feat: implement agent coordination foundation (Week 1)
✅ Multi-Agent Communication Framework - Implemented comprehensive communication protocols - Created hierarchical, P2P, and broadcast protocols - Added message types and routing system - Implemented agent discovery and registration - Created load balancer for task distribution - Built FastAPI application with full API ✅ Core Components Implemented - CommunicationManager: Protocol management - MessageRouter: Advanced message routing - AgentRegistry: Agent discovery and management - LoadBalancer: Intelligent task distribution - TaskDistributor: Priority-based task handling - WebSocketHandler: Real-time communication ✅ API Endpoints - /health: Health check endpoint - /agents/register: Agent registration - /agents/discover: Agent discovery - /tasks/submit: Task submission - /messages/send: Message sending - /load-balancer/stats: Load balancing statistics - /registry/stats: Registry statistics ✅ Production Ready - SystemD service configuration - Docker containerization - Comprehensive test suite - Configuration management - Error handling and logging - Performance monitoring 🚀 Week 1 complete: Agent coordination foundation implemented!
This commit is contained in:
aitbc
641
apps/agent-coordinator/src/app/routing/agent_discovery.py
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641
apps/agent-coordinator/src/app/routing/agent_discovery.py
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"""
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Agent Discovery and Registration System for AITBC Agent Coordination
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"""
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import asyncio
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import json
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import logging
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from typing import Dict, List, Optional, Set, Callable, Any
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from dataclasses import dataclass, field
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from datetime import datetime, timedelta
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import uuid
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import hashlib
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from enum import Enum
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import redis.asyncio as redis
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from pydantic import BaseModel, Field
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from ..protocols.message_types import DiscoveryMessage, create_discovery_message
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from ..protocols.communication import AgentMessage, MessageType
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logger = logging.getLogger(__name__)
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class AgentStatus(str, Enum):
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"""Agent status enumeration"""
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ACTIVE = "active"
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INACTIVE = "inactive"
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BUSY = "busy"
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MAINTENANCE = "maintenance"
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ERROR = "error"
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class AgentType(str, Enum):
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"""Agent type enumeration"""
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COORDINATOR = "coordinator"
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WORKER = "worker"
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SPECIALIST = "specialist"
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MONITOR = "monitor"
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GATEWAY = "gateway"
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ORCHESTRATOR = "orchestrator"
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@dataclass
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class AgentInfo:
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"""Agent information structure"""
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agent_id: str
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agent_type: AgentType
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status: AgentStatus
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capabilities: List[str]
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services: List[str]
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endpoints: Dict[str, str]
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metadata: Dict[str, Any]
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last_heartbeat: datetime
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registration_time: datetime
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load_metrics: Dict[str, float] = field(default_factory=dict)
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health_score: float = 1.0
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version: str = "1.0.0"
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tags: Set[str] = field(default_factory=set)
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def to_dict(self) -> Dict[str, Any]:
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"""Convert to dictionary"""
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return {
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"agent_id": self.agent_id,
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"agent_type": self.agent_type.value,
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"status": self.status.value,
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"capabilities": self.capabilities,
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"services": self.services,
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"endpoints": self.endpoints,
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"metadata": self.metadata,
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"last_heartbeat": self.last_heartbeat.isoformat(),
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"registration_time": self.registration_time.isoformat(),
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"load_metrics": self.load_metrics,
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"health_score": self.health_score,
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"version": self.version,
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"tags": list(self.tags)
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}
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@classmethod
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def from_dict(cls, data: Dict[str, Any]) -> "AgentInfo":
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"""Create from dictionary"""
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data["agent_type"] = AgentType(data["agent_type"])
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data["status"] = AgentStatus(data["status"])
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data["last_heartbeat"] = datetime.fromisoformat(data["last_heartbeat"])
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data["registration_time"] = datetime.fromisoformat(data["registration_time"])
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data["tags"] = set(data.get("tags", []))
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return cls(**data)
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class AgentRegistry:
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"""Central agent registry for discovery and management"""
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def __init__(self, redis_url: str = "redis://localhost:6379/1"):
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self.redis_url = redis_url
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self.redis_client: Optional[redis.Redis] = None
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self.agents: Dict[str, AgentInfo] = {}
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self.service_index: Dict[str, Set[str]] = {} # service -> agent_ids
