Agent Dashboard¶

Overview¶

The Agent Dashboard is AIDDDMAP's central hub for managing and monitoring AI agents. It provides a comprehensive interface for interacting with the platform's 6+1 core agents and any custom agents created through the UADM. The dashboard enables real-time monitoring, configuration, and orchestration of agent activities.

Core Components¶

1. Agent Overview Panel¶

interface AgentOverview {
  agents: {
    core: CoreAgent[];
    custom: CustomAgent[];
  };
  metrics: {
    activeAgents: number;
    totalTasks: number;
    successRate: number;
    resourceUsage: ResourceMetrics;
  };
  status: {
    health: HealthStatus;
    alerts: Alert[];
    notifications: Notification[];
  };
}

interface CoreAgent {
  type: AgentType;
  status: "idle" | "processing" | "error";
  metrics: AgentMetrics;
  lastActivity: Date;
}

2. Agent Types & Capabilities¶

enum AgentType {
  DATA_FINDER = "finder",
  DATA_CURATOR = "curator",
  VALUATOR = "valuator",
  TREND_ANALYZER = "trend_analyzer",
  PUBLISHER = "publisher",
  QUALITY_ASSESSOR = "quality_assessor",
  LIBRARIAN = "librarian",
}

interface AgentCapabilities {
  dataProcessing: string[];
  analysis: string[];
  communication: string[];
  integration: string[];
}

Agent Management¶

1. Core Agents¶

DataFinder AI¶

interface DataFinderAgent extends BaseAgent {
  searchCriteria: {
    keywords: string[];
    dataTypes: string[];
    dateRange?: {
      start: Date;
      end: Date;
    };
  };

  findDatasets(criteria: SearchCriteria): Promise<Dataset[]>;
  rankResults(datasets: Dataset[]): Promise<RankedDataset[]>;
  suggestRelated(dataset: Dataset): Promise<Dataset[]>;
}

DataCurator AI¶

interface DataCuratorAgent extends BaseAgent {
  supportedFormats: string[];
  enhancementCapabilities: string[];

  standardizeFormat(data: any): Promise<any>;
  enrichMetadata(dataset: Dataset): Promise<Dataset>;
  validateSchema(dataset: Dataset): Promise<ValidationResult>;
}

ValuationAI¶

interface ValuationAgent extends BaseAgent {
  marketData: MarketMetrics;

  calculateValue(dataset: Dataset): Promise<ValuationResult>;
  analyzeDemand(dataset: Dataset): Promise<DemandMetrics>;
  suggestPricing(dataset: Dataset): Promise<PricingStrategy>;
}

2. Agent Communication¶

interface AgentMessage {
  from: string;
  to: string;
  type: MessageType;
  payload: any;
  timestamp: Date;
}

enum MessageType {
  REQUEST = "request",
  RESPONSE = "response",
  ERROR = "error",
  STATUS_UPDATE = "status_update",
}

// Example of inter-agent communication
await messageBus.send({
  from: "finder_agent",
  to: "quality_agent",
  type: MessageType.REQUEST,
  payload: {
    action: "assess_quality",
    dataset: foundDataset,
  },
});

Dashboard Interface¶

1. Main View¶

interface DashboardLayout {
  header: {
    title: string;
    navigation: NavigationMenu;
    actions: ActionButton[];
  };
  sidebar: {
    agentList: AgentListPanel;
    filters: FilterPanel;
    metrics: MetricsPanel;
  };
  mainContent: {
    activeView: ViewType;
    panels: Panel[];
  };
}

enum ViewType {
  OVERVIEW = "overview",
  AGENT_DETAIL = "agent_detail",
  TASKS = "tasks",
  ANALYTICS = "analytics",
}

2. Agent Cards¶

interface AgentCard {
  agent: BaseAgent;
  metrics: {
    tasks: TaskMetrics;
    performance: PerformanceMetrics;
    resources: ResourceUsage;
  };
  actions: {
    configure: () => void;
    deploy: () => void;
    pause: () => void;
    terminate: () => void;
  };
  visualization: {
    status: StatusIndicator;
    chart: MetricsChart;
  };
}

