\n---\n\n## SwarmAssessor (Automatic Model Selection)\n\nSwarmAssessor automatically analyzes tasks and matches optimal models to agent roles based on capabilities, cost, and availability.\n\n### Basic Usage\n\n```typescript\nimport { SwarmBuilder, createAssessor } from '@cogitator-ai/swarms';\n\nconst swarm = new SwarmBuilder('smart-team')\n .strategy('hierarchical')\n .supervisor(new Agent({ name: 'lead', instructions: '...' }))\n .workers([\n new Agent({ name: 'coder', instructions: '...' }),\n new Agent({ name: 'analyst', instructions: '...' }),\n ])\n .withAssessor({\n mode: 'rules',\n preferLocal: true,\n minCapabilityMatch: 0.3,\n maxCostPerRun: 0.5,\n })\n .build(cogitator);\n\n// Models are automatically selected based on task requirements\nconst result = await swarm.run({ input: 'Complex coding task' });\n\n// View what models were assigned\nconst assessment = swarm.getLastAssessment();\nconsole.log(assessment?.assignments);\n```\n\n### Dry Run (Preview Assignments)\n\n```typescript\nconst assessment = await swarm.dryRun({\n input: 'Build a recommendation engine',\n});\n\nconsole.log('Task complexity:', assessment.taskAnalysis.complexity);\nconsole.log('Estimated cost:', assessment.totalEstimatedCost);\n\nfor (const assignment of assessment.assignments) {\n console.log(`${assignment.agentName}: ${assignment.assignedModel} (score: ${assignment.score})`);\n}\n```\n\n### Assessor Configuration\n\n```typescript\nimport { createAssessor, SwarmAssessor } from '@cogitator-ai/swarms';\n\nconst assessor = createAssessor({\n mode: 'rules',\n assessorModel: 'gpt-4o-mini',\n preferLocal: true,\n minCapabilityMatch: 0.3,\n ollamaUrl: 'http://localhost:11434',\n enabledProviders: ['ollama', 'openai', 'anthropic', 'google'],\n cacheAssessments: true,\n cacheTTL: 5 * 60 * 1000,\n maxCostPerRun: 1.0,\n});\n```\n\n### Model Suggestions\n\n```typescript\nconst candidates = await assessor.suggestModels({\n capabilities: ['code', 'reasoning'],\n complexity: 'complex',\n contextLength: 8000,\n});\n\nfor (const model of candidates) {\n console.log(`${model.modelId} (${model.provider}): score ${model.score}`);\n}\n```\n\n### Assessor Components\n\n| Component | Description |\n| ---------------- | --------------------------------------------- |\n| `TaskAnalyzer` | Analyzes task complexity and requirements |\n| `ModelDiscovery` | Discovers available models from all providers |\n| `ModelScorer` | Scores models against role requirements |\n| `RoleMatcher` | Matches agents to optimal models |\n\n---\n\n## Agent Communication\n\n### Message Bus\n\nAgents can send direct messages and broadcasts:\n\n```typescript\nimport { InMemoryMessageBus, createMessagingTools } from '@cogitator-ai/swarms';\n\nconst messageBus = new InMemoryMessageBus();\n\n// Create tools for an agent\nconst tools = createMessagingTools(messageBus, 'agent-1');\n\n// Tools available:\n// - send_message: Send to specific agent\n// - read_messages: Read incoming messages\n// - broadcast_message: Send to all agents\n// - reply_to_message: Reply to a specific message\n```\n\n### Blackboard (Shared State)\n\nAgents can read/write shared state:\n\n```typescript\nimport { InMemoryBlackboard, createBlackboardTools } from '@cogitator-ai/swarms';\n\nconst blackboard = new InMemoryBlackboard();\n\nconst tools = createBlackboardTools(blackboard, 'agent-1');\n\n// Tools available:\n// - read_blackboard: Read a section\n// - write_blackboard: Write to a section\n// - append_blackboard: Append to array section\n// - list_blackboard_sections: List all sections\n// - get_blackboard_history: Get change history\n```\n\n### Swarm Configuration with Communication\n\n```typescript\nconst swarm = new SwarmBuilder('research-team')\n .strategy('hierarchical')\n .supervisor(supervisorAgent)\n .workers([researcher1, researcher2])\n .messaging({\n enabled: true,\n historySize: 100,\n channels: ['findings', 'questions', 'progress'],\n })\n .blackboardConfig({\n enabled: true,\n sections: {\n findings: [],\n sources: [],\n conclusions: '',\n },\n })\n .build(cogitator);\n```\n\n---\n\n## Built-in Swarm Tools\n\n### All Tools at Once\n\n```typescript\nimport { createSwarmTools, SwarmToolContext } from '@cogitator-ai/swarms';\n\nconst context: SwarmToolContext = {\n coordinator,\n blackboard,\n messageBus,\n events,\n agentName: 'my-agent',\n agentWeight: 1,\n};\n\nconst tools = createSwarmTools(context);\n// Returns 16 tools: messaging (4) + blackboard (5) + delegation (4) + voting (4)\n```\n\n### Strategy-Specific Tools\n\n```typescript\nimport { createStrategyTools } from '@cogitator-ai/swarms';\n\n// Get tools appropriate for the strategy\nconst tools = createStrategyTools('hierarchical', context);\n// Returns: messaging + blackboard + delegation tools\n\nconst debateTools = createStrategyTools('debate', context);\n// Returns: messaging + blackboard + voting tools\n```\n\n### Delegation Tools (Hierarchical)\n\n```typescript\nimport { createDelegationTools } from '@cogitator-ai/swarms';\n\nconst tools = createDelegationTools(coordinator, blackboard, 'supervisor');\n\n// delegate_task - Assign work to a worker\n// check_progress - Monitor worker status\n// request_revision - Ask for corrections\n// list_workers - See available workers\n```\n\n### Voting Tools (Consensus/Debate)\n\n```typescript\nimport { createVotingTools } from '@cogitator-ai/swarms';\n\nconst tools = createVotingTools(blackboard, events, 'voter-1', 1.0);\n\n// cast_vote - Submit a vote\n// get_votes - See current votes\n// change_vote - Modify your vote\n// get_consensus_status - Check if consensus reached\n```\n\n---\n\n## Workflow Integration\n\nUse swarms as nodes in DAG workflows.\n\n### Basic Swarm Node\n\n```typescript\nimport { WorkflowBuilder } from '@cogitator-ai/workflows';\nimport { swarmNode, SwarmNodeContext } from '@cogitator-ai/swarms';\n\nconst analysisSwarm = new SwarmBuilder('analysis')\n .strategy('debate')\n .agents([...])\n .build(cogitator);\n\nconst workflow = new WorkflowBuilder('analysis-flow')\n .addNode('analyze', swarmNode(analysisSwarm, {\n inputMapper: (state) => state.document,\n stateMapper: (result) => ({ analysis: result.output }),\n }))\n .build();\n\nconst result = await workflow.run({\n cogitator,\n input: { document: 'Analyze this document...' },\n});\n```\n\n### Conditional Swarm Node\n\n```typescript\nimport { conditionalSwarmNode } from '@cogitator-ai/swarms';\n\nconst workflow = new WorkflowBuilder('conditional-flow')\n .addNode(\n 'expert-review',\n conditionalSwarmNode(expertSwarm, (state) => state.needsExpertReview, {\n stateMapper: (result) => ({ expertOpinion: result.output }),\n })\n )\n .build();\n```\n\n### Parallel Swarms Node\n\n```typescript\nimport { parallelSwarmsNode } from '@cogitator-ai/swarms';\n\nconst workflow = new WorkflowBuilder('parallel-analysis')\n .addNode(\n 'multi-analyze',\n parallelSwarmsNode(\n [\n { swarm: technicalSwarm, key: 'technical' },\n { swarm: businessSwarm, key: 'business' },\n { swarm: legalSwarm, key: 'legal' },\n ],\n (results) => ({\n technicalAnalysis: results.technical.output,\n businessAnalysis: results.business.output,\n legalAnalysis: results.legal.output,\n })\n )\n )\n .build();\n```\n\n---\n\n## Resource Tracking\n\nMonitor and limit resource usage during swarm execution.