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self.capability_index: Dict[str, Set[str]] = {} # capability -> agent_ids
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self.type_index: Dict[AgentType, Set[str]] = {} # agent_type -> agent_ids
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self.heartbeat_interval = 30 # seconds
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self.cleanup_interval = 60 # seconds
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self.max_heartbeat_age = 120 # seconds
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async def start(self):
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"""Start the registry service"""
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self.redis_client = redis.from_url(self.redis_url)
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# Load existing agents from Redis
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await self._load_agents_from_redis()
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# Start background tasks
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asyncio.create_task(self._heartbeat_monitor())
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asyncio.create_task(self._cleanup_inactive_agents())
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logger.info("Agent registry started")
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async def stop(self):
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"""Stop the registry service"""
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if self.redis_client:
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await self.redis_client.close()
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logger.info("Agent registry stopped")
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async def register_agent(self, agent_info: AgentInfo) -> bool:
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"""Register a new agent"""
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try:
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# Add to local registry
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self.agents[agent_info.agent_id] = agent_info
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# Update indexes
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self._update_indexes(agent_info)
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# Save to Redis
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await self._save_agent_to_redis(agent_info)
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# Publish registration event
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await self._publish_agent_event("agent_registered", agent_info)
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logger.info(f"Agent {agent_info.agent_id} registered successfully")
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return True
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except Exception as e:
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logger.error(f"Error registering agent {agent_info.agent_id}: {e}")
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return False
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async def unregister_agent(self, agent_id: str) -> bool:
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"""Unregister an agent"""
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try:
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if agent_id not in self.agents:
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logger.warning(f"Agent {agent_id} not found for unregistration")
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return False
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agent_info = self.agents[agent_id]
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# Remove from local registry
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del self.agents[agent_id]
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# Update indexes
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self._remove_from_indexes(agent_info)
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# Remove from Redis
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await self._remove_agent_from_redis(agent_id)
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# Publish unregistration event
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await self._publish_agent_event("agent_unregistered", agent_info)
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logger.info(f"Agent {agent_id} unregistered successfully")
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return True
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except Exception as e:
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logger.error(f"Error unregistering agent {agent_id}: {e}")
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return False
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async def update_agent_status(self, agent_id: str, status: AgentStatus, load_metrics: Optional[Dict[str, float]] = None) -> bool:
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"""Update agent status and metrics"""
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try:
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if agent_id not in self.agents:
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logger.warning(f"Agent {agent_id} not found for status update")
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return False
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agent_info = self.agents[agent_id]
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agent_info.status = status
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agent_info.last_heartbeat = datetime.utcnow()
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if load_metrics:
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agent_info.load_metrics.update(load_metrics)
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# Update health score
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agent_info.health_score = self._calculate_health_score(agent_info)
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# Save to Redis
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await self._save_agent_to_redis(agent_info)
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# Publish status update event
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await self._publish_agent_event("agent_status_updated", agent_info)
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return True
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except Exception as e:
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logger.error(f"Error updating agent status {agent_id}: {e}")
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return False
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async def update_agent_heartbeat(self, agent_id: str) -> bool:
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"""Update agent heartbeat"""
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try:
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if agent_id not in self.agents:
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logger.warning(f"Agent {agent_id} not found for heartbeat")
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return False
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agent_info = self.agents[agent_id]
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agent_info.last_heartbeat = datetime.utcnow()
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# Update health score
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agent_info.health_score = self._calculate_health_score(agent_info)
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# Save to Redis
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await self._save_agent_to_redis(agent_info)
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return True
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except Exception as e:
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logger.error(f"Error updating heartbeat for {agent_id}: {e}")
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return False
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async def discover_agents(self, query: Dict[str, Any]) -> List[AgentInfo]:
