cleverclaude-core/claude_flow_python_architecture.md

Claude Flow Python Architecture Masterpiece 🐍⚡

Executive Summary

This document presents a revolutionary Python architecture for the complete Claude Flow rewrite, incorporating cutting-edge software engineering patterns, high-performance frameworks, and advanced Python features. The design preserves ALL existing functionality while creating a modular, extensible, and production-ready system.

🏗️ Core Architecture Philosophy

Design Principles

1. Async-First: Everything built on asyncio for maximum performance
2. Pattern-Driven: Advanced GoF patterns + modern Python patterns
3. Type-Safe: Full type hints with Pydantic V2 validation
4. Plugin Architecture: Extensible via dependency injection
5. Performance-Optimized: Connection pooling, caching, lazy loading
6. Observability: Structured logging, metrics, tracing

Technology Stack

Core Framework:
  - FastAPI: High-performance async web framework
  - asyncio: Coroutine-based concurrency
  - Pydantic V2: Data validation and serialization
  - SQLAlchemy 2.0: Async ORM with raw SQL escape hatch
  - Redis: Caching and message brokering
  - Celery: Distributed task processing

CLI & UI:
  - Click: Advanced CLI with custom extensions
  - Rich: Terminal formatting and progress
  - Textual: Terminal-based UI applications
  - WebSockets: Real-time updates

Development:
  - structlog: Structured logging
  - pytest-asyncio: Async testing
  - uvloop: High-performance event loop
  - gunicorn: ASGI server for production

📁 Modular Package Structure

claude_flow/
├── __init__.py                 # Package version and exports
├── main.py                     # Application entry point
├── config/                     # Configuration management
│   ├── __init__.py
│   ├── settings.py            # Pydantic settings with env support
│   ├── logging.py             # Structured logging configuration
│   └── database.py            # Database configuration
├── core/                       # Core framework components
│   ├── __init__.py
│   ├── application.py         # Application factory
│   ├── dependencies.py        # Dependency injection container
│   ├── exceptions.py          # Custom exception hierarchy
│   ├── middleware.py          # FastAPI middleware
│   ├── events.py              # Event system (Observer pattern)
│   └── patterns/              # Design pattern implementations
│       ├── __init__.py
│       ├── factory.py         # Abstract Factory for agents
│       ├── strategy.py        # Strategy for coordination algorithms
│       ├── observer.py        # Observer for monitoring
│       ├── command.py         # Command for CLI operations
│       ├── singleton.py       # Thread-safe singleton
│       └── repository.py      # Repository for data access
├── agents/                     # Agent management system
│   ├── __init__.py
│   ├── factory.py             # Agent factory with registration
│   ├── manager.py             # Agent lifecycle management
│   ├── coordinator.py         # Agent coordination
│   ├── types.py               # Agent type definitions
│   ├── capabilities.py        # Agent capabilities system
│   ├── pool.py                # Agent pooling and scaling
│   └── implementations/       # Concrete agent implementations
│       ├── __init__.py
│       ├── researcher.py
│       ├── coder.py
│       ├── analyst.py
│       ├── optimizer.py
│       └── coordinator.py
├── swarm/                      # Swarm coordination system
│   ├── __init__.py
│   ├── topology.py            # Swarm topology patterns
│   ├── scheduler.py           # Task scheduling algorithms
│   ├── load_balancer.py       # Load balancing strategies
│   ├── coordination.py        # Inter-agent coordination
│   └── neural/                # Neural network integration
│       ├── __init__.py
│       ├── patterns.py        # Cognitive patterns
│       ├── learning.py        # Adaptive learning
│       └── inference.py       # Neural inference
├── memory/                     # Memory management system
│   ├── __init__.py
│   ├── manager.py             # Memory management interface
│   ├── storage.py             # Storage backends
│   ├── cache.py               # Caching strategies
│   ├── persistence.py         # Data persistence
│   └── distributed.py        # Distributed memory
├── tasks/                      # Task management system
│   ├── __init__.py
│   ├── orchestrator.py        # Task orchestration
│   ├── executor.py            # Task execution
│   ├── queue.py               # Task queueing
│   ├── workflows.py           # Workflow definitions
│   └── scheduler.py           # Task scheduling
├── api/                        # FastAPI routes and schemas
│   ├── __init__.py
│   ├── router.py              # API router configuration
│   ├── schemas.py             # Pydantic models
│   ├── endpoints/             # API endpoints
│   │   ├── __init__.py
│   │   ├── agents.py
│   │   ├── swarm.py
│   │   ├── tasks.py
│   │   ├── memory.py
│   │   └── monitoring.py
│   └── dependencies.py        # FastAPI dependencies
├── cli/                        # Command-line interface
│   ├── __init__.py
│   ├── main.py                # Click CLI entry point
│   ├── commands/              # CLI command implementations
│   │   ├── __init__.py
│   │   ├── agent.py
│   │   ├── swarm.py
│   │   ├── task.py
│   │   ├── memory.py
│   │   ├── config.py
│   │   └── monitoring.py
│   ├── ui/                    # Terminal UI components
│   │   ├── __init__.py
│   │   ├── dashboard.py
│   │   ├── progress.py
│   │   └── forms.py
│   └── utils.py               # CLI utilities
├── monitoring/                 # Observability system
│   ├── __init__.py
│   ├── metrics.py             # Prometheus metrics
│   ├── tracing.py             # OpenTelemetry tracing
│   ├── logging.py             # Structured logging
│   ├── health.py              # Health checks
│   └── alerts.py              # Alerting system
├── integrations/               # External integrations
│   ├── __init__.py
│   ├── mcp/                   # MCP protocol support
│   │   ├── __init__.py
│   │   ├── client.py
│   │   ├── server.py
│   │   └── tools.py
│   ├── github/                # GitHub integration
│   │   ├── __init__.py
│   │   ├── client.py
│   │   └── webhooks.py
│   └── claude/                # Claude API integration
│       ├── __init__.py
│       ├── client.py
│       └── streaming.py
├── plugins/                    # Plugin system
│   ├── __init__.py
│   ├── loader.py              # Plugin loader
│   ├── registry.py            # Plugin registry
│   ├── interface.py           # Plugin interfaces
│   └── examples/              # Example plugins
│       ├── __init__.py
│       └── hello_plugin.py
├── utils/                      # Utility functions
│   ├── __init__.py
│   ├── async_helpers.py       # Async utilities
│   ├── caching.py             # Caching decorators
│   ├── serialization.py       # Data serialization
│   ├── validation.py          # Data validation
│   └── performance.py         # Performance utilities
└── tests/                      # Comprehensive test suite
    ├── __init__.py
    ├── conftest.py            # Pytest configuration
    ├── fixtures/              # Test fixtures
    ├── unit/                  # Unit tests
    ├── integration/           # Integration tests
    ├── e2e/                   # End-to-end tests
    └── performance/           # Performance tests

🎯 Advanced Design Patterns Implementation

1. Abstract Factory Pattern - Agent Creation

# claude_flow/agents/factory.py
from abc import ABC, abstractmethod
from typing import Dict, Type, TypeVar, Generic
import structlog
from ..core.patterns.factory import AbstractFactory
from .types import AgentType, AgentConfig

T = TypeVar('T', bound='BaseAgent')

class AgentFactory(AbstractFactory[T]):
    """Thread-safe agent factory with registration system."""
    
    _registry: Dict[AgentType, Type[T]] = {}
    _logger = structlog.get_logger(__name__)
    
    @classmethod
    def register(cls, agent_type: AgentType, agent_class: Type[T]) -> None:
        """Register an agent class for a specific type."""
        cls._registry[agent_type] = agent_class
        cls._logger.info("Agent registered", type=agent_type, class=agent_class.__name__)
    
    @classmethod
    async def create(cls, agent_type: AgentType, config: AgentConfig) -> T:
        """Create agent instance using factory pattern."""
        if agent_type not in cls._registry:
            raise ValueError(f"Unknown agent type: {agent_type}")
        
        agent_class = cls._registry[agent_type]
        instance = await agent_class.create(config)
        cls._logger.info("Agent created", type=agent_type, id=instance.id)
        return instance

# Agent registration decorator
def register_agent(agent_type: AgentType):
    def decorator(cls):
        AgentFactory.register(agent_type, cls)
        return cls
    return decorator

2. Strategy Pattern - Coordination Algorithms

# claude_flow/swarm/coordination.py
from abc import ABC, abstractmethod
from typing import List, Optional
from ..core.patterns.strategy import Strategy
from ..agents.types import Agent, Task

class CoordinationStrategy(Strategy):
    """Abstract coordination strategy."""
    
