Architecture

SkinFlow is built with a modular, scalable architecture that enables flexible multi-agent systems. This guide provides a deep dive into the system architecture and design principles.

System Overview

SkinFlow follows a layered architecture that separates concerns and enables extensibility:

┌─────────────────────────────────────────────────────────────────┐
│                         Application Layer                         │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐ │
│  │   Chat UI   │  │   Web App   │  │   API       │  │   CLI       │ │
│  │   Interface │  │   Interface │  │   Gateway   │  │   Tool      │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                      SkinFlow Core Layer                         │
│  ┌─────────────────────────────────────────────────────────────┐ │
│  │                   Multi-Agent System                        │ │
│  │  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐       │ │
│  │  │  Planning   │  │ Sub-Agents  │  │ Coordination│       │ │
│  │  │   Agent    │  │  Manager    │  │   System    │       │ │
│  │  └─────────────┘  └─────────────┘  └─────────────┘       │ │
│  └─────────────────────────────────────────────────────────────┘ │
│                                                                 │
│  ┌─────────────────────────────────────────────────────────────┐ │
│  │                    Core Services                            │ │
│  │  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐       │ │
│  │  │    LLM      │  │   Memory    │  │    Tool     │       │ │
│  │  │ Abstraction │  │   System    │  │   Registry  │       │ │
│  │  └─────────────┘  └─────────────┘  └─────────────┘       │ │
│  └─────────────────────────────────────────────────────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                      Infrastructure Layer                        │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐ │
│  │   Fallback  │  │   Virtual   │  │   Stream    │  │   Event    │ │
│  │   Manager   │  │ FileSystem  │  │   Engine    │  │   System   │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                       Storage Layer                              │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐ │
│  │ PostgreSQL  │  │   SQLite    │  │    Redis    │  │   Files    │ │
│  │   (Prod)    │  │   (Dev)     │  │  (Cache)    │  │  (Local)   │ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘ │
└─────────────────────────────────────────────────────────────────┘

Core Components

1. Multi-Agent System

Planning Agent

The Planning Agent is responsible for:

• Task Analysis: Understanding user requests and requirements
• Task Decomposition: Breaking complex tasks into manageable subtasks
• Plan Generation: Creating execution plans with dependencies
• Progress Monitoring: Tracking task completion and handling failures

// Planning Agent workflow
class PlanningAgent {
  async analyzeRequest(request) {
    // Understand user intent and requirements
    return this.extractIntent(request)
  }

  async decomposeTask(task) {
    // Break down complex tasks into subtasks
    return this.generateSubtasks(task)
  }

  async createPlan(subtasks) {
    // Create execution plan with dependencies
    return this.scheduleTasks(subtasks)
  }

  async monitorExecution(plan) {
    // Track progress and handle failures
    return this.updatePlanStatus(plan)
  }
}

Sub-Agent Manager

Manages specialized agents and their execution:

• Agent Registry: Maintains available agents and their capabilities
• Agent Selection: Chooses appropriate agents for tasks
• Resource Management: Allocates resources to agents
• Lifecycle Management: Handles agent creation and destruction

class SubAgentManager {
  constructor() {
    this.agents = new Map()
    this.capabilities = new Map()
  }

  async registerAgent(agent) {
    // Register agent with its capabilities
    this.agents.set(agent.id, agent)
    this.capabilities.set(agent.id, agent.getCapabilities())
  }

  async selectAgent(task) {
    // Select best agent for the task
    return this.findBestMatch(task, this.capabilities)
  }

  async executeTask(agent, task) {
    // Execute task with selected agent
    return agent.execute(task)
  }
}

Coordination System

Handles inter-agent communication and coordination:

• Message Routing: Routes messages between agents
• Synchronization: Coordinates concurrent agent operations
• Conflict Resolution: Resolves conflicts between agents
• Result Aggregation: Combines results from multiple agents

2. Core Services

LLM Abstraction

Provides a unified interface for different LLM providers:

class LLMService {
  constructor(config) {
    this.provider = this.createProvider(config.provider, config)
  }

  async chat(messages, options = {}) {
    return this.provider.chat(messages, options)
  }

  async stream(messages, options = {}) {
    return this.provider.stream(messages, options)
  }

  createProvider(provider, config) {
    switch (provider) {
      case 'openai':
        return new OpenAIProvider(config)
      case 'anthropic':
        return new AnthropicProvider(config)
      case 'http':
        return new HTTPProvider(config)
      default:
        throw new Error(`Unsupported provider: ${provider}`)
    }
  }
}

Memory System

Manages both short-term and long-term memory:

class MemorySystem {
  constructor(config) {
    this.shortTerm = new ShortTermMemory(config.shortTerm)
    this.longTerm = new LongTermMemory(config.longTerm)
    this.semanticSearch = new SemanticSearch(config.search)
  }

  async store(memory) {
    // Store in both short-term and long-term memory
    await this.shortTerm.store(memory)
    await this.longTerm.store(memory)
  }

  async retrieve(query, options = {}) {
    // Retrieve from memory with semantic search
    return this.semanticSearch.search(query, options)
  }

  async consolidate() {
    // Move important memories from short-term to long-term
    const memories = await this.shortTerm.getImportantMemories()
    await this.longTerm.storeBatch(memories)
  }
}