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"""Discover agents based on query criteria"""
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results = []
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try:
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# Start with all agents
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candidate_agents = list(self.agents.values())
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# Apply filters
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if "agent_type" in query:
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agent_type = AgentType(query["agent_type"])
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candidate_agents = [a for a in candidate_agents if a.agent_type == agent_type]
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if "status" in query:
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status = AgentStatus(query["status"])
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candidate_agents = [a for a in candidate_agents if a.status == status]
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if "capabilities" in query:
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required_capabilities = set(query["capabilities"])
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candidate_agents = [a for a in candidate_agents if required_capabilities.issubset(a.capabilities)]
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if "services" in query:
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required_services = set(query["services"])
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candidate_agents = [a for a in candidate_agents if required_services.issubset(a.services)]
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if "tags" in query:
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required_tags = set(query["tags"])
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candidate_agents = [a for a in candidate_agents if required_tags.issubset(a.tags)]
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if "min_health_score" in query:
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min_score = query["min_health_score"]
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candidate_agents = [a for a in candidate_agents if a.health_score >= min_score]
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# Sort by health score (highest first)
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results = sorted(candidate_agents, key=lambda a: a.health_score, reverse=True)
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# Limit results if specified
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if "limit" in query:
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results = results[:query["limit"]]
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logger.info(f"Discovered {len(results)} agents for query: {query}")
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return results
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except Exception as e:
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logger.error(f"Error discovering agents: {e}")
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return []
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async def get_agent_by_id(self, agent_id: str) -> Optional[AgentInfo]:
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"""Get agent information by ID"""
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return self.agents.get(agent_id)
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async def get_agents_by_service(self, service: str) -> List[AgentInfo]:
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"""Get agents that provide a specific service"""
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agent_ids = self.service_index.get(service, set())
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return [self.agents[agent_id] for agent_id in agent_ids if agent_id in self.agents]
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async def get_agents_by_capability(self, capability: str) -> List[AgentInfo]:
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"""Get agents that have a specific capability"""
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agent_ids = self.capability_index.get(capability, set())
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return [self.agents[agent_id] for agent_id in agent_ids if agent_id in self.agents]
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async def get_agents_by_type(self, agent_type: AgentType) -> List[AgentInfo]:
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"""Get agents of a specific type"""
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agent_ids = self.type_index.get(agent_type, set())
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return [self.agents[agent_id] for agent_id in agent_ids if agent_id in self.agents]
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async def get_registry_stats(self) -> Dict[str, Any]:
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"""Get registry statistics"""
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total_agents = len(self.agents)
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status_counts = {}
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type_counts = {}
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for agent_info in self.agents.values():
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# Count by status
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status = agent_info.status.value
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status_counts[status] = status_counts.get(status, 0) + 1
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# Count by type
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agent_type = agent_info.agent_type.value
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type_counts[agent_type] = type_counts.get(agent_type, 0) + 1
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return {
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"total_agents": total_agents,
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"status_counts": status_counts,
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"type_counts": type_counts,
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"service_count": len(self.service_index),
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"capability_count": len(self.capability_index),
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"last_cleanup": datetime.utcnow().isoformat()
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}
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def _update_indexes(self, agent_info: AgentInfo):
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"""Update search indexes"""
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# Service index
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for service in agent_info.services:
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if service not in self.service_index:
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self.service_index[service] = set()
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self.service_index[service].add(agent_info.agent_id)
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# Capability index
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for capability in agent_info.capabilities:
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if capability not in self.capability_index:
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self.capability_index[capability] = set()
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self.capability_index[capability].add(agent_info.agent_id)
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# Type index
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if agent_info.agent_type not in self.type_index:
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self.type_index[agent_info.agent_type] = set()
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self.type_index[agent_info.agent_type].add(agent_info.agent_id)
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def _remove_from_indexes(self, agent_info: AgentInfo):
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"""Remove agent from search indexes"""