\n\n### Configuration\n\n```typescript\nconst swarm = new SwarmBuilder('budget-conscious')\n .strategy('hierarchical')\n .supervisor(lead)\n .workers(workers)\n .resources({\n tokenBudget: 100000,\n costLimit: 5.0,\n timeout: 300000,\n })\n .build(cogitator);\n```\n\n### ResourceTracker API\n\n```typescript\nimport { ResourceTracker } from '@cogitator-ai/swarms';\n\nconst tracker = new ResourceTracker({\n tokenBudget: 50000,\n costLimit: 2.0,\n timeout: 60000,\n});\n\n// Track agent runs\ntracker.trackAgentRun('agent-1', runResult);\n\n// Check budget\nconsole.log('Within budget:', tracker.isWithinBudget());\nconsole.log('Remaining:', tracker.getRemainingBudget());\n\n// Get usage stats\nconst usage = tracker.getUsage();\nconsole.log('Total tokens:', usage.totalTokens);\nconsole.log('Total cost:', usage.totalCost);\nconsole.log('Elapsed time:', usage.elapsedTime);\n\n// Per-agent usage\nconst agentUsage = tracker.getAgentUsage('agent-1');\nconsole.log('Agent tokens:', agentUsage?.tokens);\n```\n\n### Swarm Resource Usage\n\n```typescript\nconst result = await swarm.run({ input: 'Task...' });\n\nconst usage = swarm.getResourceUsage();\nconsole.log('Total tokens:', usage.totalTokens);\nconsole.log('Total cost:', usage.totalCost);\n\nfor (const [agent, stats] of usage.agentUsage) {\n console.log(`${agent}: ${stats.tokens} tokens, ${stats.runs} runs`);\n}\n```\n\n---\n\n## Circuit Breaker\n\nPrevent cascading failures in swarm execution.\n\n```typescript\nimport { CircuitBreaker } from '@cogitator-ai/swarms';\n\nconst breaker = new CircuitBreaker({\n threshold: 5,\n resetTimeout: 30000,\n successThreshold: 2,\n});\n\n// Check before execution\nif (breaker.canExecute()) {\n try {\n const result = await runTask();\n breaker.recordSuccess();\n } catch (error) {\n breaker.recordFailure();\n throw error;\n }\n} else {\n console.log('Circuit is open, skipping execution');\n}\n\n// Monitor state changes\nbreaker.onStateChange((state) => {\n console.log('Circuit state:', state); // 'closed' | 'open' | 'half-open'\n});\n\n// Reset manually\nbreaker.reset();\n```\n\n### Swarm Error Handling Configuration\n\n```typescript\nconst swarm = new SwarmBuilder('resilient-team')\n .strategy('hierarchical')\n .supervisor(lead)\n .workers(workers)\n .errorHandling({\n retryCount: 3,\n retryDelay: 1000,\n circuitBreaker: {\n threshold: 5,\n resetTimeout: 30000,\n },\n fallbackAgent: fallbackAgent,\n })\n .build(cogitator);\n```\n\n---\n\n## Swarm Events\n\nSubscribe to swarm lifecycle events.\n\n```typescript\nconst swarm = new SwarmBuilder('monitored-team')\n .strategy('hierarchical')\n .supervisor(lead)\n .workers(workers)\n .build(cogitator);\n\n// Subscribe to specific events\nswarm.on('swarm:start', (event) => {\n console.log('Swarm started:', event.swarmId);\n});\n\nswarm.on('agent:start', (event) => {\n console.log(`Agent ${event.agentName} started`);\n});\n\nswarm.on('agent:complete', (event) => {\n console.log(`Agent ${event.agentName} completed`);\n});\n\nswarm.on('swarm:complete', (event) => {\n console.log('Swarm completed, agents used:', event.agentCount);\n});\n\nswarm.on('swarm:error', (event) => {\n console.error('Swarm error:', event.error);\n});\n\n// Subscribe to all events\nswarm.on('*', (event) => {\n console.log('Event:', event);\n});\n\n// One-time subscription\nswarm.once('swarm:complete', (event) => {\n console.log('Finished!');\n});\n```\n\n### Event Types\n\n| Event | Description |\n| ------------------- | ---------------------------- |\n| `swarm:start` | Swarm execution started |\n| `swarm:complete` | Swarm execution completed |\n| `swarm:error` | Error during swarm execution |\n| `swarm:paused` | Swarm paused |\n| `swarm:resumed` | Swarm resumed |\n| `swarm:aborted` | Swarm aborted |\n| `swarm:reset` | Swarm reset |\n| `agent:start` | Agent started execution |\n| `agent:complete` | Agent completed execution |\n| `agent:error` | Agent encountered error |\n| `assessor:complete` | Model assessment completed |\n| `message:sent` | Message sent between agents |\n| `blackboard:write` | Blackboard updated |\n| `vote:cast` | Vote cast in consensus |\n\n---\n\n## Distributed Execution\n\nRun swarm agents across multiple workers using Redis-backed communication and BullMQ job queues. Each agent executes as a separate job, enabling horizontal scaling and parallel processing.\n\n### Basic Distributed Swarm\n\n```typescript\nimport { Cogitator, Agent } from '@cogitator-ai/core';\nimport { SwarmBuilder } from '@cogitator-ai/swarms';\n\nconst cogitator = new Cogitator({ defaultModel: 'gpt-4o' });\n\nconst swarm = new SwarmBuilder('distributed-team')\n .strategy('hierarchical')\n .supervisor(new Agent({ name: 'lead', instructions: 'Coordinate the team' }))\n .workers([\n new Agent({ name: 'analyst-1', instructions: 'Analyze data' }),\n new Agent({ name: 'analyst-2', instructions: 'Analyze data' }),\n new Agent({ name: 'analyst-3', instructions: 'Analyze data' }),\n ])\n .distributed({\n enabled: true,\n queue: 'swarm-agent-jobs',\n timeout: 300000,\n redis: {\n host: 'localhost',\n port: 6379,\n },\n })\n .build(cogitator);\n\nconst result = await swarm.run({\n input: 'Analyze Q4 sales data across all regions',\n});\n\n// Cleanup Redis connections when done\nawait swarm.close();\n```\n\n### Distributed Configuration Options\n\n```typescript\ninterface DistributedSwarmConfig {\n enabled: boolean;\n queue?: string; // Job queue name (default: 'swarm-agent-jobs')\n workerConcurrency?: number; // Workers per process (default: 4)\n timeout?: number; // Job timeout in ms (default: 300000)\n redis?: {\n host?: string; // Redis host (default: 'localhost')\n port?: number; // Redis port (default: 6379)\n password?: string; // Redis password\n keyPrefix?: string; // Key prefix (default: 'swarm')\n db?: number; // Redis database (default: 0)\n };\n retry?: {\n maxRetries?: number; // Max retry attempts\n backoff?: 'constant' | 'linear' | 'exponential';\n initialDelay?: number; // Initial delay in ms\n maxDelay?: number; // Max delay in ms\n };\n cleanupAfter?: number; // Cleanup keys after ms\n}\n```\n\n### Redis-Backed Communication\n\nDistributed swarms use Redis for shared state synchronization:\n\n```typescript\nimport { RedisMessageBus, RedisBlackboard, RedisSwarmEventEmitter } from '@cogitator-ai/swarms';\nimport Redis from 'ioredis';\n\nconst redis = new Redis({ host: 'localhost', port: 6379 });\n\n// Message bus for agent-to-agent communication\nconst messageBus = new RedisMessageBus(\n { enabled: true, protocol: 'direct' },\n { redis, swarmId: 'my-swarm', keyPrefix: 'swarm' }\n);\nawait messageBus.initialize();\n\n// Shared blackboard for state\nconst blackboard = new RedisBlackboard(\n { enabled: true, sections: { results: [] }, trackHistory: true },\n { redis, swarmId: 'my-swarm', keyPrefix: 'swarm' }\n);\nawait blackboard.initialize();\n\n// Event emitter for cross-worker events\nconst events = new RedisSwarmEventEmitter({\n redis,\n swarmId: 'my-swarm',\n keyPrefix: 'swarm',\n});\nawait