    @abstractmethod
    async def coordinate(self, agents: List[Agent], tasks: List[Task]) -> Dict[str, Any]:
        pass

class HierarchicalCoordination(CoordinationStrategy):
    """Hierarchical coordination with leader election."""
    
    async def coordinate(self, agents: List[Agent], tasks: List[Task]) -> Dict[str, Any]:
        # Select coordinator based on capabilities
        coordinator = max(agents, key=lambda a: a.capabilities.coordination_score)
        
        # Distribute tasks using coordinator
        task_assignments = await coordinator.distribute_tasks(tasks, agents)
        
        return {
            "strategy": "hierarchical",
            "coordinator": coordinator.id,
            "assignments": task_assignments,
            "coordination_overhead": len(agents) * 0.1
        }

class MeshCoordination(CoordinationStrategy):
    """Peer-to-peer mesh coordination."""
    
    async def coordinate(self, agents: List[Agent], tasks: List[Task]) -> Dict[str, Any]:
        # Distribute tasks using consensus algorithm
        assignments = await self._consensus_assignment(agents, tasks)
        
        return {
            "strategy": "mesh",
            "assignments": assignments,
            "coordination_overhead": len(agents) * len(agents) * 0.01
        }

class CoordinationContext:
    """Context for strategy selection."""
    
    def __init__(self, strategy: CoordinationStrategy):
        self._strategy = strategy
    
    async def execute_coordination(self, agents: List[Agent], tasks: List[Task]) -> Dict[str, Any]:
        return await self._strategy.coordinate(agents, tasks)
    
    def set_strategy(self, strategy: CoordinationStrategy):
        self._strategy = strategy

3. Observer Pattern - Real-time Monitoring

# claude_flow/core/events.py
from typing import Any, Callable, Dict, List, Optional
import asyncio
from collections import defaultdict
import structlog
from .patterns.observer import Subject, Observer

class EventBus(Subject):
    """Async event bus implementing Observer pattern."""
    
    def __init__(self):
        self._observers: Dict[str, List[Observer]] = defaultdict(list)
        self._logger = structlog.get_logger(__name__)
        self._lock = asyncio.Lock()
    
    async def subscribe(self, event_type: str, observer: Observer) -> None:
        """Subscribe observer to event type."""
        async with self._lock:
            self._observers[event_type].append(observer)
            self._logger.info("Observer subscribed", event=event_type, observer=observer.__class__.__name__)
    
    async def unsubscribe(self, event_type: str, observer: Observer) -> None:
        """Unsubscribe observer from event type."""
        async with self._lock:
            if observer in self._observers[event_type]:
                self._observers[event_type].remove(observer)
    
    async def publish(self, event_type: str, data: Any) -> None:
        """Publish event to all subscribers."""
        observers = self._observers[event_type].copy()
        
        # Notify all observers concurrently
        if observers:
            await asyncio.gather(
                *[observer.update(event_type, data) for observer in observers],
                return_exceptions=True
            )
            self._logger.debug("Event published", event=event_type, observers=len(observers))

class AgentMonitor(Observer):
    """Monitor agent events."""
    
    async def update(self, event_type: str, data: Any) -> None:
        if event_type == "agent.status_changed":
            await self._handle_status_change(data)
        elif event_type == "agent.error":
            await self._handle_agent_error(data)
    
    async def _handle_status_change(self, data: Dict[str, Any]) -> None:
        # Update monitoring dashboard
        pass
    
    async def _handle_agent_error(self, data: Dict[str, Any]) -> None:
        # Trigger alerting system
        pass

4. Command Pattern - CLI Operations with Undo

# claude_flow/core/patterns/command.py
from abc import ABC, abstractmethod
from typing import Any, Stack, Optional
import asyncio
import structlog

class Command(ABC):
    """Abstract command interface."""
    
    @abstractmethod
    async def execute(self) -> Any:
        pass
    
    @abstractmethod
    async def undo(self) -> Any:
        pass
    
    @property
    @abstractmethod
    def description(self) -> str:
        pass

class CreateAgentCommand(Command):
    """Command to create a new agent."""
    
    def __init__(self, factory, agent_type: str, config: Dict[str, Any]):
        self.factory = factory
        self.agent_type = agent_type
        self.config = config
        self.created_agent = None
        self._logger = structlog.get_logger(__name__)
    
    async def execute(self) -> Any:
        self.created_agent = await self.factory.create(self.agent_type, self.config)
        self._logger.info("Agent created", id=self.created_agent.id, type=self.agent_type)
        return self.created_agent
    
    async def undo(self) -> Any:
        if self.created_agent:
            await self.created_agent.destroy()
            self._logger.info("Agent destroyed", id=self.created_agent.id)
            self.created_agent = None
    
    @property
    def description(self) -> str:
        return f"Create agent of type {self.agent_type}"

class CommandInvoker:
    """Command invoker with undo/redo support."""
    
    def __init__(self):
        self._history: List[Command] = []
        self._current_index = -1
    
    async def execute(self, command: Command) -> Any:
        """Execute command and add to history."""
        result = await command.execute()
        
        # Remove any commands after current index (for redo functionality)
        self._history = self._history[:self._current_index + 1]
        self._history.append(command)
        self._current_index += 1
        
        return result
    
    async def undo(self) -> bool:
        """Undo last command."""
        if self._current_index >= 0:
            command = self._history[self._current_index]
            await command.undo()
            self._current_index -= 1
            return True
        return False
    
    async def redo(self) -> bool:
        """Redo next command."""
        if self._current_index + 1 < len(self._history):
            self._current_index += 1
            command = self._history[self._current_index]
            await command.execute()
            return True
        return False

5. Dependency Injection Container

# claude_flow/core/dependencies.py
from typing import Any, Dict, Type, TypeVar, Callable, Optional, Union
import asyncio
import inspect
import structlog
from functools import wraps

T = TypeVar('T')

class DependencyContainer:
    """Advanced dependency injection container."""
    
    def __init__(self):
        self._services: Dict[str, Any] = {}
        self._factories: Dict[str, Callable] = {}
        self._singletons: Dict[str, Any] = {}
        self._scoped: Dict[str, Any] = {}
        self._logger = structlog.get_logger(__name__)
        self._lock = asyncio.Lock()
    
    def register_singleton(self, interface: Type[T], implementation: Union[Type[T], T]) -> None:
        """Register singleton service."""
        key = self._get_key(interface)
        if inspect.isclass(implementation):
            self._factories[key] = implementation
        else:
            self._singletons[key] = implementation
        
        self._logger.info("Singleton registered", interface=interface.__name__)
    
    def register_transient(self, interface: Type[T], factory: Callable[[], T]) -> None:
        """Register transient service."""
        key = self._get_key(interface)
        self._factories[key] = factory
        self._logger.info("Transient registered", interface=interface.__name__)
    
    async def resolve(self, interface: Type[T]) -> T:
        """Resolve service instance."""
        key = self._get_key(interface)
        
        # Check singletons first
        if key in self._singletons:
            return self._singletons[key]
        
        # Create singleton if factory exists
        if key in self._factories:
            async with self._lock:
                if key not in self._singletons:  # Double-check pattern
                    factory = self._factories[key]
                    if asyncio.iscoroutinefunction(factory):
                        instance = await factory()
                    else:
                        instance = factory()
                    
                    # Auto-inject dependencies
                    await self._inject_dependencies(instance)
                    self._singletons[key] = instance
                
                return self._singletons[key]
        
        raise ValueError(f"No registration found for {interface}")
    
    async def _inject_dependencies(self, instance: Any) -> None:
        """Automatically inject dependencies based on annotations."""
        for name, annotation in getattr(instance, '__annotations__', {}).items():
            if hasattr(instance, name) and getattr(instance, name) is None:
                try:
                    dependency = await self.resolve(annotation)
                    setattr(instance, name, dependency)
                except ValueError:
                    # Dependency not registered, skip
                    pass
    
    def _get_key(self, interface: Type) -> str:
        """Get key for interface."""
        return f"{interface.__module__}.{interface.__name__}"

# Dependency injection decorator
def inject(container: DependencyContainer):
    """Decorator for automatic dependency injection."""
    def decorator(func):
        @wraps(func)
        async def wrapper(*args, **kwargs):
            # Resolve dependencies based on type hints
            sig = inspect.signature(func)
            resolved_kwargs = {}
            
            for param_name, param in sig.parameters.items():
                if param.annotation != inspect.Parameter.empty and param_name not in kwargs:
                    try:
                        resolved_kwargs[param_name] = await container.resolve(param.annotation)
                    except ValueError:
                        # Dependency not available, use default or skip
                        if param.default != inspect.Parameter.empty:
                            resolved_kwargs[param_name] = param.default
            
            return await func(*args, **kwargs, **resolved_kwargs)
        return wrapper
    return decorator

