Architecture Overview

Kuse Cowork is built as a desktop application using modern technologies for both frontend and backend.

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High-Level Architecture

Technology Stack

Frontend

Backend

Communication

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Component Overview

Frontend Components

src/
├── App.tsx              # Main app shell
├── components/
│   ├── Chat.tsx         # Chat interface
│   ├── AgentMain.tsx    # Agent execution view
│   ├── TaskPanel.tsx    # Task progress display
│   ├── Settings.tsx     # Configuration panel
│   ├── ModelSelector.tsx # Model picker
│   └── MCPSettings.tsx  # MCP configuration
├── stores/
│   ├── settings.ts      # Settings state
│   └── chat.ts          # Chat state
└── lib/
    ├── tauri-api.ts     # Backend bridge
    ├── ai-client.ts     # Direct AI access
    └── mcp-api.ts       # MCP client

Backend Modules

src-tauri/src/
├── main.rs              # Application entry
├── lib.rs               # Library root
├── commands.rs          # Tauri command handlers
├── database.rs          # SQLite operations
├── llm_client.rs        # LLM provider clients
├── agent/
│   ├── mod.rs           # Agent module
│   ├── agent_loop.rs    # Main agent logic
│   ├── message_builder.rs # Request construction
│   ├── tool_executor.rs # Tool execution
│   └── types.rs         # Type definitions
├── tools/
│   ├── mod.rs           # Tools module
│   ├── bash.rs          # Shell execution
│   ├── docker.rs        # Container management
│   ├── file_read.rs     # File reading
│   ├── file_write.rs    # File writing
│   ├── file_edit.rs     # File editing
│   ├── glob.rs          # Pattern matching
│   ├── grep.rs          # Content search
│   └── list_dir.rs      # Directory listing
├── mcp/
│   ├── mod.rs           # MCP module
│   ├── client.rs        # MCP client
│   ├── http_client.rs   # HTTP transport
│   ├── config.rs        # Configuration
│   └── types.rs         # Type definitions
└── skills/
    └── mod.rs           # Skills management

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Data Flow

Chat Message Flow

Agent Task Flow

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State Management

Frontend State

State is managed using SolidJS signals and stores:

// Settings store
const [settings, setSettings] = createSignal<Settings>(DEFAULT_SETTINGS);

// Chat store
const [messages, setMessages] = createStore<Message[]>([]);

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Backend State

State is persisted in SQLite:

-- Settings table
CREATE TABLE settings (
    key TEXT PRIMARY KEY,
    value TEXT
);

-- Conversations table
CREATE TABLE conversations (
    id TEXT PRIMARY KEY,
    title TEXT,
    created_at INTEGER,
    updated_at INTEGER
);

-- Messages table
CREATE TABLE messages (
    id TEXT PRIMARY KEY,
    conversation_id TEXT,
    role TEXT,
    content TEXT,
    timestamp INTEGER
);

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Event System

Tauri Events

Events flow from backend to frontend:

// Backend: Emit event
window.emit("chat-event", ChatEvent::Text { content })?;

// Frontend: Listen for event
await listen<ChatEvent>("chat-event", (event) => {
    onEvent(event.payload);
});

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Event Types

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Security Model

Isolation Layers

┌─────────────────────────────────────┐
│           User Space                │
│  ┌─────────────────────────────┐   │
│  │    Kuse Cowork Process      │   │
│  │  ┌───────────────────────┐  │   │
│  │  │   Docker Container    │  │   │
│  │  │   (Tool Execution)    │  │   │
│  │  └───────────────────────┘  │   │
│  └─────────────────────────────┘   │
└─────────────────────────────────────┘

Data Protection

• Local Storage: All data in local SQLite
• No Telemetry: No external data transmission
• API Keys: Stored locally, passed only to providers
• Container Isolation: Commands run in Docker

Performance Considerations

Streaming

• SSE for real-time responses
• Incremental UI updates
• Token-by-token display

Caching

• Model configurations cached
• Connection states maintained
• Context reused across turns

Resource Management

• Container cleanup after execution
• Connection pooling for HTTP
• Memory-efficient file handling

Extensibility Points

Adding Providers

1. Implement in llm_client.rs
2. Add format detection
3. Handle authentication
4. Support streaming

Adding Tools

1. Create in tools/ directory
2. Register in tools/mod.rs
3. Add to agent config
4. Handle in tool executor

Adding MCP Servers

1. Define server config
2. Implement tool discovery
3. Handle authentication
4. Process tool calls

Next Steps

• Frontend Architecture
• Backend Architecture
• Development Setup

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