Tool Registry

Manages available tools and their execution:

class ToolRegistry {
  constructor() {
    this.tools = new Map()
    this.permissions = new Map()
  }

  async registerTool(tool) {
    // Register tool with security checks
    this.validateTool(tool)
    this.tools.set(tool.name, tool)
    this.permissions.set(tool.name, tool.permissions || [])
  }

  async executeTool(name, params, context) {
    // Execute tool with permission checks
    await this.checkPermission(name, context.userId, 'execute')
    const tool = this.tools.get(name)
    return await tool.execute(params, context)
  }
}

3. Infrastructure Layer

Fallback Manager

Handles error recovery and fallback mechanisms:

class FallbackManager {
  constructor(config) {
    this.strategies = config.strategies || []
    this.circuitBreaker = new CircuitBreaker(config.circuitBreaker)
  }

  async executeWithFallback(operation, context) {
    try {
      return await this.circuitBreaker.execute(operation, context)
    } catch (error) {
      return await this.handleFallback(error, context)
    }
  }

  async handleFallback(error, context) {
    // Try fallback strategies
    for (const strategy of this.strategies) {
      try {
        return await strategy.execute(error, context)
      } catch (fallbackError) {
        continue
      }
    }
    throw error
  }
}

Virtual File System

Provides secure file operations:

class VirtualFileSystem {
  constructor(config) {
    this.basePath = config.basePath
    this.allowedPaths = config.allowedPaths || []
    this.sandbox = config.enableSandbox
  }

  async readFile(path, options = {}) {
    // Secure file reading with path validation
    this.validatePath(path)
    return await fs.readFile(this.resolvePath(path), options)
  }

  async writeFile(path, content, options = {}) {
    // Secure file writing with permission checks
    this.validatePath(path)
    await this.checkWritePermission(path)
    return await fs.writeFile(this.resolvePath(path), content, options)
  }
}

Stream Engine

Handles real-time stream processing:

class StreamEngine {
  constructor() {
    this.streams = new Map()
    this.processors = new Map()
  }

  async createStream(request, options = {}) {
    // Create new stream for real-time processing
    const stream = new TransformStream()
    this.streams.set(request.id, stream)
    this.processStream(request, stream)
    return stream
  }

  async processStream(request, stream) {
    // Process request with streaming output
    const processor = this.getProcessor(request.type)
    for await (const chunk of processor.process(request)) {
      stream.write(chunk)
    }
    stream.end()
  }
}

Data Flow

Request Processing Flow

User Request
    ↓
Planning Agent (Task Analysis & Decomposition)
    ↓
Sub-Agent Manager (Agent Selection)
    ↓
Agent Execution (with Tool Integration)
    ↓
Memory System (Context Management)
    ↓
Result Aggregation & Response
    ↓
User Response

Memory Management Flow

User Interaction
    ↓
Short-term Memory (Session Context)
    ↓
Memory Consolidation (Important → Long-term)
    ↓
Long-term Memory (Persistent Storage)
    ↓
Semantic Search (Intelligent Retrieval)
    ↓
Context Enhancement (Future Interactions)

Tool Execution Flow

Agent Request
    ↓
Tool Registry (Validation)
    ↓
Permission Check (Security)
    ↓
Tool Execution (Sandboxed)
    ↓
Result Processing
    ↓
Agent Response

Security Architecture

Permission System

• Role-based Access Control: Different access levels for different users
• Tool Permissions: Fine-grained control over tool execution
• Resource Limits: Prevent resource abuse and DoS attacks

Sandboxing

• Process Isolation: Tools run in isolated environments
• Path Restrictions: Limited file system access
• Network Controls: Restricted network access

Data Protection

• Encryption: Data at rest and in transit
• Audit Logging: Complete audit trail of all operations
• Data Retention: Configurable data retention policies

Performance Considerations

Caching Strategy

• LLM Response Caching: Cache LLM responses to reduce API calls
• Memory Caching: Cache frequently accessed memories
• Tool Result Caching: Cache tool execution results

Resource Management

• Connection Pooling: Reuse database and API connections
• Memory Management: Efficient memory usage and garbage collection
• Concurrency Control: Limit concurrent operations to prevent overload

Scalability

• Horizontal Scaling: Support for multiple instances
• Load Balancing: Distribute load across instances
• Graceful Degradation: Maintain functionality under heavy load

Extensibility Points

Custom Agents

class CustomAgent extends BaseAgent {
  async execute(task) {
    // Custom agent implementation
    return await this.processTask(task)
  }

  getCapabilities() {
    return ['custom-task', 'data-processing']
  }
}

Custom Tools

class CustomTool extends BaseTool {
  async execute(params, context) {
    // Custom tool implementation
    return await this.performOperation(params, context)
  }
}

Custom Memory Backends

class CustomMemoryBackend extends BaseMemoryBackend {
  async store(memory) {
    // Custom storage implementation
  }

  async retrieve(query) {
    // Custom retrieval implementation
  }
}

Monitoring and Observability

Metrics Collection

• Performance Metrics: Response times, success rates, resource usage
• Business Metrics: Task completion, user satisfaction, error rates
• System Health: Memory usage, CPU usage, disk space

Logging

• Structured Logging: JSON-formatted logs for easy parsing
• Log Levels: Debug, info, warn, error with configurable levels
• Log Aggregation: Centralized log collection and analysis

Tracing

• Request Tracing: Track requests across the system
• Distributed Tracing: Trace requests across multiple services
• Performance Analysis: Identify bottlenecks and optimization opportunities

Next Steps

• Configuration - Learn about configuration options
• API Reference - Detailed API documentation
• Examples - Practical implementations