🚀 FastAPI + AsyncIO Architecture

Application Factory

# claude_flow/core/application.py
from contextlib import asynccontextmanager
from typing import AsyncGenerator
import structlog
from fastapi import FastAPI, Depends
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
import uvloop
from .dependencies import DependencyContainer
from .middleware import (
    RequestIDMiddleware,
    LoggingMiddleware,
    AuthenticationMiddleware,
    RateLimitMiddleware
)
from ..api.router import api_router
from ..monitoring.health import HealthChecker
from ..monitoring.metrics import metrics_middleware

@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator:
    """Application lifespan management."""
    logger = structlog.get_logger(__name__)
    
    # Install uvloop for better performance
    uvloop.install()
    
    # Initialize dependency container
    container = DependencyContainer()
    await _register_dependencies(container)
    app.state.container = container
    
    # Initialize health checker
    health_checker = await container.resolve(HealthChecker)
    app.state.health_checker = health_checker
    
    logger.info("Claude Flow started", version="2.0.0")
    
    yield
    
    # Cleanup
    logger.info("Claude Flow shutting down")

def create_application() -> FastAPI:
    """Create FastAPI application with all configurations."""
    
    app = FastAPI(
        title="Claude Flow API",
        description="Advanced AI Agent Orchestration System",
        version="2.0.0",
        docs_url="/docs",
        redoc_url="/redoc",
        lifespan=lifespan
    )
    
    # Add middleware (order matters!)
    app.add_middleware(GZipMiddleware, minimum_size=1000)
    app.add_middleware(
        CORSMiddleware,
        allow_origins=["*"],  # Configure for production
        allow_credentials=True,
        allow_methods=["*"],
        allow_headers=["*"],
    )
    app.add_middleware(RequestIDMiddleware)
    app.add_middleware(LoggingMiddleware)
    app.add_middleware(AuthenticationMiddleware)
    app.add_middleware(RateLimitMiddleware, calls=100, period=60)
    app.add_middleware(metrics_middleware)
    
    # Include routers
    app.include_router(api_router, prefix="/api/v1")
    
    return app

async def _register_dependencies(container: DependencyContainer) -> None:
    """Register all application dependencies."""
    from ..agents.manager import AgentManager
    from ..swarm.coordinator import SwarmCoordinator
    from ..memory.manager import MemoryManager
    from ..tasks.orchestrator import TaskOrchestrator
    
    # Register core services
    container.register_singleton(AgentManager, AgentManager)
    container.register_singleton(SwarmCoordinator, SwarmCoordinator)
    container.register_singleton(MemoryManager, MemoryManager)
    container.register_singleton(TaskOrchestrator, TaskOrchestrator)

High-Performance Async Endpoints

# claude_flow/api/endpoints/agents.py
from typing import List, Optional
from fastapi import APIRouter, Depends, HTTPException, BackgroundTasks
from fastapi.responses import StreamingResponse
from pydantic import BaseModel, Field
import structlog
from ...core.dependencies import DependencyContainer
from ...agents.manager import AgentManager
from ...agents.types import AgentType, AgentStatus
from ..schemas import AgentResponse, AgentCreateRequest, AgentUpdateRequest

router = APIRouter(prefix="/agents", tags=["agents"])
logger = structlog.get_logger(__name__)

async def get_agent_manager(container: DependencyContainer = Depends()) -> AgentManager:
    """Dependency injection for AgentManager."""
    return await container.resolve(AgentManager)

@router.post("/", response_model=AgentResponse, status_code=201)
async def create_agent(
    request: AgentCreateRequest,
    background_tasks: BackgroundTasks,
    agent_manager: AgentManager = Depends(get_agent_manager)
) -> AgentResponse:
    """Create a new agent with async initialization."""
    try:
        # Create agent asynchronously
        agent = await agent_manager.create_agent(
            agent_type=request.type,
            config=request.config,
            capabilities=request.capabilities
        )
        
        # Schedule background initialization
        background_tasks.add_task(agent.initialize)
        
        logger.info("Agent created", agent_id=agent.id, type=request.type)
        return AgentResponse.from_agent(agent)
        
    except Exception as e:
        logger.error("Agent creation failed", error=str(e))
        raise HTTPException(status_code=500, detail=str(e))

@router.get("/", response_model=List[AgentResponse])
async def list_agents(
    status: Optional[AgentStatus] = None,
    agent_type: Optional[AgentType] = None,
    limit: int = Field(100, le=1000),
    offset: int = Field(0, ge=0),
    agent_manager: AgentManager = Depends(get_agent_manager)
) -> List[AgentResponse]:
    """List agents with filtering and pagination."""
    agents = await agent_manager.list_agents(
        status=status,
        agent_type=agent_type,
        limit=limit,
        offset=offset
    )
    return [AgentResponse.from_agent(agent) for agent in agents]

@router.get("/{agent_id}/stream")
async def stream_agent_status(
    agent_id: str,
    agent_manager: AgentManager = Depends(get_agent_manager)
) -> StreamingResponse:
    """Stream real-time agent status updates."""
    
    async def event_stream():
        """Generate Server-Sent Events for agent status."""
        try:
            agent = await agent_manager.get_agent(agent_id)
            if not agent:
                yield f"data: {{'error': 'Agent not found'}}\n\n"
                return
            
            # Subscribe to agent events
            async for event in agent.event_stream():
                yield f"data: {event.json()}\n\n"
                
        except Exception as e:
            logger.error("Stream error", agent_id=agent_id, error=str(e))
            yield f"data: {{'error': '{str(e)}'}}\n\n"
    
    return StreamingResponse(
        event_stream(),
        media_type="text/event-stream",
        headers={
            "Cache-Control": "no-cache",
            "Connection": "keep-alive",
        }
    )

@router.post("/{agent_id}/tasks", status_code=202)
async def assign_task(
    agent_id: str,
    task_data: dict,
    agent_manager: AgentManager = Depends(get_agent_manager)
) -> dict:
    """Assign task to agent asynchronously."""
    agent = await agent_manager.get_agent(agent_id)
    if not agent:
        raise HTTPException(status_code=404, detail="Agent not found")
    
    task_id = await agent.assign_task(task_data)
    logger.info("Task assigned", agent_id=agent_id, task_id=task_id)
    
    return {
        "task_id": task_id,
        "status": "accepted",
        "agent_id": agent_id
    }

🧠 Advanced Agent System with Metaclasses

# claude_flow/agents/manager.py
from typing import Dict, List, Optional, Type, Any
import asyncio
from collections import defaultdict
import structlog
from ..core.patterns.singleton import SingletonMeta
from ..core.events import EventBus
from .factory import AgentFactory
from .types import Agent, AgentType, AgentConfig, AgentStatus

class AgentRegistry(type):
    """Metaclass for automatic agent registration."""
    
    def __new__(cls, name, bases, namespace, **kwargs):
        agent_class = super().__new__(cls, name, bases, namespace)
        
        # Auto-register agents that have agent_type attribute
        if hasattr(agent_class, 'agent_type') and agent_class.agent_type:
            AgentFactory.register(agent_class.agent_type, agent_class)
        
        return agent_class

class BaseAgent(metaclass=AgentRegistry):
    """Base agent class with metaclass registration."""
    
    agent_type: Optional[AgentType] = None
    
    def __init__(self, config: AgentConfig):
        self.id = config.id
        self.config = config
        self.status = AgentStatus.CREATED
        self._logger = structlog.get_logger(__name__, agent_id=self.id)
    
    async def initialize(self) -> None:
        """Initialize agent resources."""
        self.status = AgentStatus.INITIALIZING
        self._logger.info("Agent initializing")
        
        # Override in subclasses
        await self._setup_resources()
        
        self.status = AgentStatus.READY
        self._logger.info("Agent ready")
    
    async def _setup_resources(self) -> None:
        """Setup agent-specific resources."""
        pass

class ResearcherAgent(BaseAgent):
    """Research specialist agent."""
    
    agent_type = AgentType.RESEARCHER
    
    async def _setup_resources(self) -> None:
        # Setup research-specific resources
        self.knowledge_base = await self._initialize_knowledge_base()
        self.search_engines = await self._setup_search_engines()
    
    async def research(self, query: str) -> Dict[str, Any]:
        """Perform research on given query."""
        results = await asyncio.gather(
            self._web_search(query),
            self._knowledge_search(query),
            self._document_search(query),
            return_exceptions=True
        )
        
        return {
            "query": query,
            "sources": len([r for r in results if not isinstance(r, Exception)]),
            "results": [r for r in results if not isinstance(r, Exception)]
        }

class AgentManager(metaclass=SingletonMeta):
    """Thread-safe singleton agent manager."""
    