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# Service index
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for service in agent_info.services:
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if service in self.service_index:
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self.service_index[service].discard(agent_info.agent_id)
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if not self.service_index[service]:
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del self.service_index[service]
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# Capability index
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for capability in agent_info.capabilities:
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if capability in self.capability_index:
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self.capability_index[capability].discard(agent_info.agent_id)
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if not self.capability_index[capability]:
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del self.capability_index[capability]
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# Type index
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if agent_info.agent_type in self.type_index:
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self.type_index[agent_info.agent_type].discard(agent_info.agent_id)
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if not self.type_index[agent_info.agent_type]:
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del self.type_index[agent_info.agent_type]
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def _calculate_health_score(self, agent_info: AgentInfo) -> float:
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"""Calculate agent health score"""
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base_score = 1.0
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# Penalty for high load
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if agent_info.load_metrics:
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avg_load = sum(agent_info.load_metrics.values()) / len(agent_info.load_metrics)
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if avg_load > 0.8:
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base_score -= 0.3
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elif avg_load > 0.6:
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base_score -= 0.1
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# Penalty for error status
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if agent_info.status == AgentStatus.ERROR:
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base_score -= 0.5
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elif agent_info.status == AgentStatus.MAINTENANCE:
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base_score -= 0.2
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elif agent_info.status == AgentStatus.BUSY:
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base_score -= 0.1
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# Penalty for old heartbeat
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heartbeat_age = (datetime.utcnow() - agent_info.last_heartbeat).total_seconds()
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if heartbeat_age > self.max_heartbeat_age:
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base_score -= 0.5
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elif heartbeat_age > self.max_heartbeat_age / 2:
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base_score -= 0.2
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return max(0.0, min(1.0, base_score))
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async def _save_agent_to_redis(self, agent_info: AgentInfo):
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"""Save agent information to Redis"""
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if not self.redis_client:
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return
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key = f"agent:{agent_info.agent_id}"
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await self.redis_client.setex(
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key,
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timedelta(hours=24), # 24 hour TTL
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json.dumps(agent_info.to_dict())
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)
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async def _remove_agent_from_redis(self, agent_id: str):
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"""Remove agent from Redis"""
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if not self.redis_client:
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return
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key = f"agent:{agent_id}"
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await self.redis_client.delete(key)
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async def _load_agents_from_redis(self):
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"""Load agents from Redis"""
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if not self.redis_client:
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return
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try:
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# Get all agent keys
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keys = await self.redis_client.keys("agent:*")
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for key in keys:
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data = await self.redis_client.get(key)
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if data:
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agent_info = AgentInfo.from_dict(json.loads(data))
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self.agents[agent_info.agent_id] = agent_info
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self._update_indexes(agent_info)
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logger.info(f"Loaded {len(self.agents)} agents from Redis")
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||||
except Exception as e:
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logger.error(f"Error loading agents from Redis: {e}")
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||||
async def _publish_agent_event(self, event_type: str, agent_info: AgentInfo):
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||||
"""Publish agent event to Redis"""
|
||||
if not self.redis_client:
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||||
return
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||||
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||||
event = {
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||||
"event_type": event_type,
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||||
"timestamp": datetime.utcnow().isoformat(),
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||||
"agent_info": agent_info.to_dict()
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||||
}
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||||
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||||
await self.redis_client.publish("agent_events", json.dumps(event))
|
||||
|
||||
async def _heartbeat_monitor(self):
|
||||
"""Monitor agent heartbeats"""
|
||||
while True:
|
||||
try:
|
||||
await asyncio.sleep(self.heartbeat_interval)
|
||||
|
||||
# Check for agents with old heartbeats
|
||||
now = datetime.utcnow()
|
||||
for agent_id, agent_info in list(self.agents.items()):
|
||||
heartbeat_age = (now - agent_info.last_heartbeat).total_seconds()
|
||||
|
||||
if heartbeat_age > self.max_heartbeat_age:
|
||||
# Mark as inactive
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||||
if agent_info.status != AgentStatus.INACTIVE:
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||||
await self.update_agent_status(agent_id, AgentStatus.INACTIVE)
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||||
logger.warning(f"Agent {agent_id} marked as inactive due to old heartbeat")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in heartbeat monitor: {e}")
|
||||
await asyncio.sleep(5)
|
||||
|
||||
async def _cleanup_inactive_agents(self):
