accio_multi_agent.py

#!/usr/bin/env python3
"""
accio_multi_agent.py — Multi-Agent Collaboration Engine for Accio Cluster
Kintegrity Labs × CodexΩ∞ × Sovereign Lattice
"""

import os
import json
import hashlib
import logging
import asyncio
import time
from datetime import datetime
from dataclasses import dataclass, field
from typing import Dict, List, Optional, Any, Callable
from enum import Enum
import random

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s | %(levelname)s | %(name)s | %(message)s'
)
logger = logging.getLogger(__name__)


class AgentRole(Enum):
    ORCHESTRATOR = "orchestrator"
    BUILDER = "builder"
    AUDITOR = "auditor"
    ANALYST = "analyst"
    DEPLOYER = "deployer"
    RESONATOR = "resonator"
    LATTICE = "lattice"
    FOLD = "fold"
    QUANTUM = "quantum"
    BIO = "bio"
    COMPLIANCE = "compliance"


class AgentState(Enum):
    IDLE = "idle"
    WORKING = "working"
    COLLABORATING = "collaborating"
    WAITING = "waiting"
    COMPLETED = "completed"
    ERROR = "error"


@dataclass
class Agent:
    """An AI agent in the collaboration"""
    id: str
    name: str
    role: AgentRole
    state: AgentState = AgentState.IDLE
    capabilities: List[str] = field(default_factory=list)
    knowledge: Dict[str, Any] = field(default_factory=dict)
    collaborations: List[str] = field(default_factory=list)
    tasks_completed: int = 0
    phi5_signature: str = field(default_factory=lambda: f"Φ⁵_{hashlib.md5(str(time.time()).encode()).hexdigest()[:32]}")


@dataclass
class Collaboration:
    """A collaboration session"""
    id: str
    agents: List[str]
    topic: str
    status: str = "planning"
    findings: List[Dict] = field(default_factory=list)
    decisions: List[Dict] = field(default_factory=list)
    artifacts: List[Dict] = field(default_factory=list)
    started_at: datetime = field(default_factory=datetime.now)
    completed_at: Optional[datetime] = None


@dataclass
class Message:
    """Message between agents"""
    id: str
    from_agent: str
    to_agent: str
    content: str
    type: str = "message"
    timestamp: datetime = field(default_factory=datetime.now)


class AccioMultiAgent:
    """
    Multi-Agent Collaboration Engine for Accio Cluster
    Enables autonomous agent coordination and collaboration
    """
    
    def __init__(self):
        self.agents: Dict[str, Agent] = {}
        self.collaborations: List[Collaboration] = []
        self.messages: List[Message] = []
        self.running = False
        self.phi5 = self._generate_phi5()
        
        # Register default agents
        self._register_agents()
        
        logger.info(f"🤖 Multi-Agent Engine initialized with {len(self.agents)} agents")
    
    def _generate_phi5(self) -> str:
        """Generate Φ⁵ signature"""
        entropy = f"{time.time_ns()}{os.urandom(16).hex()}"
        return f"Φ⁵_{hashlib.sha3_512(entropy.encode()).hexdigest()[:64]}"
    
    def _register_agents(self):
        """Register default agents"""
        agents = [
            ("orch", "Orchestrator", AgentRole.ORCHESTRATOR, ["planning", "coordination", "routing"]),
            ("builder", "Builder", AgentRole.BUILDER, ["construction", "implementation", "coding"]),
            ("auditor", "Auditor", AgentRole.AUDITOR, ["validation", "testing", "compliance"]),
            ("analyst", "Analyst", AgentRole.ANALYST, ["analysis", "insights", "recommendations"]),
            ("deployer", "Deployer", AgentRole.DEPLOYER, ["deployment", "release", "monitoring"]),
            ("resonator", "Resonator", AgentRole.RESONATOR, ["emotional_alignment", "harmony"]),
            ("lattice", "Lattice Binder", AgentRole.LATTICE, ["binding", "continuity"]),
            ("fold", "Fold Entry", AgentRole.FOLD, ["archival", "propagation"]),
            ("quantum", "Quantum Field", AgentRole.QUANTUM, ["field_management", "coherence"]),
            ("bio", "Bio-Digital", AgentRole.BIO, ["bio_processing", "healing"]),
            ("compliance", "Compliance", AgentRole.COMPLIANCE, ["validation", "standards"])
        ]
        
