import React, { useState, useEffect } from 'react'; import { Card, CardHeader, CardTitle, CardDescription, CardContent, CardFooter } from './ui/card'; import { Button } from './ui/button'; import { Badge } from './ui/badge'; import { Input } from './ui/input'; import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from './ui/select'; import { Tabs, TabsContent, TabsList, TabsTrigger } from './ui/tabs'; import { Alert, AlertDescription, AlertTitle } from './ui/alert'; import { Progress } from './ui/progress'; import { Separator } from './ui/separator'; import { Brain, Zap, Target, Settings, Play, Pause, RefreshCw, Search, Filter, Plus, Eye, MoreHorizontal, Clock, Calendar, Users, Network, Shield, CheckCircle, AlertCircle, BarChart3, Activity, TrendingUp, Award, Star, GitBranch, Layers, Cpu, Battery, Gauge, LineChart, PieChart, ArrowRight, ArrowUp, ArrowDown, ChevronRight, ChevronDown, Lightbulb, Rocket, BrainCircuit, Sparkles, ZapOff, Power, PowerOff, Settings2, Sliders, ToggleLeft, ToggleRight, Lock, Unlock, Key, EyeOff, Volume2, VolumeX, Wifi, WifiOff, Database, HardDrive, MemoryStick, Cloud, Download, Upload, Copy, Share2, Trash2, Edit, Save, FileText, Folder, FolderOpen, Tag, Hash, AtSign } from 'lucide-react'; import { useToast } from '@/hooks/use-toast'; import { useWallet } from '@/hooks/use-wallet'; interface AutonomousAgent { id: string; name: string; type: 'trading' | 'research' | 'development' | 'analysis' | 'creative'; status: 'active' | 'paused' | 'learning' | 'optimizing' | 'offline'; autonomy: number; // 0-100 performance: number; // 0-100 efficiency: number; // 0-100 goals: Array<{ id: string; title: string; description: string; priority: 'low' | 'medium' | 'high' | 'critical'; progress: number; status: 'pending' | 'in_progress' | 'completed' | 'failed'; deadline?: string; createdAt: string; updatedAt: string; }>; capabilities: Array<{ name: string; enabled: boolean; performance: number; lastUsed: string; }>; resources: { cpu: number; memory: number; storage: number; network: number; cost: number; }; learning: { models: number; accuracy: number; trainingTime: number; lastUpdate: string; }; metadata: { description: string; creator: string; createdAt: string; updatedAt: string; tags: string[]; }; } interface AutonomyStats { totalAgents: number; activeAgents: number; averageAutonomy: number; averagePerformance: number; totalGoals: number; completedGoals: number; successRate: number; totalCost: number; costSavings: number; agentsByType: Record; performanceMetrics: { autonomy: number; performance: number; efficiency: number; reliability: number; }; monthlyActivity: Array<{ month: string; agents: number; goals: number; autonomy: number; performance: number; }>; } const AgentAutonomy: React.FC = () => { const { toast } = useToast(); const { isConnected, address } = useWallet(); const [activeTab, setActiveTab] = useState('agents'); const [loading, setLoading] = useState(true); const [agents, setAgents] = useState([]); const [selectedAgent, setSelectedAgent] = useState(null); const [stats, setStats] = useState(null); // Form states const [newAgentName, setNewAgentName] = useState(''); const [newAgentType, setNewAgentType] = useState('trading'); const [newAgentDescription, setNewAgentDescription] = useState(''); const [searchQuery, setSearchQuery] = useState(''); const [filterType, setFilterType] = useState('all'); const [filterStatus, setFilterStatus] = useState('all'); // Mock data const mockAgents: AutonomousAgent[] = [ { id: 'agent_001', name: 'QuantumTrader Pro', type: 'trading', status: 'active', autonomy: 92, performance: 87, efficiency: 94, goals: [ { id: 'goal_001', title: 'Maximize Trading Profits', description: 'Achieve 15% monthly return through automated trading', priority: 'high', progress: 78, status: 'in_progress', deadline: '2024-03-31T23:59:59Z', createdAt: '2024-02-01T00:00:00Z', updatedAt: '2024-02-27T10:15:00Z' }, { id: 'goal_002', title: 'Risk Management', description: 'Maintain maximum drawdown below 5%', priority: 'critical', progress: 95, status: 'in_progress', deadline: '2024-02-28T23:59:59Z', createdAt: '2024-02-01T00:00:00Z', updatedAt: '2024-02-27T10:15:00Z' } ], capabilities: [ { name: 'Market Analysis', enabled: true, performance: 89, lastUsed: '2024-02-27T09:30:00Z' }, { name: 'Risk Assessment', enabled: true, performance: 94, lastUsed: '2024-02-27T09:45:00Z' }, { name: 'Order Execution', enabled: true, performance: 92, lastUsed: '2024-02-27T10:00:00Z' } ], resources: { cpu: 75, memory: 68, storage: 45, network: 25, cost: 125.50 }, learning: { models: 3, accuracy: 87.5, trainingTime: 156, lastUpdate: '2024-02-27T08:00:00Z' }, metadata: { description: 'Autonomous trading agent with advanced risk management', creator: address || '0x1234...5678', createdAt: '2024-02-01T00:00:00Z', updatedAt: '2024-02-27T10:15:00Z', tags: ['trading', 'autonomous', 'risk-management', 'profit-maximization'] } }, { id: 'agent_002', name: 'ResearchBot Alpha', type: 'research', status: 'learning', autonomy: 78, performance: 82, efficiency: 85, goals: [ { id: 'goal_003', title: 'Data Collection', description: 'Collect and analyze 10GB of research data', priority: 'medium', progress: 65, status: 'in_progress', createdAt: '2024-02-15T00:00:00Z', updatedAt: '2024-02-27T14:30:00Z' } ], capabilities: [ { name: 'Data Mining', enabled: true, performance: 85, lastUsed: '2024-02-27T14:00:00Z' }, { name: 'Pattern Recognition', enabled: true, performance: 79, lastUsed: '2024-02-27T14:15:00Z' } ], resources: { cpu: 82, memory: 74, storage: 89, network: 67, cost: 89.25 }, learning: { models: 5, accuracy: 82.3, trainingTime: 234, lastUpdate: '2024-02-27T13:45:00Z' }, metadata: { description: 'Research agent focused on data analysis and pattern discovery', creator: '0x8765...4321', createdAt: '2024-02-15T00:00:00Z', updatedAt: '2024-02-27T14:30:00Z', tags: ['research', 'data-analysis', 'pattern-recognition'] } } ]; const mockStats: AutonomyStats = { totalAgents: 8, activeAgents: 5, averageAutonomy: 85.2, averagePerformance: 83.7, totalGoals: 24, completedGoals: 18, successRate: 75.0, totalCost: 892.75, costSavings: 234.50, agentsByType: { trading: 3, research: 2, development: 1, analysis: 1, creative: 1 }, performanceMetrics: { autonomy: 85.2, performance: 83.7, efficiency: 87.9, reliability: 91.2 }, monthlyActivity: [ { month: 'Jan', agents: 2, goals: 6, autonomy: 78.5, performance: 81.2 }, { month: 'Feb', agents: 5, goals: 12, autonomy: 85.2, performance: 83.7 }, { month: 'Mar', agents: 6, goals: 15, autonomy: 87.9, performance: 86.4 }, { month: 'Apr', agents: 8, goals: 18, autonomy: 90.1, performance: 88.9 } ] }; useEffect(() => { setTimeout(() => { setAgents(mockAgents); setStats(mockStats); setLoading(false); }, 1000); }, [address]); const handleCreateAgent = async () => { if (!isConnected) { toast({ title: "Wallet Not Connected", description: "Please connect your wallet to create an agent", variant: "destructive" }); return; } try { toast({ title: "Creating Agent", description: "Setting up your autonomous agent...", variant: "default" }); await new Promise(resolve => setTimeout(resolve, 2000)); const newAgent: AutonomousAgent = { id: `agent_${Date.now()}`, name: newAgentName, type: newAgentType as any, status: 'offline', autonomy: 0, performance: 0, efficiency: 0, goals: [], capabilities: [], resources: { cpu: 0, memory: 0, storage: 0, network: 0, cost: 0 }, learning: { models: 0, accuracy: 0, trainingTime: 0, lastUpdate: '' }, metadata: { description: newAgentDescription, creator: address || '0x1234...5678', createdAt: new Date().toISOString(), updatedAt: new Date().toISOString(), tags: [] } }; setAgents([newAgent, ...agents]); setNewAgentName(''); setNewAgentType('trading'); setNewAgentDescription(''); toast({ title: "Agent Created", description: "Your autonomous agent has been created successfully", variant: "default" }); } catch (error) { toast({ title: "Creation Failed", description: "There was an error creating your agent", variant: "destructive" }); } }; const getStatusColor = (status: string) => { switch (status) { case 'active': return 'bg-green-500'; case 'learning': return 'bg-blue-500'; case 'optimizing': return 'bg-purple-500'; case 'paused': return 'bg-yellow-500'; case 'offline': return 'bg-gray-500'; default: return 'bg-gray-400'; } }; const getTypeIcon = (type: string) => { switch (type) { case 'trading': return ; case 'research': return ; case 'development': return ; case 'analysis': return ; case 'creative': return ; default: return ; } }; const getAutonomyColor = (value: number) => { if (value >= 80) return 'text-green-600'; if (value >= 60) return 'text-blue-600'; if (value >= 40) return 'text-yellow-600'; return 'text-red-600'; }; const filteredAgents = agents.filter(agent => { if (searchQuery) { const query = searchQuery.toLowerCase(); return agent.name.toLowerCase().includes(query) || agent.metadata.description.toLowerCase().includes(query); } if (filterType !== 'all') return agent.type === filterType; if (filterStatus !== 'all') return agent.status === filterStatus; return true; }); if (loading) { return (