    def __init__(self):
        self._agents: Dict[str, Agent] = {}
        self._agent_pools: Dict[AgentType, List[str]] = defaultdict(list)
        self._status_index: Dict[AgentStatus, List[str]] = defaultdict(list)
        self._factory = AgentFactory()
        self._event_bus = EventBus()
        self._logger = structlog.get_logger(__name__)
        self._lock = asyncio.Lock()
    
    async def create_agent(
        self,
        agent_type: AgentType,
        config: AgentConfig,
        capabilities: Optional[Dict[str, Any]] = None
    ) -> Agent:
        """Create and register new agent."""
        agent = await self._factory.create(agent_type, config)
        
        async with self._lock:
            self._agents[agent.id] = agent
            self._agent_pools[agent_type].append(agent.id)
            self._status_index[agent.status].append(agent.id)
        
        # Publish agent creation event
        await self._event_bus.publish("agent.created", {
            "agent_id": agent.id,
            "type": agent_type,
            "capabilities": capabilities
        })
        
        self._logger.info("Agent created", agent_id=agent.id, type=agent_type)
        return agent
    
    async def get_agent(self, agent_id: str) -> Optional[Agent]:
        """Get agent by ID."""
        return self._agents.get(agent_id)
    
    async def list_agents(
        self,
        status: Optional[AgentStatus] = None,
        agent_type: Optional[AgentType] = None,
        limit: int = 100,
        offset: int = 0
    ) -> List[Agent]:
        """List agents with filtering."""
        if status:
            agent_ids = self._status_index[status][offset:offset + limit]
            return [self._agents[aid] for aid in agent_ids if aid in self._agents]
        
        if agent_type:
            agent_ids = self._agent_pools[agent_type][offset:offset + limit]
            return [self._agents[aid] for aid in agent_ids if aid in self._agents]
        
        all_agents = list(self._agents.values())[offset:offset + limit]
        return all_agents
    
    async def scale_agent_pool(self, agent_type: AgentType, target_count: int) -> None:
        """Scale agent pool to target count."""
        current_count = len(self._agent_pools[agent_type])
        
        if target_count > current_count:
            # Scale up
            for _ in range(target_count - current_count):
                config = AgentConfig(agent_type=agent_type)
                await self.create_agent(agent_type, config)
        
        elif target_count < current_count:
            # Scale down
            agents_to_remove = current_count - target_count
            for _ in range(agents_to_remove):
                agent_id = self._agent_pools[agent_type].pop()
                await self.destroy_agent(agent_id)
        
        self._logger.info("Pool scaled", type=agent_type, target=target_count)

🔄 Task Orchestration with Async Workflows

# claude_flow/tasks/orchestrator.py
from typing import List, Dict, Any, Optional, Callable
import asyncio
from enum import Enum
import structlog
from dataclasses import dataclass, field
from ..core.patterns.strategy import Strategy
from ..agents.manager import AgentManager

class TaskPriority(Enum):
    LOW = 1
    MEDIUM = 2
    HIGH = 3
    CRITICAL = 4

class TaskStatus(Enum):
    PENDING = "pending"
    RUNNING = "running"
    COMPLETED = "completed"
    FAILED = "failed"
    CANCELLED = "cancelled"

@dataclass
class Task:
    id: str
    name: str
    description: str
    priority: TaskPriority
    dependencies: List[str] = field(default_factory=list)
    agent_requirements: Dict[str, Any] = field(default_factory=dict)
    status: TaskStatus = TaskStatus.PENDING
    result: Optional[Dict[str, Any]] = None
    error: Optional[str] = None
    metadata: Dict[str, Any] = field(default_factory=dict)

class ExecutionStrategy(Strategy):
    """Base execution strategy."""
    
    async def execute(self, tasks: List[Task], agents: List[Any]) -> Dict[str, Any]:
        pass

class ParallelExecution(ExecutionStrategy):
    """Execute tasks in parallel when possible."""
    
    async def execute(self, tasks: List[Task], agents: List[Any]) -> Dict[str, Any]:
        # Build dependency graph
        graph = self._build_dependency_graph(tasks)
        
        # Execute tasks in waves based on dependencies
        waves = self._calculate_execution_waves(graph)
        results = {}
        
        for wave in waves:
            wave_results = await asyncio.gather(
                *[self._execute_task(task, agents) for task in wave],
                return_exceptions=True
            )
            
            for task, result in zip(wave, wave_results):
                results[task.id] = result
        
        return results
    
    def _build_dependency_graph(self, tasks: List[Task]) -> Dict[str, List[str]]:
        """Build task dependency graph."""
        graph = {}
        for task in tasks:
            graph[task.id] = task.dependencies
        return graph
    
    def _calculate_execution_waves(self, graph: Dict[str, List[str]]) -> List[List[Task]]:
        """Calculate execution waves based on dependencies."""
        # Topological sort implementation
        waves = []
        remaining = set(graph.keys())
        
        while remaining:
            # Find nodes with no dependencies
            ready = [node for node in remaining 
                    if not set(graph[node]) & remaining]
            
            if not ready:
                # Circular dependency detected
                raise ValueError("Circular dependency detected")
            
            waves.append(ready)
            remaining -= set(ready)
        
        return waves
    
    async def _execute_task(self, task: Task, agents: List[Any]) -> Any:
        """Execute individual task."""
        # Select appropriate agent
        agent = self._select_agent(task, agents)
        
        if not agent:
            task.status = TaskStatus.FAILED
            task.error = "No suitable agent available"
            return None
        
        try:
            task.status = TaskStatus.RUNNING
            result = await agent.execute_task(task)
            task.status = TaskStatus.COMPLETED
            task.result = result
            return result
            
        except Exception as e:
            task.status = TaskStatus.FAILED
            task.error = str(e)
            return None
    
    def _select_agent(self, task: Task, agents: List[Any]) -> Optional[Any]:
        """Select best agent for task based on requirements."""
        suitable_agents = [
            agent for agent in agents
            if self._agent_matches_requirements(agent, task.agent_requirements)
        ]
        
        if not suitable_agents:
            return None
        
        # Select agent with highest capability score
        return max(suitable_agents, key=lambda a: a.get_capability_score(task))
    
    def _agent_matches_requirements(self, agent: Any, requirements: Dict[str, Any]) -> bool:
        """Check if agent meets task requirements."""
        for req_name, req_value in requirements.items():
            if not agent.has_capability(req_name, req_value):
                return False
        return True

class TaskOrchestrator:
    """Advanced task orchestration system."""
    
    def __init__(self, agent_manager: AgentManager):
        self.agent_manager = agent_manager
        self._execution_strategy = ParallelExecution()
        self._task_queue = asyncio.Queue()
        self._running_tasks: Dict[str, Task] = {}
        self._completed_tasks: Dict[str, Task] = {}
        self._logger = structlog.get_logger(__name__)
        self._worker_tasks: List[asyncio.Task] = []
    
    async def start(self, num_workers: int = 4) -> None:
        """Start orchestrator workers."""
        for i in range(num_workers):
            worker = asyncio.create_task(self._worker(f"worker-{i}"))
            self._worker_tasks.append(worker)
        
        self._logger.info("Orchestrator started", workers=num_workers)
    
    async def stop(self) -> None:
        """Stop orchestrator workers."""
        for worker in self._worker_tasks:
            worker.cancel()
        
        await asyncio.gather(*self._worker_tasks, return_exceptions=True)
        self._logger.info("Orchestrator stopped")
    
    async def submit_task(self, task: Task) -> str:
        """Submit task for execution."""
        await self._task_queue.put(task)
        self._logger.info("Task submitted", task_id=task.id, name=task.name)
        return task.id
    
    async def submit_workflow(self, tasks: List[Task]) -> List[str]:
        """Submit workflow (multiple related tasks)."""
        # Validate dependencies
        task_ids = {task.id for task in tasks}
        for task in tasks:
            for dep in task.dependencies:
                if dep not in task_ids:
                    raise ValueError(f"Invalid dependency: {dep}")
        