Monitoring & Analytics¶

1. Performance Metrics¶

interface AgentMetrics {
  performance: {
    responseTime: number;
    throughput: number;
    successRate: number;
    errorRate: number;
  };
  resources: {
    cpuUsage: number;
    memoryUsage: number;
    networkIO: {
      incoming: number;
      outgoing: number;
    };
  };
  tasks: {
    completed: number;
    failed: number;
    pending: number;
    active: number;
  };
}

2. Analytics Dashboard¶

interface AnalyticsDashboard {
  timeRange: TimeRange;
  metrics: MetricDefinition[];
  visualizations: Visualization[];
  filters: Filter[];
  export: ExportOptions;
}

interface Visualization {
  type: "line" | "bar" | "pie" | "heatmap";
  data: MetricData[];
  options: ChartOptions;
}

Integration Features¶

1. IDAT Integration¶

interface IDATIntegration {
  deployToCanvas: (agent: BaseAgent) => void;
  monitorWorkflow: (workflow: Workflow) => void;
  syncStatus: (status: AgentStatus) => void;
}

// Example: Deploy agent to IDAT
dashboard.deployToIDAT(agent, {
  position: { x: 100, y: 100 },
  connections: ["DataCurator", "Valuator"],
});

2. UADM Integration¶

interface UADMIntegration {
  importAgent: (agentConfig: UADMConfig) => Promise<BaseAgent>;
  exportAgent: (agent: BaseAgent) => Promise<UADMConfig>;
  updateAgent: (agent: BaseAgent, config: UADMConfig) => Promise<void>;
}

Task Management¶

1. Task Queue¶

interface TaskQueue {
  pending: Task[];
  active: Task[];
  completed: Task[];
  failed: Task[];

  addTask(task: Task): void;
  processNext(): Promise<void>;
  cancelTask(taskId: string): void;
}

interface Task {
  id: string;
  type: TaskType;
  agent: BaseAgent;
  status: TaskStatus;
  progress: number;
  created: Date;
  updated: Date;
}

2. Task Monitoring¶

interface TaskMonitor {
  activeTasks: Map<string, Task>;
  history: TaskHistory;

  trackProgress(taskId: string): Observable<TaskProgress>;
  getMetrics(timeRange: TimeRange): TaskMetrics;
}

Best Practices¶

1. Resource Management¶

const resourceManager = new ResourceManager({
  maxConcurrentTasks: 10,
  memoryThreshold: 0.8,
  cpuThreshold: 0.7,
  autoScale: true,
});

// Monitor resource usage
resourceManager.on("threshold_exceeded", (metric) => {
  console.warn(`Resource threshold exceeded: ${metric}`);
  resourceManager.optimizeResources();
});

2. Error Handling¶

class AgentError extends Error {
  constructor(
    message: string,
    public agent: BaseAgent,
    public task: Task,
    public recoverable: boolean,
  ) {
    super(message);
  }

  async recover(): Promise<void> {
    if (this.recoverable) {
      await this.agent.retry(this.task);
    }
  }
}

Example Usage¶

1. Basic Dashboard Setup¶

const dashboard = new AgentDashboard({
  layout: "grid",
  theme: "dark",
  refreshInterval: 5000,
  features: {
    realTimeUpdates: true,
    analytics: true,
    notifications: true,
  },
});

// Initialize core agents
dashboard.initializeCoreAgents();

// Subscribe to agent events
dashboard.on("agent_status_change", (agent, status) => {
  updateAgentCard(agent, status);
});

2. Advanced Configuration¶

const advancedDashboard = new AgentDashboard({
  // ... basic config ...
  features: {
    customMetrics: true,
    advancedAnalytics: true,
    automatedOptimization: true,
  },
  integration: {
    idat: true,
    uadm: true,
    marketplace: true,
  },
  security: {
    roleBasedAccess: true,
    auditLogging: true,
  },
});