DESIGN_DOC_UI.md

ArgOS UI/UX Design Document

Overview

ArgOS requires a sophisticated interface to manage and monitor complex agent swarms while maintaining deep observability and control. This document outlines the design of a scalable, intuitive interface that can handle everything from simple two-agent scenarios to complex multi-agent swarms with human-in-the-loop capabilities.

Core Design Principles

1. Scalable Observation: Must handle 2 to 2000+ agents without losing detail or control
2. Deep Inspection: Every aspect of agent behavior must be observable
3. Temporal Awareness: Full timeline visibility and control
4. Human Integration: Seamless interaction between human operators and agent swarms
5. Performance First: Handle large data streams without UI degradation

Layout Structure

1. Command Bar (Top)

• Primary Controls

  • Start/Stop/Reset simulation
  • Time controls (pause/slow/normal/fast)
  • Global search and filter
  • Snapshot management
  • Command palette trigger

• Status Indicators

  • System health
  • Active agent count
  • Current simulation time
  • Performance metrics

2. Agent Network View (Left Panel)

• Interactive Network Graph

  • Nodes

    • Room nodes (larger, hub-like)
    • Agent nodes (clustered around rooms)
    • Size indicates activity/importance
    • Color coding:
      • Rooms: by type (physical, Discord, Twitter, etc.)
      • Agents: by role/type

  • Edges

    • Room-Agent: shows presence/attention level
    • Agent-Agent: shows interaction strength
    • Edge thickness: interaction frequency
    • Edge color: type of relationship
    • Animated particles: active communication

  • Interaction

    • Click room to "join" and view detailed activity
    • Hover for quick stats
    • Double-click to focus/expand
    • Drag to rearrange
    • Mouse wheel to zoom

• Network Controls

  • Zoom/pan
  • Filter by:
    • Room type
    • Agent role
    • Activity level
    • Relationship type
  • Layout algorithms:
    • Force-directed (default)
    • Hierarchical (room-centric)
    • Circular (room-based clustering)
  • Group/ungroup clusters

3. Chat Interface (Center Panel)

• Contextual Chat Display

  • Adapts based on selection:
    • Room Chat: When room selected
    • Agent Chat: When agent selected
    • God Chat: When no selection (system level)

• Room Chat Mode

  • Real-time activity stream
  • Present agents with attention levels
  • Filterable stimulus types:
    • Speech/Messages
    • Visual actions
    • Cognitive processes
    • Environmental changes
  • Participant list with attention indicators
  • Room context and description

• Agent Chat Mode

  • Direct communication with agent
  • Agent's thought stream
  • Current perceptions across all rooms
  • Memory access and query
  • Relationship insights
  • Action history

• God Chat Mode

  • System-level commands
  • Agent creation and management
  • Room creation and configuration
  • Scenario building
  • Simulation control
  • Environment modification

• Chat Controls

  • Stimulus type filters
  • Time range filters
  • Search within chat
  • Export conversation
  • Clear chat
  • Pin important messages

• Interactive Elements

  • Click agent names to switch to agent chat
  • Click room references to switch rooms
  • Click stimuli for detailed view
  • Drag & drop support for:
    • Moving agents between rooms
    • Creating new rooms
    • Setting up relationships

4. Inspector Panel (Right Panel)

• Context-Sensitive Display

  Agent Context:

  • Identity & Role
  • Current state
  • Memory browser
    • Recent memories
    • Core memories
    • Experience timeline
  • Thought stream
    • Real-time thoughts
    • Decision points
    • Emotional state
  • Action log
    • Pending actions
    • Action history
    • Success/failure metrics
  • Perception feed
    • Current stimuli
    • Sensory history
    • Attention focus
  • Relationship map
    • Agent connections
    • Interaction history
    • Trust metrics

  Room Context:

  • Room properties
  • Present agents
  • Environmental conditions
  • Activity log
  • Resource status

5. Timeline/Event Stream (Bottom Panel)

• Event Visualization

  • Chronological event display
  • Multi-track timeline
  • Event categorization
  • Pattern highlighting

• Control Features

  • Playback controls
  • Time window selection
  • Event filtering
  • Bookmark system
  • Export capabilities

Advanced Features

1. Agent Focus Mode

• Full-screen agent detail view
• Complete history access
• Real-time monitoring
• Direct interaction tools
• Debug capabilities

2. Time Control System

• Variable simulation speed
• Time window isolation
• Event-based pausing
• Replay functionality
• State snapshot system

3. Query & Analysis

• Advanced search syntax
• Cross-agent pattern matching
• Behavior analysis tools
• Custom metric tracking
• Data export tools

4. God AI Interface

• Swarm management controls
• Policy adjustment
• Resource allocation
• Emergency interventions
• Performance optimization

Technical Considerations

1. Performance

• Virtualized lists for large datasets
• Incremental rendering
• Data streaming optimization
• Efficient state management
• Background processing

2. Data Management

• Hierarchical data structure
• Efficient storage patterns
• Caching strategies
• State persistence
• Export/import capabilities

3. Scalability

• Dynamic component loading
• Adaptive detail levels
• Resource management
• Connection pooling
• Load balancing

Implementation Priorities

Phase 1: Core Framework

1. Basic layout structure
2. Essential controls
3. Agent network view
4. Basic inspection capabilities

Phase 2: Enhanced Monitoring

1. Timeline implementation
2. Advanced inspector features
3. Query system
4. Performance optimization

Phase 3: Advanced Features

1. God AI interface
2. Pattern detection
3. Advanced analysis tools
4. Custom visualization options

Future Considerations

• VR/AR integration
• Collaborative features
• AI-assisted monitoring
• Custom extension system
• Remote control capabilities