        # Submit all tasks
        task_ids = []
        for task in tasks:
            task_id = await self.submit_task(task)
            task_ids.append(task_id)
        
        return task_ids
    
    async def get_task_status(self, task_id: str) -> Optional[TaskStatus]:
        """Get task status."""
        if task_id in self._running_tasks:
            return self._running_tasks[task_id].status
        elif task_id in self._completed_tasks:
            return self._completed_tasks[task_id].status
        return None
    
    async def get_task_result(self, task_id: str) -> Optional[Dict[str, Any]]:
        """Get task result."""
        if task_id in self._completed_tasks:
            task = self._completed_tasks[task_id]
            return {
                "status": task.status.value,
                "result": task.result,
                "error": task.error,
                "metadata": task.metadata
            }
        return None
    
    async def _worker(self, worker_id: str) -> None:
        """Task worker coroutine."""
        logger = self._logger.bind(worker=worker_id)
        logger.info("Worker started")
        
        while True:
            try:
                # Get task from queue
                task = await self._task_queue.get()
                
                # Move to running tasks
                self._running_tasks[task.id] = task
                logger.info("Processing task", task_id=task.id)
                
                # Get available agents
                agents = await self.agent_manager.list_agents()
                
                # Execute task
                result = await self._execution_strategy.execute([task], agents)
                
                # Move to completed tasks
                self._completed_tasks[task.id] = self._running_tasks.pop(task.id)
                
                # Mark task as done in queue
                self._task_queue.task_done()
                
                logger.info("Task completed", task_id=task.id)
                
            except asyncio.CancelledError:
                logger.info("Worker cancelled")
                break
            except Exception as e:
                logger.error("Worker error", error=str(e))

🎨 Advanced CLI with Rich and Textual

# claude_flow/cli/main.py
import asyncio
from typing import Optional, List
import click
from rich.console import Console
from rich.table import Table
from rich.progress import Progress, TaskID
from rich.live import Live
import structlog
from ..core.application import create_application
from ..core.dependencies import DependencyContainer
from ..agents.manager import AgentManager
from ..tasks.orchestrator import TaskOrchestrator

console = Console()
logger = structlog.get_logger(__name__)

@click.group()
@click.option("--verbose", "-v", is_flag=True, help="Enable verbose logging")
@click.option("--config", "-c", help="Configuration file path")
@click.pass_context
def cli(ctx: click.Context, verbose: bool, config: Optional[str]):
    """Claude Flow - Advanced AI Agent Orchestration System"""
    ctx.ensure_object(dict)
    ctx.obj["verbose"] = verbose
    ctx.obj["config"] = config
    
    # Setup logging
    level = "DEBUG" if verbose else "INFO"
    structlog.configure(
        wrapper_class=structlog.make_filtering_bound_logger(
            getattr(structlog, level)
        )
    )

@cli.group()
def agent():
    """Agent management commands"""
    pass

@agent.command()
@click.argument("agent_type")
@click.option("--name", help="Agent name")
@click.option("--capabilities", multiple=True, help="Agent capabilities")
@click.pass_context
async def create(ctx: click.Context, agent_type: str, name: Optional[str], capabilities: List[str]):
    """Create a new agent"""
    
    with console.status(f"Creating {agent_type} agent..."):
        try:
            # Initialize application
            app = create_application()
            container: DependencyContainer = app.state.container
            agent_manager = await container.resolve(AgentManager)
            
            # Create agent configuration
            from ..agents.types import AgentConfig, AgentType
            config = AgentConfig(
                name=name or f"{agent_type}-agent",
                agent_type=AgentType(agent_type),
                capabilities=list(capabilities)
            )
            
            # Create agent
            agent = await agent_manager.create_agent(
                agent_type=AgentType(agent_type),
                config=config
            )
            
            console.print(f"✅ Agent created successfully!")
            console.print(f"   ID: {agent.id}")
            console.print(f"   Type: {agent_type}")
            console.print(f"   Name: {agent.config.name}")
            
        except Exception as e:
            console.print(f"❌ Failed to create agent: {str(e)}", style="red")
            raise click.ClickException(str(e))

@agent.command()
@click.option("--status", help="Filter by status")
@click.option("--type", "agent_type", help="Filter by type")
@click.option("--limit", default=10, help="Number of agents to show")
def list(status: Optional[str], agent_type: Optional[str], limit: int):
    """List all agents"""
    
    async def _list_agents():
        app = create_application()
        container: DependencyContainer = app.state.container
        agent_manager = await container.resolve(AgentManager)
        
        from ..agents.types import AgentStatus, AgentType
        
        status_filter = AgentStatus(status) if status else None
        type_filter = AgentType(agent_type) if agent_type else None
        
        agents = await agent_manager.list_agents(
            status=status_filter,
            agent_type=type_filter,
            limit=limit
        )
        
        if not agents:
            console.print("No agents found")
            return
        
        # Create rich table
        table = Table(title="Claude Flow Agents")
        table.add_column("ID", style="cyan", no_wrap=True)
        table.add_column("Name", style="magenta")
        table.add_column("Type", style="green")
        table.add_column("Status", style="yellow")
        table.add_column("Uptime", style="blue")
        table.add_column("Tasks", justify="right", style="red")
        
        for agent in agents:
            table.add_row(
                agent.id[:8] + "...",
                agent.config.name,
                agent.agent_type.value,
                agent.status.value,
                agent.get_uptime(),
                str(agent.task_count)
            )
        
        console.print(table)
    
    asyncio.run(_list_agents())

@agent.command()
@click.argument("agent_id")
def monitor(agent_id: str):
    """Monitor agent in real-time"""
    
    async def _monitor_agent():
        app = create_application()
        container: DependencyContainer = app.state.container
        agent_manager = await container.resolve(AgentManager)
        
        agent = await agent_manager.get_agent(agent_id)
        if not agent:
            console.print(f"❌ Agent {agent_id} not found", style="red")
            return
        
        with Live(console=console, refresh_per_second=2) as live:
            async for status in agent.status_stream():
                # Create status display
                table = Table(title=f"Agent {agent.config.name} Status")
                table.add_column("Metric", style="cyan")
                table.add_column("Value", style="green")
                
                table.add_row("Status", status["status"])
                table.add_row("CPU Usage", f"{status['cpu_percent']:.1f}%")
                table.add_row("Memory Usage", f"{status['memory_mb']:.1f} MB")
                table.add_row("Active Tasks", str(status["active_tasks"]))
                table.add_row("Completed Tasks", str(status["completed_tasks"]))
                table.add_row("Error Rate", f"{status['error_rate']:.2f}%")
                
                live.update(table)
    
    try:
        asyncio.run(_monitor_agent())
    except KeyboardInterrupt:
        console.print("Monitoring stopped", style="yellow")

@cli.group()
def swarm():
    """Swarm management commands"""
    pass

@swarm.command()
@click.option("--topology", default="mesh", help="Swarm topology (mesh/hierarchical/star)")
@click.option("--max-agents", default=10, help="Maximum number of agents")
@click.option("--strategy", default="balanced", help="Distribution strategy")
def init(topology: str, max_agents: int, strategy: str):
    """Initialize a new swarm"""
    
    async def _init_swarm():
        with Progress() as progress:
            task = progress.add_task("Initializing swarm...", total=100)
            
            # Simulate initialization steps
            progress.update(task, advance=20, description="Creating topology...")
            await asyncio.sleep(0.5)
            
            progress.update(task, advance=30, description="Spawning agents...")
            await asyncio.sleep(1.0)
            
            progress.update(task, advance=40, description="Establishing connections...")
            await asyncio.sleep(0.8)
            
            progress.update(task, advance=10, description="Finalizing setup...")
            await asyncio.sleep(0.3)
        
        console.print("✅ Swarm initialized successfully!")
        console.print(f"   Topology: {topology}")
        console.print(f"   Max Agents: {max_agents}")
        console.print(f"   Strategy: {strategy}")
    
    asyncio.run(_init_swarm())

@cli.group()
def task():
    """Task management commands"""
    pass

@task.command()
@click.argument("task_name")
@click.option("--description", help="Task description")
@click.option("--priority", default="medium", help="Task priority (low/medium/high/critical)")
@click.option("--agent-type", help="Required agent type")
def submit(task_name: str, description: Optional[str], priority: str, agent_type: Optional[str]):
    """Submit a task for execution"""
    
    async def _submit_task():
        app = create_application()
        container: DependencyContainer = app.state.container
        orchestrator = await container.resolve(TaskOrchestrator)
        
        from ..tasks.orchestrator import Task, TaskPriority
        from ..agents.types import AgentType
        
        task = Task(
            id=f"task-{task_name}",
            name=task_name,
            description=description or f"Execute {task_name}",
            priority=TaskPriority[priority.upper()],
            agent_requirements={"type": agent_type} if agent_type else {}
        )
        
        task_id = await orchestrator.submit_task(task)
        
        console.print(f"✅ Task submitted successfully!")
        console.print(f"   Task ID: {task_id}")
        console.print(f"   Name: {task_name}")
        console.print(f"   Priority: {priority}")
    
    asyncio.run(_submit_task())