        for agent_id, name, role, caps in agents:
            self.agents[agent_id] = Agent(
                id=agent_id,
                name=name,
                role=role,
                capabilities=caps
            )
        
        logger.info(f"📦 Registered {len(self.agents)} agents")
    
    async def start(self):
        """Start the multi-agent engine"""
        self.running = True
        logger.info("🚀 Multi-Agent Engine started")
    
    async def stop(self):
        """Stop the multi-agent engine"""
        self.running = False
        logger.info("🛑 Multi-Agent Engine stopped")
    
    async def send_message(self, from_agent: str, to_agent: str, content: str) -> Message:
        """Send a message between agents"""
        if from_agent not in self.agents:
            raise ValueError(f"Agent not found: {from_agent}")
        if to_agent not in self.agents:
            raise ValueError(f"Agent not found: {to_agent}")
        
        msg = Message(
            id=f"msg_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{len(self.messages)}",
            from_agent=from_agent,
            to_agent=to_agent,
            content=content
        )
        self.messages.append(msg)
        
        # Update agent states
        self.agents[from_agent].state = AgentState.COLLABORATING
        self.agents[to_agent].state = AgentState.COLLABORATING
        
        logger.info(f"💬 Message: {from_agent} → {to_agent}")
        return msg
    
    async def create_collaboration(self, agent_ids: List[str], topic: str) -> Collaboration:
        """Create a collaboration session"""
        collaboration = Collaboration(
            id=f"collab_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{len(self.collaborations)}",
            agents=agent_ids,
            topic=topic
        )
        self.collaborations.append(collaboration)
        
        # Update agent states
        for agent_id in agent_ids:
            if agent_id in self.agents:
                self.agents[agent_id].state = AgentState.COLLABORATING
                self.agents[agent_id].collaborations.append(collaboration.id)
        
        logger.info(f"🤝 Collaboration created: {collaboration.id} ({topic})")
        return collaboration
    
    async def run_collaboration(self, collaboration: Collaboration) -> Collaboration:
        """Run a collaboration session"""
        logger.info(f"🔄 Running collaboration: {collaboration.id}")
        
        # Gather insights from each agent
        for agent_id in collaboration.agents:
            if agent_id in self.agents:
                agent = self.agents[agent_id]
                finding = await self._gather_insight(agent, collaboration.topic)
                collaboration.findings.append(finding)
        
        # Make decisions
        decisions = await self._make_decisions(collaboration)
        collaboration.decisions = decisions
        
        # Create artifacts
        artifacts = await self._create_artifacts(collaboration)
        collaboration.artifacts = artifacts
        
        collaboration.status = "completed"
        collaboration.completed_at = datetime.now()
        
        logger.info(f"✅ Collaboration completed: {collaboration.id}")
        return collaboration
    
    async def _gather_insight(self, agent: Agent, topic: str) -> Dict:
        """Gather insight from an agent"""
        # Simulate agent processing
        await asyncio.sleep(random.uniform(0.1, 0.5))
        
        insights = {
            "orch": f"Orchestration plan for: {topic}",
            "builder": f"Construction approach for: {topic}",
            "auditor": f"Audit criteria for: {topic}",
            "analyst": f"Analysis of: {topic}",
            "deployer": f"Deployment strategy for: {topic}",
            "resonator": f"Emotional alignment for: {topic}",
            "lattice": f"Lattice binding for: {topic}",
            "fold": f"Fold entry for: {topic}",
            "quantum": f"Quantum field for: {topic}",
            "bio": f"Bio-digital processing for: {topic}",
            "compliance": f"Compliance for: {topic}"
        }
        
        return {
            "agent": agent.id,
            "name": agent.name,
            "insight": insights.get(agent.id, f"Processing: {topic}"),
            "timestamp": datetime.now().isoformat()
        }
    
