bandit-runner/docs/development_documentation/IMPLEMENTATION-SUMMARY.md

LangGraph Agent Framework - Implementation Summary

Overview

Successfully implemented a comprehensive LangGraph.js-based agentic framework for the Bandit Runner application. The framework runs entirely in Cloudflare Durable Objects and provides a beautiful retro terminal UI for interacting with autonomous agents that solve the OverTheWire Bandit wargame.

✅ What Was Implemented

1. Core Backend Components

State Management (src/lib/agents/bandit-state.ts)

• Comprehensive TypeScript interfaces for agent state
• Level goals for all 34 Bandit levels
• Command and thought log tracking
• Checkpoint system for pause/resume functionality

LLM Provider Layer (src/lib/agents/llm-provider.ts)

• OpenRouter integration supporting multiple models:
  • OpenAI (GPT-4o, GPT-4o Mini)
  • Anthropic (Claude 3.5 Sonnet, Claude 3 Haiku)
  • Meta (Llama 3.1)
  • DeepSeek, Gemini, Mistral, and more
• Streaming and non-streaming response modes
• Abstraction layer for easy provider switching

SSH Tool Wrappers (src/lib/agents/tools.ts)

• ssh_connect - Establish SSH connections
• ssh_exec - Execute commands with safety allowlist
• validate_password - Test passwords via SSH
• ssh_disconnect - Close connections
• Command validation and security checks

LangGraph State Machine (src/lib/agents/graph.ts)

• State graph with nodes:
  • plan_level - LLM plans next command
  • execute_command - Runs SSH command
  • validate_result - Checks for password
  • advance_level - Moves to next level
• Conditional edges based on agent status
• Integration with LangChain tools

Error Handling (src/lib/agents/error-handler.ts)

• Error classification (network, SSH, timeout, API)
• Retry strategies with exponential backoff
• Cost tracking for LLM API calls
• Spending limit enforcement

Storage Layer (src/lib/storage/run-storage.ts)

• Durable Object storage interface
• D1 database schema for run metadata
• R2 storage for JSONL logs
• Password vault with encryption
• Data lifecycle management (DO → D1 → R2)

2. Durable Object Implementation

BanditAgentDO (src/lib/durable-objects/BanditAgentDO.ts)

• Runs LangGraph state machine
• WebSocket server for real-time streaming
• HTTP endpoints for agent control:
  • /start - Start new run
  • /pause - Pause execution
  • /resume - Resume from checkpoint
  • /command - Manual command injection
  • /retry - Retry current level
  • /status - Get current state
• Alarm-based auto-cleanup after 2 hours
• State persistence in DO storage

3. API Routes

Agent Lifecycle (src/app/api/agent/[runId]/route.ts)

• POST endpoints for all agent actions
• GET endpoint for status queries
• Durable Object proxy layer
• Error handling and validation

WebSocket Route (src/app/api/agent/[runId]/ws/route.ts)

• WebSocket upgrade handling
• Bidirectional communication with Durable Object
• Real-time event streaming

4. Frontend Components

WebSocket Hook (src/hooks/useAgentWebSocket.ts)

• React hook for WebSocket management
• Auto-reconnect with exponential backoff
• Event handlers for terminal and chat updates
• Connection state tracking
• Ping/pong keep-alive

Agent Control Panel (src/components/agent-control-panel.tsx)

• Model selection dropdown
• Level range selector (0-33)
• Streaming mode toggle
• Start/Pause/Resume/Stop buttons
• Status indicators (idle/running/paused/complete/failed)
• Connection status display

Enhanced Terminal Interface (src/components/terminal-chat-interface.tsx)

• Integrated with WebSocket for real-time updates
• Split-pane layout (terminal left, agent chat right)
• Command history with arrow keys
• Panel switching (Ctrl+K/J, ESC)
• Support for manual intervention when paused
• Beautiful retro styling with scan lines and grid patterns
• System messages for agent events
• Thinking indicators

5. WebSocket Event System

Event Handlers (src/lib/websocket/agent-events.ts)

• Standardized event types:
  • terminal_output - Command execution
  • agent_message - Agent commentary
  • thinking - Agent reasoning
  • tool_call - Tool execution
  • level_complete - Level advancement
  • run_complete - Full run completion
  • error - Error messages
• Event routing to terminal and chat displays
• Timestamp and metadata tracking