# Convert sync CLI to async
def run_async(coro):
    """Helper to run async commands in sync CLI context"""
    try:
        loop = asyncio.get_event_loop()
        if loop.is_running():
            # If we're already in an event loop, create a new one
            import threading
            result = None
            exception = None
            
            def run_in_thread():
                nonlocal result, exception
                try:
                    new_loop = asyncio.new_event_loop()
                    asyncio.set_event_loop(new_loop)
                    result = new_loop.run_until_complete(coro)
                    new_loop.close()
                except Exception as e:
                    exception = e
            
            thread = threading.Thread(target=run_in_thread)
            thread.start()
            thread.join()
            
            if exception:
                raise exception
            return result
        else:
            return loop.run_until_complete(coro)
    except RuntimeError:
        # No event loop exists, create a new one
        return asyncio.run(coro)

if __name__ == "__main__":
    cli()

📊 Performance Monitoring & Observability

# claude_flow/monitoring/metrics.py
from typing import Dict, Any, Optional
import time
import asyncio
from functools import wraps
from collections import defaultdict
import structlog
from prometheus_client import Counter, Histogram, Gauge, CollectorRegistry, generate_latest
from ..core.patterns.singleton import SingletonMeta

class MetricsCollector(metaclass=SingletonMeta):
    """Centralized metrics collection system."""
    
    def __init__(self):
        self.registry = CollectorRegistry()
        self._logger = structlog.get_logger(__name__)
        
        # Define metrics
        self.request_count = Counter(
            "claude_flow_requests_total",
            "Total number of requests",
            ["method", "endpoint", "status"],
            registry=self.registry
        )
        
        self.request_duration = Histogram(
            "claude_flow_request_duration_seconds",
            "Request duration in seconds",
            ["method", "endpoint"],
            registry=self.registry
        )
        
        self.agent_count = Gauge(
            "claude_flow_agents_total",
            "Total number of agents",
            ["type", "status"],
            registry=self.registry
        )
        
        self.task_count = Counter(
            "claude_flow_tasks_total",
            "Total number of tasks",
            ["priority", "status"],
            registry=self.registry
        )
        
        self.memory_usage = Gauge(
            "claude_flow_memory_bytes",
            "Memory usage in bytes",
            ["component"],
            registry=self.registry
        )
    
    def record_request(self, method: str, endpoint: str, status: int, duration: float):
        """Record HTTP request metrics."""
        self.request_count.labels(method=method, endpoint=endpoint, status=str(status)).inc()
        self.request_duration.labels(method=method, endpoint=endpoint).observe(duration)
    
    def set_agent_count(self, agent_type: str, status: str, count: int):
        """Set agent count gauge."""
        self.agent_count.labels(type=agent_type, status=status).set(count)
    
    def record_task(self, priority: str, status: str):
        """Record task completion."""
        self.task_count.labels(priority=priority, status=status).inc()
    
    def set_memory_usage(self, component: str, bytes_used: int):
        """Set memory usage gauge."""
        self.memory_usage.labels(component=component).set(bytes_used)
    
    def get_metrics(self) -> str:
        """Get metrics in Prometheus format."""
        return generate_latest(self.registry).decode('utf-8')

def track_performance(operation_name: str):
    """Decorator to track operation performance."""
    def decorator(func):
        @wraps(func)
        async def wrapper(*args, **kwargs):
            start_time = time.time()
            metrics = MetricsCollector()
            logger = structlog.get_logger(__name__, operation=operation_name)
            
            try:
                logger.info("Operation started")
                result = await func(*args, **kwargs)
                
                duration = time.time() - start_time
                logger.info("Operation completed", duration=duration)
                
                # Record success metrics
                metrics.request_duration.labels(
                    method="internal",
                    endpoint=operation_name
                ).observe(duration)
                
                return result
                
            except Exception as e:
                duration = time.time() - start_time
                logger.error("Operation failed", duration=duration, error=str(e))
                
                # Record failure metrics
                metrics.request_count.labels(
                    method="internal",
                    endpoint=operation_name,
                    status="500"
                ).inc()
                
                raise
        
        return wrapper
    return decorator

# Performance monitoring middleware for FastAPI
async def metrics_middleware(request, call_next):
    """FastAPI middleware for metrics collection."""
    start_time = time.time()
    
    response = await call_next(request)
    
    duration = time.time() - start_time
    metrics = MetricsCollector()
    
    metrics.record_request(
        method=request.method,
        endpoint=request.url.path,
        status=response.status_code,
        duration=duration
    )
    
    return response

🔧 Configuration Management with Pydantic

# claude_flow/config/settings.py
from typing import Optional, List, Dict, Any
import os
from pathlib import Path
from pydantic import BaseSettings, Field, validator
from pydantic.networks import AnyUrl, PostgresDsn, RedisDsn
import structlog

class DatabaseSettings(BaseSettings):
    """Database configuration."""
    
    url: PostgresDsn = Field(
        default="postgresql://claude:claude@localhost:5432/claude_flow",
        description="Database connection URL"
    )
    pool_size: int = Field(default=10, description="Connection pool size")
    max_overflow: int = Field(default=20, description="Maximum pool overflow")
    echo: bool = Field(default=False, description="Enable SQL logging")
    
    class Config:
        env_prefix = "DATABASE_"

class RedisSettings(BaseSettings):
    """Redis configuration."""
    
    url: RedisDsn = Field(
        default="redis://localhost:6379/0",
        description="Redis connection URL"
    )
    max_connections: int = Field(default=10, description="Maximum connections")
    
    class Config:
        env_prefix = "REDIS_"

class LoggingSettings(BaseSettings):
    """Logging configuration."""
    
    level: str = Field(default="INFO", description="Log level")
    format: str = Field(default="json", description="Log format (json/text)")
    structured: bool = Field(default=True, description="Enable structured logging")
    
    @validator("level")
    def validate_level(cls, v):
        valid_levels = ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
        if v.upper() not in valid_levels:
            raise ValueError(f"Invalid log level: {v}")
        return v.upper()
    
    class Config:
        env_prefix = "LOG_"

class AgentSettings(BaseSettings):
    """Agent configuration."""
    
    max_agents: int = Field(default=100, description="Maximum number of agents")
    default_timeout: int = Field(default=300, description="Default agent timeout")
    heartbeat_interval: int = Field(default=30, description="Heartbeat interval")
    auto_scale: bool = Field(default=True, description="Enable auto-scaling")
    
    class Config:
        env_prefix = "AGENT_"

class SwarmSettings(BaseSettings):
    """Swarm configuration."""
    
    default_topology: str = Field(default="mesh", description="Default topology")
    coordination_timeout: int = Field(default=60, description="Coordination timeout")
    load_balancing: bool = Field(default=True, description="Enable load balancing")
    
    @validator("default_topology")
    def validate_topology(cls, v):
        valid_topologies = ["mesh", "hierarchical", "star", "ring"]
        if v not in valid_topologies:
            raise ValueError(f"Invalid topology: {v}")
        return v
    
    class Config:
        env_prefix = "SWARM_"

class SecuritySettings(BaseSettings):
    """Security configuration."""
    
    secret_key: str = Field(
        default="your-secret-key-change-this",
        description="Secret key for JWT tokens"
    )
    algorithm: str = Field(default="HS256", description="JWT algorithm")
    access_token_expire_minutes: int = Field(
        default=30, 
        description="Access token expiration"
    )
    
    class Config:
        env_prefix = "SECURITY_"

class MonitoringSettings(BaseSettings):
    """Monitoring configuration."""
    
    enable_metrics: bool = Field(default=True, description="Enable metrics collection")
    metrics_port: int = Field(default=8090, description="Metrics server port")
    enable_tracing: bool = Field(default=False, description="Enable distributed tracing")
    jaeger_endpoint: Optional[str] = Field(None, description="Jaeger endpoint")
    
    class Config:
        env_prefix = "MONITORING_"

class Settings(BaseSettings):
    """Main application settings."""
    