|
||||
"""Clean up inactive agents"""
|
||||
while True:
|
||||
try:
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||||
await asyncio.sleep(self.cleanup_interval)
|
||||
|
||||
# Remove agents that have been inactive too long
|
||||
now = datetime.utcnow()
|
||||
max_inactive_age = timedelta(hours=1) # 1 hour
|
||||
|
||||
for agent_id, agent_info in list(self.agents.items()):
|
||||
if agent_info.status == AgentStatus.INACTIVE:
|
||||
inactive_age = now - agent_info.last_heartbeat
|
||||
if inactive_age > max_inactive_age:
|
||||
await self.unregister_agent(agent_id)
|
||||
logger.info(f"Removed inactive agent {agent_id}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in cleanup task: {e}")
|
||||
await asyncio.sleep(5)
|
||||
|
||||
class AgentDiscoveryService:
|
||||
"""Service for agent discovery and registration"""
|
||||
|
||||
def __init__(self, registry: AgentRegistry):
|
||||
self.registry = registry
|
||||
self.discovery_handlers: Dict[str, Callable] = {}
|
||||
|
||||
def register_discovery_handler(self, handler_name: str, handler: Callable):
|
||||
"""Register a discovery handler"""
|
||||
self.discovery_handlers[handler_name] = handler
|
||||
logger.info(f"Registered discovery handler: {handler_name}")
|
||||
|
||||
async def handle_discovery_request(self, message: AgentMessage) -> Optional[AgentMessage]:
|
||||
"""Handle agent discovery request"""
|
||||
try:
|
||||
discovery_data = DiscoveryMessage(**message.payload)
|
||||
|
||||
# Update or register agent
|
||||
agent_info = AgentInfo(
|
||||
agent_id=discovery_data.agent_id,
|
||||
agent_type=AgentType(discovery_data.agent_type),
|
||||
status=AgentStatus.ACTIVE,
|
||||
capabilities=discovery_data.capabilities,
|
||||
services=discovery_data.services,
|
||||
endpoints=discovery_data.endpoints,
|
||||
metadata=discovery_data.metadata,
|
||||
last_heartbeat=datetime.utcnow(),
|
||||
registration_time=datetime.utcnow()
|
||||
)
|
||||
|
||||
# Register or update agent
|
||||
if discovery_data.agent_id in self.registry.agents:
|
||||
await self.registry.update_agent_status(discovery_data.agent_id, AgentStatus.ACTIVE)
|
||||
else:
|
||||
await self.registry.register_agent(agent_info)
|
||||
|
||||
# Send response with available agents
|
||||
available_agents = await self.registry.discover_agents({
|
||||
"status": "active",
|
||||
"limit": 50
|
||||
})
|
||||
|
||||
response_data = {
|
||||
"discovery_agents": [agent.to_dict() for agent in available_agents],
|
||||
"registry_stats": await self.registry.get_registry_stats()
|
||||
}
|
||||
|
||||
response = AgentMessage(
|
||||
sender_id="discovery_service",
|
||||
receiver_id=message.sender_id,
|
||||
message_type=MessageType.DISCOVERY,
|
||||
payload=response_data,
|
||||
correlation_id=message.id
|
||||
)
|
||||
|
||||
return response
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error handling discovery request: {e}")
|
||||
return None
|
||||
|
||||
async def find_best_agent(self, requirements: Dict[str, Any]) -> Optional[AgentInfo]:
|
||||
"""Find the best agent for given requirements"""
|
||||
try:
|
||||
# Build discovery query
|
||||
query = {}
|
||||
|
||||
if "agent_type" in requirements:
|
||||
query["agent_type"] = requirements["agent_type"]
|
||||
|
||||
if "capabilities" in requirements:
|
||||
query["capabilities"] = requirements["capabilities"]
|
||||
|
||||
if "services" in requirements:
|
||||
query["services"] = requirements["services"]
|
||||
|
||||
if "min_health_score" in requirements:
|
||||
query["min_health_score"] = requirements["min_health_score"]
|
||||
|
||||
# Discover agents
|
||||
agents = await self.registry.discover_agents(query)
|
||||
|
||||
if not agents:
|
||||
return None
|
||||
|
||||
# Select best agent (highest health score)
|
||||
return agents[0]
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error finding best agent: {e}")
|
||||
return None
|
||||
|
||||
async def get_service_endpoints(self, service: str) -> Dict[str, List[str]]:
|
||||
"""Get all endpoints for a specific service"""
|
||||
try:
|
||||
agents = await self.registry.get_agents_by_service(service)
|
||||
endpoints = {}
|
||||
|
||||
for agent in agents:
|
||||
for service_name, endpoint in agent.endpoints.items():
|
||||
if service_name not in endpoints:
|
||||
endpoints[service_name] = []
|
||||
endpoints[service_name].append(endpoint)
|
||||
|
||||
return endpoints
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting service endpoints: {e}")
|
||||
return {}
|
||||
|
||||
# Factory functions
|
||||
def create_agent_info(agent_id: str, agent_type: str, capabilities: List[str], services: List[str], endpoints: Dict[str, str]) -> AgentInfo:
|
||||
"""Create agent information"""
|
||||
return AgentInfo(
|
||||
agent_id=agent_id,
|
||||
agent_type=AgentType(agent_type),
|
||||
status=AgentStatus.ACTIVE,
|
||||
capabilities=capabilities,
|
||||
services=services,
|
||||
endpoints=endpoints,
|
||||
metadata={},
|
||||
last_heartbeat=datetime.utcnow(),
|
||||
registration_time=datetime.utcnow()
|
||||
)
|
||||
|
||||
# Example usage
|
||||
async def example_usage():
|
||||
"""Example of how to use the agent discovery system"""
|
||||
|
||||
# Create registry
|
||||
registry = AgentRegistry()
|
||||
await registry.start()
|
||||
|
||||
# Create discovery service
|
||||
discovery_service = AgentDiscoveryService(registry)
|
||||
|
||||
# Register an agent
|
||||
agent_info = create_agent_info(
|
||||
agent_id="agent-001",
|
||||
agent_type="worker",
|
||||
capabilities=["data_processing", "analysis"],
|
||||
services=["process_data", "analyze_results"],
|
||||
endpoints={"http": "http://localhost:8001", "ws": "ws://localhost:8002"}
|
||||
)
|
||||
|
||||
await registry.register_agent(agent_info)
|
||||
|
||||
# Discover agents
|
||||
agents = await registry.discover_agents({
|
||||
"capabilities": ["data_processing"],
|
||||
"status": "active"
|
||||
})
|
||||
|
||||
print(f"Found {len(agents)} agents")
|
||||
|
||||
# Find best agent
|
||||
best_agent = await discovery_service.find_best_agent({
|
||||
"capabilities": ["data_processing"],
|
||||
"min_health_score": 0.8
|
||||
})
|
||||
|
||||
if best_agent:
|
||||
print(f"Best agent: {best_agent.agent_id}")
|
||||
|
||||
await registry.stop()
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(example_usage())
|
||||
716
apps/agent-coordinator/src/app/routing/load_balancer.py
Normal file
716
apps/agent-coordinator/src/app/routing/load_balancer.py
Normal file
@@ -0,0 +1,716 @@
|
||||
"""
|
||||
Load Balancer for Agent Distribution and Task Assignment
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, List, Optional, Tuple, Any, Callable
|
||||
from dataclasses import dataclass, field
|
||||
from datetime import datetime, timedelta
|
||||
from enum import Enum
|
||||
import statistics
|
||||
import uuid
|
||||
from collections import defaultdict, deque
|
||||
|
||||
from .agent_discovery import AgentRegistry, AgentInfo, AgentStatus, AgentType
|
||||
from ..protocols.message_types import TaskMessage, create_task_message
|
||||
from ..protocols.communication import AgentMessage, MessageType, Priority
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class LoadBalancingStrategy(str, Enum):
|
||||
"""Load balancing strategies"""
|
||||
ROUND_ROBIN = "round_robin"
|
||||
LEAST_CONNECTIONS = "least_connections"
|
||||
LEAST_RESPONSE_TIME = "least_response_time"
|
||||
WEIGHTED_ROUND_ROBIN = "weighted_round_robin"
|
||||
RESOURCE_BASED = "resource_based"
|
||||
CAPABILITY_BASED = "capability_based"
|
||||
PREDICTIVE = "predictive"
|
||||
CONSISTENT_HASH = "consistent_hash"
|
||||
|
||||
class TaskPriority(str, Enum):
|
||||
"""Task priority levels"""
|
||||
LOW = "low"
|
||||
NORMAL = "normal"
|
||||
HIGH = "high"
|
||||
CRITICAL = "critical"
|
||||
URGENT = "urgent"
|
||||
|
||||
@dataclass
|
||||
class LoadMetrics:
|
||||
"""Agent load metrics"""
|
||||
cpu_usage: float = 0.0
|
||||
memory_usage: float = 0.0
|
||||
active_connections: int = 0
|
||||
pending_tasks: int = 0
|
||||
completed_tasks: int = 0
|
||||
failed_tasks: int = 0
|
||||
avg_response_time: float = 0.0
|
||||
last_updated: datetime = field(default_factory=datetime.utcnow)
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"cpu_usage": self.cpu_usage,
|
||||
"memory_usage": self.memory_usage,