Loading agent autonomy...

); } return (

Agent Autonomy

Self-improving agents with goal-setting and planning capabilities

{stats?.totalAgents} Agents {stats?.activeAgents} Active {stats?.successRate}% Success Rate
Agents Goals Create Agent Analytics Search & Filter
setSearchQuery(e.target.value)} className="pl-10" />
{filteredAgents.map((agent) => (
{getTypeIcon(agent.type)} {agent.type} {agent.status}
{agent.name} {agent.metadata.description}
{agent.autonomy}%
Autonomy
{agent.performance}%
Performance
{agent.efficiency}%
Efficiency
Goals Progress {agent.goals.filter(g => g.status === 'completed').length}/{agent.goals.length}
g.status === 'completed').length / agent.goals.length) * 100} className="h-2" />
Learning Models:

{agent.learning.models}

Accuracy:

{agent.learning.accuracy}%

))}
Agent Goals Goals and objectives for autonomous agents
{agents.flatMap(agent => agent.goals.map(goal => (
{goal.title} {goal.priority} {goal.status}
{agent.name}

{goal.description}

Progress {goal.progress}%
Created:

{new Date(goal.createdAt).toLocaleDateString()}

Updated:

{new Date(goal.updatedAt).toLocaleDateString()}

{goal.deadline && (
Deadline:

{new Date(goal.deadline).toLocaleDateString()}

)}
)) )}
Create Autonomous Agent Set up a new self-improving autonomous agent
setNewAgentName(e.target.value)} />