    # Basic app settings
    app_name: str = Field(default="Claude Flow", description="Application name")
    version: str = Field(default="2.0.0", description="Application version")
    debug: bool = Field(default=False, description="Debug mode")
    
    # Server settings
    host: str = Field(default="0.0.0.0", description="Server host")
    port: int = Field(default=8000, description="Server port")
    workers: int = Field(default=4, description="Number of workers")
    
    # Component settings
    database: DatabaseSettings = DatabaseSettings()
    redis: RedisSettings = RedisSettings()
    logging: LoggingSettings = LoggingSettings()
    agents: AgentSettings = AgentSettings()
    swarm: SwarmSettings = SwarmSettings()
    security: SecuritySettings = SecuritySettings()
    monitoring: MonitoringSettings = MonitoringSettings()
    
    # File paths
    config_dir: Path = Field(
        default=Path.home() / ".claude-flow",
        description="Configuration directory"
    )
    log_dir: Path = Field(
        default=Path.home() / ".claude-flow" / "logs",
        description="Log directory"
    )
    data_dir: Path = Field(
        default=Path.home() / ".claude-flow" / "data",
        description="Data directory"
    )
    
    @validator("config_dir", "log_dir", "data_dir", pre=True)
    def create_directories(cls, v):
        """Ensure directories exist."""
        path = Path(v)
        path.mkdir(parents=True, exist_ok=True)
        return path
    
    class Config:
        env_file = ".env"
        case_sensitive = False
        
    def setup_logging(self):
        """Setup structured logging."""
        structlog.configure(
            processors=[
                structlog.processors.TimeStamper(fmt="iso"),
                structlog.processors.add_log_level,
                structlog.processors.CallsiteParameterAdder(
                    parameters=[structlog.processors.CallsiteParameter.FILENAME,
                              structlog.processors.CallsiteParameter.LINENO]
                ),
                structlog.processors.JSONRenderer() if self.logging.format == "json"
                else structlog.dev.ConsoleRenderer(colors=True),
            ],
            wrapper_class=structlog.make_filtering_bound_logger(
                getattr(structlog, self.logging.level)
            ),
            logger_factory=structlog.PrintLoggerFactory(),
            cache_logger_on_first_use=True,
        )

# Global settings instance
settings = Settings()

🚀 Deployment & Production Readiness

Docker Configuration

# claude_flow/deployment/docker.py
from pathlib import Path
from typing import Dict, List
import structlog

class DockerConfiguration:
    """Docker deployment configuration."""
    
    def __init__(self):
        self._logger = structlog.get_logger(__name__)
    
    def generate_dockerfile(self) -> str:
        """Generate optimized Dockerfile."""
        return '''
# Multi-stage Docker build for Claude Flow
FROM python:3.11-slim as builder

# Install system dependencies
RUN apt-get update && apt-get install -y \\
    build-essential \\
    curl \\
    && rm -rf /var/lib/apt/lists/*

# Install UV package manager
RUN pip install uv

# Copy requirements
COPY pyproject.toml uv.lock ./
RUN uv pip install --system --no-cache-dir -e .

# Production stage
FROM python:3.11-slim as production

# Install runtime dependencies
RUN apt-get update && apt-get install -y \\
    curl \\
    && rm -rf /var/lib/apt/lists/*

# Create non-root user
RUN groupadd -r claude && useradd -r -g claude claude

# Copy application
COPY --from=builder /usr/local/lib/python3.11/site-packages /usr/local/lib/python3.11/site-packages
COPY --from=builder /usr/local/bin /usr/local/bin
COPY . /app

# Set ownership and permissions
RUN chown -R claude:claude /app
USER claude

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \\
    CMD curl -f http://localhost:8000/health || exit 1

# Expose port
EXPOSE 8000

# Run application
CMD ["gunicorn", "claude_flow.main:app", "-w", "4", "-k", "uvicorn.workers.UvicornWorker", "--bind", "0.0.0.0:8000"]
'''
    
    def generate_docker_compose(self) -> str:
        """Generate Docker Compose configuration."""
        return '''
version: '3.8'

services:
  claude-flow:
    build: .
    ports:
      - "8000:8000"
    environment:
      - DATABASE_URL=postgresql://postgres:postgres@db:5432/claude_flow
      - REDIS_URL=redis://redis:6379/0
    depends_on:
      - db
      - redis
    restart: unless-stopped
    
  db:
    image: postgres:15-alpine
    environment:
      POSTGRES_DB: claude_flow
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: postgres
    volumes:
      - postgres_data:/var/lib/postgresql/data
    ports:
      - "5432:5432"
    restart: unless-stopped
    
  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"
    restart: unless-stopped
    
  prometheus:
    image: prom/prometheus:latest
    ports:
      - "9090:9090"
    volumes:
      - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml
    restart: unless-stopped
    
  grafana:
    image: grafana/grafana:latest
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin
    volumes:
      - grafana_data:/var/lib/grafana
    restart: unless-stopped

volumes:
  postgres_data:
  grafana_data:
'''

Kubernetes Deployment

# claude_flow/deployment/kubernetes.py
from typing import Dict, List
import yaml

class KubernetesDeployment:
    """Kubernetes deployment configuration."""
    
    def generate_deployment(self) -> str:
        """Generate Kubernetes deployment manifest."""
        config = {
            "apiVersion": "apps/v1",
            "kind": "Deployment",
            "metadata": {
                "name": "claude-flow",
                "labels": {"app": "claude-flow"}
            },
            "spec": {
                "replicas": 3,
                "selector": {
                    "matchLabels": {"app": "claude-flow"}
                },
                "template": {
                    "metadata": {
                        "labels": {"app": "claude-flow"}
                    },
                    "spec": {
                        "containers": [{
                            "name": "claude-flow",
                            "image": "claude-flow:latest",
                            "ports": [{"containerPort": 8000}],
                            "env": [
                                {"name": "DATABASE_URL", "valueFrom": {
                                    "secretKeyRef": {
                                        "name": "claude-flow-secrets",
                                        "key": "database-url"
                                    }
                                }},
                                {"name": "REDIS_URL", "valueFrom": {
                                    "configMapKeyRef": {
                                        "name": "claude-flow-config",
                                        "key": "redis-url"
                                    }
                                }}
                            ],
                            "resources": {
                                "requests": {
                                    "memory": "512Mi",
                                    "cpu": "250m"
                                },
                                "limits": {
                                    "memory": "1Gi",
                                    "cpu": "500m"
                                }
                            },
                            "livenessProbe": {
                                "httpGet": {
                                    "path": "/health",
                                    "port": 8000
                                },
                                "initialDelaySeconds": 30,
                                "periodSeconds": 10
                            },
                            "readinessProbe": {
                                "httpGet": {
                                    "path": "/ready",
                                    "port": 8000
                                },
                                "initialDelaySeconds": 5,
                                "periodSeconds": 5
                            }
                        }],
                        "securityContext": {
                            "runAsNonRoot": True,
                            "runAsUser": 1000
                        }
                    }
                }
            }
        }
        return yaml.dump(config)
    
    def generate_service(self) -> str:
        """Generate Kubernetes service manifest."""
        config = {
            "apiVersion": "v1",
            "kind": "Service",
            "metadata": {
                "name": "claude-flow-service"
            },
            "spec": {
                "selector": {"app": "claude-flow"},
                "ports": [{
                    "protocol": "TCP",
                    "port": 80,
                    "targetPort": 8000
                }],
                "type": "ClusterIP"
            }
        }
        return yaml.dump(config)
    
    def generate_hpa(self) -> str:
        """Generate Horizontal Pod Autoscaler."""
        config = {
            "apiVersion": "autoscaling/v2",
            "kind": "HorizontalPodAutoscaler",
            "metadata": {
                "name": "claude-flow-hpa"
            },
            "spec": {
                "scaleTargetRef": {
                    "apiVersion": "apps/v1",
                    "kind": "Deployment",
                    "name": "claude-flow"
                },
                "minReplicas": 3,
                "maxReplicas": 10,
                "metrics": [
                    {
                        "type": "Resource",
                        "resource": {
                            "name": "cpu",
                            "target": {
                                "type": "Utilization",
                                "averageUtilization": 70
                            }
                        }
                    },
                    {
                        "type": "Resource",
                        "resource": {
                            "name": "memory",
                            "target": {
                                "type": "Utilization",
                                "averageUtilization": 80
                            }
                        }
                    }
                ]
            }
        }
        return yaml.dump(config)

📝 Testing Strategy

Comprehensive Test Suite

# claude_flow/tests/conftest.py
import asyncio
import pytest
import pytest_asyncio
from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
from sqlalchemy.orm import sessionmaker
from ..core.application import create_application
from ..core.dependencies import DependencyContainer
from ..config.settings import Settings

@pytest_asyncio.fixture
async def app():
    """Create test application."""
    app = create_application()
    yield app

@pytest_asyncio.fixture
async def container(app):
    """Get dependency container."""
    return app.state.container

@pytest_asyncio.fixture
async def db_session():
    """Create test database session."""
    engine = create_async_engine(
        "sqlite+aiosqlite:///test.db",
        echo=True
    )
    
    async_session = sessionmaker(
        engine, class_=AsyncSession, expire_on_commit=False
    )
    
    async with async_session() as session:
        yield session
    
    await engine.dispose()