events.initialize();\n```\n\n### Setting Up Workers\n\nWorkers process distributed swarm jobs. Use with `@cogitator-ai/worker`:\n\n```typescript\nimport { WorkerPool } from '@cogitator-ai/worker';\n\nconst pool = new WorkerPool({\n concurrency: 4,\n redis: {\n host: 'localhost',\n port: 6379,\n },\n queues: ['swarm-agent-jobs'],\n});\n\nawait pool.start();\n\n// Workers automatically process swarm-agent jobs\n// Each job runs a single agent and publishes results back to Redis\n```\n\n### Architecture\n\n```\n┌─────────────────────────────────────────────────────────────┐\n│ Swarm.run() │\n│ distributed: true → DistributedSwarmCoordinator │\n│ distributed: false → SwarmCoordinator (in-memory) │\n└─────────────────────────────────────────────────────────────┘\n │\n ┌───────────────┴───────────────┐\n ▼ ▼\n┌─────────────────────────┐ ┌─────────────────────────────┐\n│ DistributedCoordinator │ │ Redis (Shared State) │\n│ - dispatches agent jobs│────▶│ - swarm:{id}:blackboard │\n│ - subscribes to results│ │ - swarm:{id}:messages │\n│ - coordinates strategy │ │ - swarm:{id}:results │\n└─────────────────────────┘ └─────────────────────────────┘\n │ ▲\n │ job queue │\n ▼ │\n┌─────────────────────────┐ │\n│ BullMQ Queue │ │\n│ swarm-agent-jobs │ │\n└─────────────────────────┘ │\n │ │\n ┌─────────┼─────────┐ │\n ▼ ▼ ▼ │\n┌───────┐ ┌───────┐ ┌───────┐ │\n│Worker1│ │Worker2│ │Worker3│ ───────────────┘\n│ Agent │ │ Agent │ │ Agent │ publish results\n└───────┘ └───────┘ └───────┘\n```\n\n### Local vs Distributed\n\nThe same swarm works in both modes with identical API:\n\n```typescript\n// Local execution (in-process)\nconst localSwarm = new SwarmBuilder('local-team')\n .strategy('consensus')\n .agents([agent1, agent2, agent3])\n .consensus({ threshold: 0.6, maxRounds: 3, resolution: 'majority', onNoConsensus: 'fail' })\n .build(cogitator);\n\n// Distributed execution (across workers)\nconst distributedSwarm = new SwarmBuilder('distributed-team')\n .strategy('consensus')\n .agents([agent1, agent2, agent3])\n .consensus({ threshold: 0.6, maxRounds: 3, resolution: 'majority', onNoConsensus: 'fail' })\n .distributed({ enabled: true, redis: { host: 'redis.example.com' } })\n .build(cogitator);\n\n// Same API for both\nconst localResult = await localSwarm.run({ input: 'Task...' });\nconst distributedResult = await distributedSwarm.run({ input: 'Task...' });\n```\n\n---\n\n## Swarm Control\n\n### Pause and Resume\n\n```typescript\nconst swarm = new SwarmBuilder('controllable')\n .strategy('pipeline')\n .pipeline({ stages: [...] })\n .build(cogitator);\n\n// Start execution\nconst resultPromise = swarm.run({ input: 'Process this...' });\n\n// Pause mid-execution\nsetTimeout(() => {\n swarm.pause();\n console.log('Paused:', swarm.isPaused());\n\n // Resume later\n setTimeout(() => {\n swarm.resume();\n }, 5000);\n}, 2000);\n\nconst result = await resultPromise;\n```\n\n### Abort\n\n```typescript\nconst timeoutId = setTimeout(() => {\n if (!swarm.isAborted()) {\n swarm.abort();\n console.log('Swarm aborted due to timeout');\n }\n}, 60000);\n\ntry {\n const result = await swarm.run({ input: 'Task...' });\n clearTimeout(timeoutId);\n} catch (error) {\n if (swarm.isAborted()) {\n console.log('Task was aborted');\n }\n}\n```\n\n### Reset\n\n```typescript\n// Reset swarm state for a new run\nswarm.reset();\n\n// Run again with fresh state\nconst result = await swarm.run({ input: 'New task...' });\n```\n\n---\n\n## Type Reference\n\n### Core Types\n\n```typescript\nimport type {\n SwarmConfig,\n SwarmRunOptions,\n SwarmAgent,\n SwarmAgentMetadata,\n