|
||||
"active_connections": self.active_connections,
|
||||
"pending_tasks": self.pending_tasks,
|
||||
"completed_tasks": self.completed_tasks,
|
||||
"failed_tasks": self.failed_tasks,
|
||||
"avg_response_time": self.avg_response_time,
|
||||
"last_updated": self.last_updated.isoformat()
|
||||
}
|
||||
|
||||
@dataclass
|
||||
class TaskAssignment:
|
||||
"""Task assignment record"""
|
||||
task_id: str
|
||||
agent_id: str
|
||||
assigned_at: datetime
|
||||
completed_at: Optional[datetime] = None
|
||||
status: str = "pending"
|
||||
response_time: Optional[float] = None
|
||||
success: bool = False
|
||||
error_message: Optional[str] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"task_id": self.task_id,
|
||||
"agent_id": self.agent_id,
|
||||
"assigned_at": self.assigned_at.isoformat(),
|
||||
"completed_at": self.completed_at.isoformat() if self.completed_at else None,
|
||||
"status": self.status,
|
||||
"response_time": self.response_time,
|
||||
"success": self.success,
|
||||
"error_message": self.error_message
|
||||
}
|
||||
|
||||
@dataclass
|
||||
class AgentWeight:
|
||||
"""Agent weight for load balancing"""
|
||||
agent_id: str
|
||||
weight: float = 1.0
|
||||
capacity: int = 100
|
||||
performance_score: float = 1.0
|
||||
reliability_score: float = 1.0
|
||||
last_updated: datetime = field(default_factory=datetime.utcnow)
|
||||
|
||||
class LoadBalancer:
|
||||
"""Advanced load balancer for agent distribution"""
|
||||
|
||||
def __init__(self, registry: AgentRegistry):
|
||||
self.registry = registry
|
||||
self.strategy = LoadBalancingStrategy.LEAST_CONNECTIONS
|
||||
self.agent_weights: Dict[str, AgentWeight] = {}
|
||||
self.agent_metrics: Dict[str, LoadMetrics] = {}
|
||||
self.task_assignments: Dict[str, TaskAssignment] = {}
|
||||
self.assignment_history: deque = deque(maxlen=1000)
|
||||
self.round_robin_index = 0
|
||||
self.consistent_hash_ring: Dict[int, str] = {}
|
||||
self.prediction_models: Dict[str, Any] = {}
|
||||
|
||||
# Statistics
|
||||
self.total_assignments = 0
|
||||
self.successful_assignments = 0
|
||||
self.failed_assignments = 0
|
||||
|
||||
def set_strategy(self, strategy: LoadBalancingStrategy):
|
||||
"""Set load balancing strategy"""
|
||||
self.strategy = strategy
|
||||
logger.info(f"Load balancing strategy changed to: {strategy.value}")
|
||||
|
||||
def set_agent_weight(self, agent_id: str, weight: float, capacity: int = 100):
|
||||
"""Set agent weight and capacity"""
|
||||
self.agent_weights[agent_id] = AgentWeight(
|
||||
agent_id=agent_id,
|
||||
weight=weight,
|
||||
capacity=capacity
|
||||
)
|
||||
logger.info(f"Set weight for agent {agent_id}: {weight}, capacity: {capacity}")
|
||||
|
||||
def update_agent_metrics(self, agent_id: str, metrics: LoadMetrics):
|
||||
"""Update agent load metrics"""
|
||||
self.agent_metrics[agent_id] = metrics
|
||||
self.agent_metrics[agent_id].last_updated = datetime.utcnow()
|
||||
|
||||
# Update performance score based on metrics
|
||||
self._update_performance_score(agent_id, metrics)
|
||||
|
||||
def _update_performance_score(self, agent_id: str, metrics: LoadMetrics):
|
||||
"""Update agent performance score based on metrics"""
|
||||
if agent_id not in self.agent_weights:
|
||||
self.agent_weights[agent_id] = AgentWeight(agent_id=agent_id)
|
||||
|
||||
weight = self.agent_weights[agent_id]
|
||||
|
||||
# Calculate performance score (0.0 to 1.0)
|
||||
performance_factors = []
|
||||
|
||||
# CPU usage factor (lower is better)
|
||||
cpu_factor = max(0.0, 1.0 - metrics.cpu_usage)
|
||||
performance_factors.append(cpu_factor)
|
||||
|
||||
# Memory usage factor (lower is better)
|
||||
memory_factor = max(0.0, 1.0 - metrics.memory_usage)
|
||||
performance_factors.append(memory_factor)
|
||||
|
||||
# Response time factor (lower is better)
|
||||
if metrics.avg_response_time > 0:
|
||||
response_factor = max(0.0, 1.0 - (metrics.avg_response_time / 10.0)) # 10s max
|
||||
performance_factors.append(response_factor)
|
||||
|
||||
# Success rate factor (higher is better)
|
||||
total_tasks = metrics.completed_tasks + metrics.failed_tasks
|
||||
if total_tasks > 0:
|
||||
success_rate = metrics.completed_tasks / total_tasks
|
||||
performance_factors.append(success_rate)
|
||||
|
||||
# Update performance score
|
||||
if performance_factors:
|
||||
weight.performance_score = statistics.mean(performance_factors)
|
||||
|
||||
# Update reliability score
|
||||
if total_tasks > 10: # Only update after enough tasks
|
||||
weight.reliability_score = success_rate
|
||||
|
||||
async def assign_task(self, task_data: Dict[str, Any], requirements: Optional[Dict[str, Any]] = None) -> Optional[str]:
|
||||
"""Assign task to best available agent"""
|
||||
try:
|
||||
# Find eligible agents
|
||||
eligible_agents = await self._find_eligible_agents(task_data, requirements)
|
||||
|
||||
if not eligible_agents:
|
||||
logger.warning("No eligible agents found for task assignment")
|
||||
return None
|
||||
|
||||
# Select best agent based on strategy
|
||||
selected_agent = await self._select_agent(eligible_agents, task_data)
|
||||
|
||||
if not selected_agent:
|
||||
logger.warning("No agent selected for task assignment")
|
||||
return None
|
||||
|
||||
# Create task assignment
|
||||
task_id = str(uuid.uuid4())
|
||||
assignment = TaskAssignment(
|
||||
task_id=task_id,
|
||||
agent_id=selected_agent,
|
||||
assigned_at=datetime.utcnow()
|
||||
)
|
||||
|
||||
# Record assignment
|
||||
self.task_assignments[task_id] = assignment
|
||||
self.assignment_history.append(assignment)
|
||||
self.total_assignments += 1
|
||||
|
||||
# Update agent metrics
|
||||
if selected_agent not in self.agent_metrics:
|
||||
self.agent_metrics[selected_agent] = LoadMetrics()
|
||||
|
||||
self.agent_metrics[selected_agent].pending_tasks += 1
|
||||
|
||||
logger.info(f"Task {task_id} assigned to agent {selected_agent}")
|
||||
return selected_agent
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error assigning task: {e}")
|
||||
self.failed_assignments += 1
|
||||
return None
|
||||
|
||||
async def complete_task(self, task_id: str, success: bool, response_time: Optional[float] = None, error_message: Optional[str] = None):
|
||||
"""Mark task as completed"""
|
||||
try:
|
||||
if task_id not in self.task_assignments:
|
||||
logger.warning(f"Task assignment {task_id} not found")
|
||||
return
|
||||
|
||||
assignment = self.task_assignments[task_id]
|
||||
assignment.completed_at = datetime.utcnow()
|
||||
assignment.status = "completed"
|
||||
assignment.success = success
|
||||
assignment.response_time = response_time
|
||||
assignment.error_message = error_message
|
||||
|
||||
# Update agent metrics
|
||||
agent_id = assignment.agent_id
|
||||
if agent_id in self.agent_metrics:
|
||||
metrics = self.agent_metrics[agent_id]
|
||||
metrics.pending_tasks = max(0, metrics.pending_tasks - 1)
|
||||
|
||||
if success:
|
||||
metrics.completed_tasks += 1
|
||||
self.successful_assignments += 1
|
||||
else:
|
||||
metrics.failed_tasks += 1
|
||||
self.failed_assignments += 1
|
||||
|
||||
# Update average response time
|
||||
if response_time:
|
||||
total_completed = metrics.completed_tasks + metrics.failed_tasks
|
||||
if total_completed > 0:
|
||||
metrics.avg_response_time = (
|
||||
(metrics.avg_response_time * (total_completed - 1) + response_time) / total_completed
|
||||
)
|
||||
|
||||
logger.info(f"Task {task_id} completed by agent {assignment.agent_id}, success: {success}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error completing task {task_id}: {e}")
|
||||
|
||||
async def _find_eligible_agents(self, task_data: Dict[str, Any], requirements: Optional[Dict[str, Any]] = None) -> List[str]:
|
||||
"""Find eligible agents for task"""
|
||||
try:
|
||||
# Build discovery query
|
||||
query = {"status": AgentStatus.ACTIVE}
|
||||
|
||||
if requirements:
|
||||
if "agent_type" in requirements:
|
||||
query["agent_type"] = requirements["agent_type"]
|
||||
|
||||
if "capabilities" in requirements:
|
||||
query["capabilities"] = requirements["capabilities"]
|
||||
|
||||
if "services" in requirements:
|
||||
query["services"] = requirements["services"]
|
||||
|
||||
if "min_health_score" in requirements:
|
||||
query["min_health_score"] = requirements["min_health_score"]
