# 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 ```yaml 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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 ```python # 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()) ``` [{"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"}]