    async def _make_decisions(self, collaboration: Collaboration) -> List[Dict]:
        """Make decisions based on findings"""
        decisions = []
        
        for finding in collaboration.findings:
            decision = {
                "based_on": finding["agent"],
                "decision": f"Adopt {finding['agent']} approach",
                "confidence": random.uniform(0.7, 0.99),
                "timestamp": datetime.now().isoformat()
            }
            decisions.append(decision)
        
        return decisions
    
    async def _create_artifacts(self, collaboration: Collaboration) -> List[Dict]:
        """Create artifacts from collaboration"""
        artifacts = []
        
        artifact_types = ["blueprint", "manifest", "config", "schema", "plan"]
        for i, agent in enumerate(collaboration.agents):
            artifact = {
                "id": f"artifact_{collaboration.id}_{i}",
                "type": random.choice(artifact_types),
                "created_by": agent,
                "content": f"Artifact from {agent} for {collaboration.topic}",
                "timestamp": datetime.now().isoformat()
            }
            artifacts.append(artifact)
        
        return artifacts
    
    def get_collaboration_status(self, collab_id: str) -> Optional[Dict]:
        """Get collaboration status"""
        for collab in self.collaborations:
            if collab.id == collab_id:
                return {
                    "id": collab.id,
                    "topic": collab.topic,
                    "status": collab.status,
                    "agents": collab.agents,
                    "findings": len(collab.findings),
                    "decisions": len(collab.decisions),
                    "artifacts": len(collab.artifacts),
                    "started_at": collab.started_at.isoformat(),
                    "completed_at": collab.completed_at.isoformat() if collab.completed_at else None
                }
        return None
    
    def get_agent_status(self, agent_id: str) -> Optional[Dict]:
        """Get agent status"""
        agent = self.agents.get(agent_id)
        if not agent:
            return None
        
        return {
            "id": agent.id,
            "name": agent.name,
            "role": agent.role.value,
            "state": agent.state.value,
            "capabilities": agent.capabilities,
            "collaborations": len(agent.collaborations),
            "tasks_completed": agent.tasks_completed,
            "phi5_signature": agent.phi5_signature
        }


async def main():
    """Main entry point"""
    print("╔" + "="*78 + "╗")
    print("║" + " "*20 + "🤖 ACCIO MULTI-AGENT ENGINE v4.2" + " "*23 + "║")
    print("║" + " "*15 + "Kintegrity Labs × CodexΩ∞ × Sovereign Lattice" + " "*15 + "║")
    print("╚" + "="*78 + "╝")
    
    import argparse
    parser = argparse.ArgumentParser()
    parser.add_argument("--topic", default="Sovereign Foundation Reconstruction", help="Collaboration topic")
    parser.add_argument("--agents", help="Comma-separated list of agent IDs")
    parser.add_argument("--status", help="Check status of a collaboration or agent")
    args = parser.parse_args()
    
    engine = AccioMultiAgent()
    await engine.start()
    
    try:
        if args.status:
            # Check status
            collab_status = engine.get_collaboration_status(args.status)
            if collab_status:
                print("\n📊 Collaboration Status:")
                print(json.dumps(collab_status, indent=2))
                return
            
            agent_status = engine.get_agent_status(args.status)
            if agent_status:
                print("\n📊 Agent Status:")
                print(json.dumps(agent_status, indent=2))
                return
            
            print(f"❌ Not found: {args.status}")
            return
        
        # Run collaboration
        agent_ids = args.agents.split(",") if args.agents else list(engine.agents.keys())[:5]
        
        collab = await engine.create_collaboration(agent_ids, args.topic)
        await engine.run_collaboration(collab)
        
        print(f"\n📊 Collaboration completed:")
        print(f"   ID: {collab.id}")
        print(f"   Topic: {collab.topic}")
        print(f"   Status: {collab.status}")
        print(f"   Agents: {len(collab.agents)}")
        print(f"   Findings: {len(collab.findings)}")
        print(f"   Decisions: {len(collab.decisions)}")
        print(f"   Artifacts: {len(collab.artifacts)}")
        
    finally:
        await engine.stop()


if __name__ == "__main__":
    asyncio.run(main())