SwarmAgentState,\n StrategyResult,\n SwarmStrategy,\n} from '@cogitator-ai/swarms';\n```\n\n### Strategy Types\n\n```typescript\nimport type {\n HierarchicalConfig,\n RoundRobinConfig,\n ConsensusConfig,\n AuctionConfig,\n PipelineConfig,\n PipelineStage,\n DebateConfig,\n} from '@cogitator-ai/swarms';\n```\n\n### Communication Types\n\n```typescript\nimport type {\n MessageBus,\n MessageBusConfig,\n Blackboard,\n BlackboardConfig,\n BlackboardEntry,\n SwarmMessage,\n SwarmMessageType,\n} from '@cogitator-ai/swarms';\n```\n\n### Assessor Types\n\n```typescript\nimport type {\n AssessorConfig,\n AssessmentResult,\n TaskRequirements,\n RoleRequirements,\n ModelAssignment,\n ModelCandidate,\n DiscoveredModel,\n ScoredModel,\n} from '@cogitator-ai/swarms';\n```\n\n### Event Types\n\n```typescript\nimport type {\n SwarmEventEmitter,\n SwarmEventType,\n SwarmEvent,\n SwarmEventHandler,\n} from '@cogitator-ai/swarms';\n```\n\n### Distributed Types\n\n```typescript\nimport type { DistributedSwarmConfig } from '@cogitator-ai/types';\n\nimport {\n RedisMessageBus,\n RedisBlackboard,\n RedisSwarmEventEmitter,\n DistributedSwarmCoordinator,\n} from '@cogitator-ai/swarms';\n```\n\n---\n\n## Examples\n\n### Research Team with Shared Knowledge\n\n```typescript\nconst swarm = new SwarmBuilder('research-team')\n .strategy('hierarchical')\n .supervisor(\n new Agent({\n name: 'lead-researcher',\n instructions: 'Coordinate research and synthesize findings',\n })\n )\n .workers([\n new Agent({\n name: 'web-researcher',\n instructions: 'Search and analyze web sources',\n tools: [webSearchTool],\n }),\n new Agent({\n name: 'data-analyst',\n instructions: 'Analyze data and statistics',\n tools: [calculatorTool],\n }),\n new Agent({\n name: 'writer',\n instructions: 'Write clear summaries',\n }),\n ])\n .messaging({ enabled: true })\n .blackboardConfig({\n enabled: true,\n sections: { findings: [], sources: [], draft: '' },\n })\n .withAssessor({ preferLocal: true })\n .build(cogitator);\n\nconst result = await swarm.run({\n input: 'Research the impact of AI on job markets',\n});\n```\n\n### Code Review Pipeline\n\n```typescript\nconst swarm = new SwarmBuilder('code-review')\n .strategy('pipeline')\n .pipeline({\n stages: [\n {\n agent: new Agent({\n name: 'syntax-checker',\n instructions: 'Check for syntax errors and style issues',\n }),\n },\n {\n agent: new Agent({\n name: 'security-reviewer',\n instructions: 'Check for security vulnerabilities',\n }),\n },\n {\n agent: new Agent({\n name: 'performance-reviewer',\n instructions: 'Check for performance issues',\n }),\n },\n {\n agent: new Agent({\n name: 'summarizer',\n instructions: 'Summarize all findings',\n }),\n },\n ],\n stopOnError: false,\n passContext: true,\n })\n .build(cogitator);\n```\n\n### Decision Making with Consensus\n\n```typescript\nconst swarm = new SwarmBuilder('investment-committee')\n .strategy('consensus')\n .agents([\n new Agent({ name: 'risk-analyst', instructions: 'Evaluate risks' }),\n new Agent({ name: 'growth-analyst', instructions: 'Evaluate growth potential' }),\n new Agent({ name: 'market-analyst', instructions: 'Evaluate market conditions' }),\n ])\n .consensus({\n votingMethod: 'weighted',\n minVotes: 3,\n weights: { 'risk-analyst': 1.5, 'growth-analyst': 1.0, 'market-analyst': 1.0 },\n })\n .build(cogitator);\n\nconst result = await swarm.run({\n input: 'Should we invest in Company X?',\n});\n\nconsole.log('Decision:', result.output);\nconsole.log('Vote breakdown:', result.metadata?.votes);\n```\n\n---\n\n## License\n\nMIT\n","readmeFilename":"README.md"}