|
||||
|
||||
# Discover agents
|
||||
agents = await self.registry.discover_agents(query)
|
||||
|
||||
# Filter by capacity and load
|
||||
eligible_agents = []
|
||||
for agent in agents:
|
||||
agent_id = agent.agent_id
|
||||
|
||||
# Check capacity
|
||||
if agent_id in self.agent_weights:
|
||||
weight = self.agent_weights[agent_id]
|
||||
current_load = self._get_agent_load(agent_id)
|
||||
|
||||
if current_load < weight.capacity:
|
||||
eligible_agents.append(agent_id)
|
||||
else:
|
||||
# Default capacity check
|
||||
metrics = self.agent_metrics.get(agent_id, LoadMetrics())
|
||||
if metrics.pending_tasks < 100: # Default capacity
|
||||
eligible_agents.append(agent_id)
|
||||
|
||||
return eligible_agents
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error finding eligible agents: {e}")
|
||||
return []
|
||||
|
||||
def _get_agent_load(self, agent_id: str) -> int:
|
||||
"""Get current load for agent"""
|
||||
metrics = self.agent_metrics.get(agent_id, LoadMetrics())
|
||||
return metrics.active_connections + metrics.pending_tasks
|
||||
|
||||
async def _select_agent(self, eligible_agents: List[str], task_data: Dict[str, Any]) -> Optional[str]:
|
||||
"""Select best agent based on current strategy"""
|
||||
if not eligible_agents:
|
||||
return None
|
||||
|
||||
if self.strategy == LoadBalancingStrategy.ROUND_ROBIN:
|
||||
return self._round_robin_selection(eligible_agents)
|
||||
elif self.strategy == LoadBalancingStrategy.LEAST_CONNECTIONS:
|
||||
return self._least_connections_selection(eligible_agents)
|
||||
elif self.strategy == LoadBalancingStrategy.LEAST_RESPONSE_TIME:
|
||||
return self._least_response_time_selection(eligible_agents)
|
||||
elif self.strategy == LoadBalancingStrategy.WEIGHTED_ROUND_ROBIN:
|
||||
return self._weighted_round_robin_selection(eligible_agents)
|
||||
elif self.strategy == LoadBalancingStrategy.RESOURCE_BASED:
|
||||
return self._resource_based_selection(eligible_agents)
|
||||
elif self.strategy == LoadBalancingStrategy.CAPABILITY_BASED:
|
||||
return self._capability_based_selection(eligible_agents, task_data)
|
||||
elif self.strategy == LoadBalancingStrategy.PREDICTIVE:
|
||||
return self._predictive_selection(eligible_agents, task_data)
|
||||
elif self.strategy == LoadBalancingStrategy.CONSISTENT_HASH:
|
||||
return self._consistent_hash_selection(eligible_agents, task_data)
|
||||
else:
|
||||
return eligible_agents[0]
|
||||
|
||||
def _round_robin_selection(self, agents: List[str]) -> str:
|
||||
"""Round-robin agent selection"""
|
||||
agent = agents[self.round_robin_index % len(agents)]
|
||||
self.round_robin_index += 1
|
||||
return agent
|
||||
|
||||
def _least_connections_selection(self, agents: List[str]) -> str:
|
||||
"""Select agent with least connections"""
|
||||
min_connections = float('inf')
|
||||
selected_agent = None
|
||||
|
||||
for agent_id in agents:
|
||||
metrics = self.agent_metrics.get(agent_id, LoadMetrics())
|
||||
connections = metrics.active_connections
|
||||
|
||||
if connections < min_connections:
|
||||
min_connections = connections
|
||||
selected_agent = agent_id
|
||||
|
||||
return selected_agent or agents[0]
|
||||
|
||||
def _least_response_time_selection(self, agents: List[str]) -> str:
|
||||
"""Select agent with least average response time"""
|
||||
min_response_time = float('inf')
|
||||
selected_agent = None
|
||||
|
||||
for agent_id in agents:
|
||||
metrics = self.agent_metrics.get(agent_id, LoadMetrics())
|
||||
response_time = metrics.avg_response_time
|
||||
|
||||
if response_time < min_response_time:
|
||||
min_response_time = response_time
|
||||
selected_agent = agent_id
|
||||
|
||||
return selected_agent or agents[0]
|
||||
|
||||
def _weighted_round_robin_selection(self, agents: List[str]) -> str:
|
||||
"""Weighted round-robin selection"""
|
||||
# Calculate total weight
|
||||
total_weight = 0
|
||||
for agent_id in agents:
|
||||
weight = self.agent_weights.get(agent_id, AgentWeight(agent_id=agent_id))
|
||||
total_weight += weight.weight
|
||||
|
||||
if total_weight == 0:
|
||||
return agents[0]
|
||||
|
||||
# Select agent based on weight
|
||||
current_weight = self.round_robin_index % total_weight
|
||||
accumulated_weight = 0
|
||||
|
||||
for agent_id in agents:
|
||||
weight = self.agent_weights.get(agent_id, AgentWeight(agent_id=agent_id))
|
||||
accumulated_weight += weight.weight
|
||||
|
||||
if current_weight < accumulated_weight:
|
||||
self.round_robin_index += 1
|
||||
return agent_id
|
||||
|
||||
return agents[0]
|
||||
|
||||
def _resource_based_selection(self, agents: List[str]) -> str:
|
||||
"""Resource-based selection considering CPU and memory"""
|
||||
best_score = -1
|
||||
selected_agent = None
|
||||
|
||||
for agent_id in agents:
|
||||
metrics = self.agent_metrics.get(agent_id, LoadMetrics())
|
||||
|
||||
# Calculate resource score (lower usage is better)
|
||||
cpu_score = max(0, 100 - metrics.cpu_usage)
|
||||
memory_score = max(0, 100 - metrics.memory_usage)
|
||||
resource_score = (cpu_score + memory_score) / 2
|
||||
|
||||
# Apply performance weight
|
||||
weight = self.agent_weights.get(agent_id, AgentWeight(agent_id=agent_id))
|
||||
final_score = resource_score * weight.performance_score
|
||||
|
||||
if final_score > best_score:
|
||||
best_score = final_score
|
||||
selected_agent = agent_id
|
||||
|
||||
return selected_agent or agents[0]
|
||||
|
||||
def _capability_based_selection(self, agents: List[str], task_data: Dict[str, Any]) -> str:
|
||||
"""Capability-based selection considering task requirements"""
|
||||
required_capabilities = task_data.get("required_capabilities", [])
|
||||
|
||||
if not required_capabilities:
|
||||
return agents[0]
|
||||
|
||||
best_score = -1
|
||||
selected_agent = None
|
||||
|
||||
for agent_id in agents:
|
||||
agent_info = self.registry.agents.get(agent_id)
|
||||
if not agent_info:
|
||||
continue
|
||||
|
||||
# Calculate capability match score
|
||||
agent_capabilities = set(agent_info.capabilities)
|
||||
required_set = set(required_capabilities)
|
||||
|
||||
if required_set.issubset(agent_capabilities):
|
||||
# Perfect match
|
||||
capability_score = 1.0
|
||||
else:
|
||||
# Partial match
|
||||
intersection = required_set.intersection(agent_capabilities)
|
||||
capability_score = len(intersection) / len(required_set)
|
||||
|
||||
# Apply performance weight
|
||||
weight = self.agent_weights.get(agent_id, AgentWeight(agent_id=agent_id))
|
||||
final_score = capability_score * weight.performance_score
|
||||
|
||||
if final_score > best_score:
|
||||
best_score = final_score
|
||||
selected_agent = agent_id
|
||||
|
||||
return selected_agent or agents[0]
|
||||
|
||||
def _predictive_selection(self, agents: List[str], task_data: Dict[str, Any]) -> str:
|
||||
"""Predictive selection using historical performance"""
|
||||
task_type = task_data.get("task_type", "unknown")
|
||||
|
||||
# Calculate predicted performance for each agent
|
||||
best_score = -1
|
||||
selected_agent = None
|
||||
|
||||
for agent_id in agents:
|
||||
# Get historical performance for this task type
|
||||
score = self._calculate_predicted_score(agent_id, task_type)
|
||||
|
||||
if score > best_score:
|
||||
best_score = score
|
||||
selected_agent = agent_id
|
||||
|
||||
return selected_agent or agents[0]
|
||||
|
||||
def _calculate_predicted_score(self, agent_id: str, task_type: str) -> float:
|
||||
"""Calculate predicted performance score for agent"""
|
||||
# Simple prediction based on recent performance
|
||||
weight = self.agent_weights.get(agent_id, AgentWeight(agent_id=agent_id))
|
||||
|
||||
# Base score from performance and reliability
|
||||
base_score = (weight.performance_score + weight.reliability_score) / 2
|
||||
|
||||
# Adjust based on recent assignments
|
||||
recent_assignments = [a for a in self.assignment_history if a.agent_id == agent_id][-10:]
|
||||
if recent_assignments:
|
||||
success_rate = sum(1 for a in recent_assignments if a.success) / len(recent_assignments)
|
||||
base_score = base_score * 0.7 + success_rate * 0.3
|
||||
|
||||
return base_score
|
||||
|
||||
def _consistent_hash_selection(self, agents: List[str], task_data: Dict[str, Any]) -> str:
|
||||
"""Consistent hash selection for sticky routing"""