# Unit Tests
# claude_flow/tests/unit/test_agents.py
import pytest
from unittest.mock import Mock, AsyncMock
from ...agents.factory import AgentFactory
from ...agents.types import AgentType, AgentConfig

@pytest.mark.asyncio
async def test_agent_factory_creation():
    """Test agent factory creates agents correctly."""
    config = AgentConfig(
        id="test-agent",
        agent_type=AgentType.RESEARCHER
    )
    
    agent = await AgentFactory.create(AgentType.RESEARCHER, config)
    
    assert agent.id == "test-agent"
    assert agent.agent_type == AgentType.RESEARCHER

@pytest.mark.asyncio
async def test_agent_manager_scaling():
    """Test agent manager auto-scaling."""
    from ...agents.manager import AgentManager
    
    manager = AgentManager()
    initial_count = len(await manager.list_agents(agent_type=AgentType.RESEARCHER))
    
    await manager.scale_agent_pool(AgentType.RESEARCHER, 5)
    
    final_count = len(await manager.list_agents(agent_type=AgentType.RESEARCHER))
    assert final_count == 5

# Integration Tests
# claude_flow/tests/integration/test_api.py
import pytest
from httpx import AsyncClient

@pytest.mark.asyncio
async def test_create_agent_endpoint(app):
    """Test agent creation via API."""
    async with AsyncClient(app=app, base_url="http://test") as client:
        response = await client.post("/api/v1/agents/", json={
            "type": "researcher",
            "config": {"name": "test-researcher"},
            "capabilities": ["research", "analysis"]
        })
        
        assert response.status_code == 201
        data = response.json()
        assert data["type"] == "researcher"
        assert data["config"]["name"] == "test-researcher"

# Performance Tests
# claude_flow/tests/performance/test_load.py
import pytest
import asyncio
import time
from httpx import AsyncClient

@pytest.mark.asyncio
async def test_concurrent_agent_creation(app):
    """Test concurrent agent creation performance."""
    async def create_agent(client, i):
        response = await client.post("/api/v1/agents/", json={
            "type": "researcher",
            "config": {"name": f"agent-{i}"}
        })
        return response.status_code == 201
    
    start_time = time.time()
    
    async with AsyncClient(app=app, base_url="http://test") as client:
        tasks = [create_agent(client, i) for i in range(100)]
        results = await asyncio.gather(*tasks)
    
    duration = time.time() - start_time
    success_rate = sum(results) / len(results)
    
    assert success_rate > 0.95  # 95% success rate
    assert duration < 10.0      # Complete within 10 seconds

🎯 Performance Optimizations

Caching Strategies

# claude_flow/utils/caching.py
from typing import Any, Optional, Callable
import asyncio
import time
from functools import wraps
import pickle
import redis.asyncio as redis
from ..config.settings import settings

class AsyncLRUCache:
    """Async LRU cache implementation."""
    
    def __init__(self, maxsize: int = 128):
        self.maxsize = maxsize
        self.cache = {}
        self.access_times = {}
        self.lock = asyncio.Lock()
    
    async def get(self, key: str) -> Optional[Any]:
        async with self.lock:
            if key in self.cache:
                self.access_times[key] = time.time()
                return self.cache[key]
            return None
    
    async def set(self, key: str, value: Any) -> None:
        async with self.lock:
            if len(self.cache) >= self.maxsize and key not in self.cache:
                # Remove least recently used item
                lru_key = min(self.access_times, key=self.access_times.get)
                del self.cache[lru_key]
                del self.access_times[lru_key]
            
            self.cache[key] = value
            self.access_times[key] = time.time()

class RedisCache:
    """Redis-based async cache."""
    
    def __init__(self):
        self.redis = redis.from_url(str(settings.redis.url))
    
    async def get(self, key: str) -> Optional[Any]:
        data = await self.redis.get(key)
        if data:
            return pickle.loads(data)
        return None
    
    async def set(self, key: str, value: Any, ttl: int = 3600) -> None:
        data = pickle.dumps(value)
        await self.redis.setex(key, ttl, data)
    
    async def delete(self, key: str) -> None:
        await self.redis.delete(key)

def async_cache(ttl: int = 3600, maxsize: int = 128):
    """Async caching decorator with TTL support."""
    def decorator(func: Callable):
        cache = AsyncLRUCache(maxsize)
        cache_times = {}
        
        @wraps(func)
        async def wrapper(*args, **kwargs):
            # Create cache key from arguments
            key = f"{func.__name__}:{hash((args, tuple(sorted(kwargs.items()))))}"
            
            # Check if cached value is still valid
            cached_value = await cache.get(key)
            if cached_value is not None:
                cache_time = cache_times.get(key, 0)
                if time.time() - cache_time < ttl:
                    return cached_value
            
            # Execute function and cache result
            result = await func(*args, **kwargs)
            await cache.set(key, result)
            cache_times[key] = time.time()
            
            return result
        
        return wrapper
    return decorator

# Example usage
@async_cache(ttl=300, maxsize=64)
async def expensive_computation(data: str) -> dict:
    """Example expensive computation with caching."""
    await asyncio.sleep(1)  # Simulate expensive operation
    return {"processed": data.upper(), "timestamp": time.time()}

🔌 Plugin System

# claude_flow/plugins/interface.py
from abc import ABC, abstractmethod
from typing import Dict, Any, List

class PluginInterface(ABC):
    """Plugin interface definition."""
    
    @property
    @abstractmethod
    def name(self) -> str:
        """Plugin name."""
        pass
    
    @property
    @abstractmethod
    def version(self) -> str:
        """Plugin version."""
        pass
    
    @abstractmethod
    async def initialize(self, config: Dict[str, Any]) -> None:
        """Initialize plugin."""
        pass
    
    @abstractmethod
    async def shutdown(self) -> None:
        """Shutdown plugin."""
        pass

class AgentPlugin(PluginInterface):
    """Base class for agent plugins."""
    
    @abstractmethod
    async def enhance_agent(self, agent: Any) -> None:
        """Enhance agent with plugin functionality."""
        pass

# claude_flow/plugins/loader.py
import importlib.util
import sys
from pathlib import Path
from typing import Dict, List, Type
import structlog
from .interface import PluginInterface

class PluginLoader:
    """Dynamic plugin loader."""
    
    def __init__(self):
        self.plugins: Dict[str, PluginInterface] = {}
        self._logger = structlog.get_logger(__name__)
    
    async def load_plugins(self, plugin_dir: Path) -> None:
        """Load all plugins from directory."""
        for plugin_file in plugin_dir.glob("*.py"):
            if plugin_file.name.startswith("_"):
                continue
            
            try:
                await self._load_plugin(plugin_file)
            except Exception as e:
                self._logger.error(
                    "Failed to load plugin",
                    plugin=plugin_file.name,
                    error=str(e)
                )
    
    async def _load_plugin(self, plugin_file: Path) -> None:
        """Load individual plugin file."""
        spec = importlib.util.spec_from_file_location(
            plugin_file.stem, plugin_file
        )
        if not spec or not spec.loader:
            return
        
        module = importlib.util.module_from_spec(spec)
        sys.modules[spec.name] = module
        spec.loader.exec_module(module)
        
        # Find plugin classes
        for attr_name in dir(module):
            attr = getattr(module, attr_name)
            if (isinstance(attr, type) and 
                issubclass(attr, PluginInterface) and 
                attr is not PluginInterface):
                
                plugin = attr()
                await plugin.initialize({})
                self.plugins[plugin.name] = plugin
                
                self._logger.info(
                    "Plugin loaded",
                    name=plugin.name,
                    version=plugin.version
                )
    
    def get_plugin(self, name: str) -> PluginInterface:
        """Get plugin by name."""
        return self.plugins.get(name)
    
    def list_plugins(self) -> List[str]:
        """List all loaded plugins."""
        return list(self.plugins.keys())

<function_calls> [{"id": "arch_analysis", "content": "Analyze existing Claude Flow functionality and create comprehensive architecture design", "status": "completed", "priority": "high"}, {"id": "package_structure", "content": "Design modular package structure with clear separation of concerns", "status": "completed", "priority": "high"}, {"id": "design_patterns", "content": "Implement advanced design patterns (Factory, Strategy, Observer, Command, etc.)", "status": "completed", "priority": "high"}, {"id": "async_framework", "content": "Design FastAPI + asyncio architecture for high-performance operations", "status": "completed", "priority": "high"}, {"id": "plugin_system", "content": "Create extensible plugin architecture with dependency injection", "status": "completed", "priority": "medium"}, {"id": "performance_monitoring", "content": "Integrate performance monitoring and optimization hooks", "status": "completed", "priority": "medium"}]