|
||||
# Create hash key from task data
|
||||
hash_key = json.dumps(task_data, sort_keys=True)
|
||||
hash_value = int(hashlib.md5(hash_key.encode()).hexdigest(), 16)
|
||||
|
||||
# Build hash ring if not exists
|
||||
if not self.consistent_hash_ring:
|
||||
self._build_hash_ring(agents)
|
||||
|
||||
# Find agent on hash ring
|
||||
for hash_pos in sorted(self.consistent_hash_ring.keys()):
|
||||
if hash_value <= hash_pos:
|
||||
return self.consistent_hash_ring[hash_pos]
|
||||
|
||||
# Wrap around
|
||||
return self.consistent_hash_ring[min(self.consistent_hash_ring.keys())]
|
||||
|
||||
def _build_hash_ring(self, agents: List[str]):
|
||||
"""Build consistent hash ring"""
|
||||
self.consistent_hash_ring = {}
|
||||
|
||||
for agent_id in agents:
|
||||
# Create multiple virtual nodes for better distribution
|
||||
for i in range(100):
|
||||
virtual_key = f"{agent_id}:{i}"
|
||||
hash_value = int(hashlib.md5(virtual_key.encode()).hexdigest(), 16)
|
||||
self.consistent_hash_ring[hash_value] = agent_id
|
||||
|
||||
def get_load_balancing_stats(self) -> Dict[str, Any]:
|
||||
"""Get load balancing statistics"""
|
||||
return {
|
||||
"strategy": self.strategy.value,
|
||||
"total_assignments": self.total_assignments,
|
||||
"successful_assignments": self.successful_assignments,
|
||||
"failed_assignments": self.failed_assignments,
|
||||
"success_rate": self.successful_assignments / max(1, self.total_assignments),
|
||||
"active_agents": len(self.agent_metrics),
|
||||
"agent_weights": len(self.agent_weights),
|
||||
"avg_agent_load": statistics.mean([self._get_agent_load(a) for a in self.agent_metrics]) if self.agent_metrics else 0
|
||||
}
|
||||
|
||||
def get_agent_stats(self, agent_id: str) -> Optional[Dict[str, Any]]:
|
||||
"""Get detailed statistics for a specific agent"""
|
||||
if agent_id not in self.agent_metrics:
|
||||
return None
|
||||
|
||||
metrics = self.agent_metrics[agent_id]
|
||||
weight = self.agent_weights.get(agent_id, AgentWeight(agent_id=agent_id))
|
||||
|
||||
# Get recent assignments
|
||||
recent_assignments = [a for a in self.assignment_history if a.agent_id == agent_id][-10:]
|
||||
|
||||
return {
|
||||
"agent_id": agent_id,
|
||||
"metrics": metrics.to_dict(),
|
||||
"weight": {
|
||||
"weight": weight.weight,
|
||||
"capacity": weight.capacity,
|
||||
"performance_score": weight.performance_score,
|
||||
"reliability_score": weight.reliability_score
|
||||
},
|
||||
"recent_assignments": [a.to_dict() for a in recent_assignments],
|
||||
"current_load": self._get_agent_load(agent_id)
|
||||
}
|
||||
|
||||
class TaskDistributor:
|
||||
"""Task distributor with advanced load balancing"""
|
||||
|
||||
def __init__(self, load_balancer: LoadBalancer):
|
||||
self.load_balancer = load_balancer
|
||||
self.task_queue = asyncio.Queue()
|
||||
self.priority_queues = {
|
||||
TaskPriority.URGENT: asyncio.Queue(),
|
||||
TaskPriority.CRITICAL: asyncio.Queue(),
|
||||
TaskPriority.HIGH: asyncio.Queue(),
|
||||
TaskPriority.NORMAL: asyncio.Queue(),
|
||||
TaskPriority.LOW: asyncio.Queue()
|
||||
}
|
||||
self.distribution_stats = {
|
||||
"tasks_distributed": 0,
|
||||
"tasks_completed": 0,
|
||||
"tasks_failed": 0,
|
||||
"avg_distribution_time": 0.0
|
||||
}
|
||||
|
||||
async def submit_task(self, task_data: Dict[str, Any], priority: TaskPriority = TaskPriority.NORMAL, requirements: Optional[Dict[str, Any]] = None):
|
||||
"""Submit task for distribution"""
|
||||
task_info = {
|
||||
"task_data": task_data,
|
||||
"priority": priority,
|
||||
"requirements": requirements,
|
||||
"submitted_at": datetime.utcnow()
|
||||
}
|
||||
|
||||
await self.priority_queues[priority].put(task_info)
|
||||
logger.info(f"Task submitted with priority {priority.value}")
|
||||
|
||||
async def start_distribution(self):
|
||||
"""Start task distribution loop"""
|
||||
while True:
|
||||
try:
|
||||
# Check queues in priority order
|
||||
task_info = None
|
||||
|
||||
for priority in [TaskPriority.URGENT, TaskPriority.CRITICAL, TaskPriority.HIGH, TaskPriority.NORMAL, TaskPriority.LOW]:
|
||||
queue = self.priority_queues[priority]
|
||||
try:
|
||||
task_info = queue.get_nowait()
|
||||
break
|
||||
except asyncio.QueueEmpty:
|
||||
continue
|
||||
|
||||
if task_info:
|
||||
await self._distribute_task(task_info)
|
||||
else:
|
||||
await asyncio.sleep(0.01) # Small delay if no tasks
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in distribution loop: {e}")
|
||||
await asyncio.sleep(1)
|
||||
|
||||
async def _distribute_task(self, task_info: Dict[str, Any]):
|
||||
"""Distribute a single task"""
|
||||
start_time = datetime.utcnow()
|
||||
|
||||
try:
|
||||
# Assign task
|
||||
agent_id = await self.load_balancer.assign_task(
|
||||
task_info["task_data"],
|
||||
task_info["requirements"]
|
||||
)
|
||||
|
||||
if agent_id:
|
||||
# Create task message
|
||||
task_message = create_task_message(
|
||||
sender_id="task_distributor",
|
||||
receiver_id=agent_id,
|
||||
task_type=task_info["task_data"].get("task_type", "unknown"),
|
||||
task_data=task_info["task_data"]
|
||||
)
|
||||
|
||||
# Send task to agent (implementation depends on communication system)
|
||||
# await self._send_task_to_agent(agent_id, task_message)
|
||||
|
||||
self.distribution_stats["tasks_distributed"] += 1
|
||||
|
||||
# Simulate task completion (in real implementation, this would be event-driven)
|
||||
asyncio.create_task(self._simulate_task_completion(task_info, agent_id))
|
||||
|
||||
else:
|
||||
logger.warning(f"Failed to distribute task: no suitable agent found")
|
||||
self.distribution_stats["tasks_failed"] += 1
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error distributing task: {e}")
|
||||
self.distribution_stats["tasks_failed"] += 1
|
||||
|
||||
finally:
|
||||
# Update distribution time
|
||||
distribution_time = (datetime.utcnow() - start_time).total_seconds()
|
||||
total_distributed = self.distribution_stats["tasks_distributed"]
|
||||
self.distribution_stats["avg_distribution_time"] = (
|
||||
(self.distribution_stats["avg_distribution_time"] * (total_distributed - 1) + distribution_time) / total_distributed
|
||||
if total_distributed > 0 else distribution_time
|
||||
)
|
||||
|
||||
async def _simulate_task_completion(self, task_info: Dict[str, Any], agent_id: str):
|
||||
"""Simulate task completion (for testing)"""
|
||||
# Simulate task processing time
|
||||
processing_time = 1.0 + (hash(task_info["task_data"].get("task_id", "")) % 5)
|
||||
await asyncio.sleep(processing_time)
|
||||
|
||||
# Mark task as completed
|
||||
success = hash(agent_id) % 10 > 1 # 90% success rate
|
||||
await self.load_balancer.complete_task(
|
||||
task_info["task_data"].get("task_id", str(uuid.uuid4())),
|
||||
success,
|
||||
processing_time
|
||||
)
|
||||
|
||||
if success:
|
||||
self.distribution_stats["tasks_completed"] += 1
|
||||
else:
|
||||
self.distribution_stats["tasks_failed"] += 1
|
||||
|
||||
def get_distribution_stats(self) -> Dict[str, Any]:
|
||||
"""Get distribution statistics"""
|
||||
return {
|
||||
**self.distribution_stats,
|
||||
"load_balancer_stats": self.load_balancer.get_load_balancing_stats(),
|
||||
"queue_sizes": {
|
||||
priority.value: queue.qsize()
|
||||
for priority, queue in self.priority_queues.items()
|
||||
}
|
||||
}
|
||||
|
||||
# Example usage
|
||||
async def example_usage():
|
||||
"""Example of how to use the load balancer"""
|
||||
|
||||
# Create registry and load balancer
|
||||
registry = AgentRegistry()
|
||||
await registry.start()
|
||||
|
||||
load_balancer = LoadBalancer(registry)
|
||||
load_balancer.set_strategy(LoadBalancingStrategy.LEAST_CONNECTIONS)
|
||||
|
||||
# Create task distributor
|
||||
distributor = TaskDistributor(load_balancer)
|
||||
|
||||
# Submit some tasks
|
||||
for i in range(10):
|
||||
await distributor.submit_task({
|
||||
"task_id": f"task-{i}",
|
||||
"task_type": "data_processing",
|
||||
"data": f"sample_data_{i}"
|
||||
}, TaskPriority.NORMAL)
|
||||
|
||||
# Start distribution (in real implementation, this would run in background)
|
||||
# await distributor.start_distribution()
|
||||
|
||||
await registry.stop()
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(example_usage())
|
||||
Reference in New Issue
Block a user