6. Configuration

Wrangler (wrangler.jsonc)

• Durable Object bindings configured
• Environment variables for SSH proxy
• Placeholders for D1 and R2 (ready to uncomment)
• Secret management instructions

TypeScript (src/types/env.d.ts)

• Environment type declarations
• Cloudflare binding types
• Type safety for all env variables

7. Dependencies Installed

{
  "@langchain/langgraph": "latest",
  "@langchain/core": "latest", 
  "@langchain/openai": "latest",
  "zod": "latest"
}

🚧 What Still Needs to Be Done

1. SSH Proxy Service (CRITICAL)

• Build the Node.js SSH proxy (see SSH-PROXY-README.md)
• Deploy to Fly.io/Railway/Render
• Update SSH_PROXY_URL in wrangler.jsonc

2. Durable Object Export

• Export BanditAgentDO in worker entry point
• Configure migration tag for DO deployment

3. LangGraph Integration Refinement

• Test graph execution in Workers environment
• May need to use @langchain/langgraph/web entry point
• Add manual config passing to avoid async_hooks issues
• Integrate actual tool execution (currently mocked)

4. D1 and R2 Setup

• Create D1 database: wrangler d1 create bandit-runs
• Run schema migrations
• Create R2 bucket: wrangler r2 bucket create bandit-logs
• Uncomment bindings in wrangler.jsonc

5. Secrets Configuration

wrangler secret put OPENROUTER_API_KEY
wrangler secret put ENCRYPTION_KEY

6. Testing

• Unit tests for graph nodes
• Integration tests for WebSocket
• Mock SSH proxy for development
• Load testing for concurrent runs

7. Advanced Features (Future)

• Run history and comparison UI
• Export functionality (JSONL, CSV)
• Keyboard shortcuts reference modal
• Run templates and presets
• Cost analytics dashboard
• Multi-run leaderboard

📝 Key Files Created

bandit-runner-app/src/
├── lib/
│   ├── agents/
│   │   ├── bandit-state.ts        (State schema, level goals)
│   │   ├── llm-provider.ts        (OpenRouter integration)
│   │   ├── tools.ts               (SSH tool wrappers)
│   │   ├── graph.ts               (LangGraph state machine)
│   │   └── error-handler.ts       (Retry logic, cost tracking)
│   ├── durable-objects/
│   │   └── BanditAgentDO.ts       (Durable Object implementation)
│   ├── storage/
│   │   └── run-storage.ts         (DO/D1/R2 storage layer)
│   └── websocket/
│       └── agent-events.ts        (Event handlers)
├── app/api/agent/[runId]/
│   ├── route.ts                   (HTTP API routes)
│   └── ws/
│       └── route.ts               (WebSocket route)
├── components/
│   ├── agent-control-panel.tsx    (Control panel UI)
│   └── terminal-chat-interface.tsx (Enhanced terminal)
├── hooks/
│   └── useAgentWebSocket.ts       (WebSocket React hook)
└── types/
    └── env.d.ts                   (Environment types)

🎯 How to Use

1. Local Development

cd bandit-runner-app
pnpm install
pnpm dev

2. Configure SSH Proxy

Build and deploy the SSH proxy service (see SSH-PROXY-README.md), then update:

export SSH_PROXY_URL=https://your-proxy.fly.dev

3. Set API Key

export OPENROUTER_API_KEY=sk-or-...

4. Start a Run

1. Open http://localhost:3000
2. Select a model (e.g., GPT-4o Mini)
3. Choose level range (e.g., 0-5)
4. Click START
5. Watch the agent work in real-time!

5. Manual Intervention

• Click PAUSE to stop the agent
• Type commands in the terminal (left pane)
• Message the agent in chat (right pane)
• Click RESUME to continue

🏗️ Architecture Highlights

Execution Flow

User clicks START
    ↓
POST /api/agent/{runId}/start
    ↓
Durable Object spawned/retrieved
    ↓
LangGraph state machine initialized
    ↓
WebSocket connection established
    ↓
Graph executes: plan → execute → validate → advance
    ↓
Events streamed to UI in real-time
    ↓
State checkpointed in DO storage
    ↓
On completion: metadata saved to D1, logs to R2

WebSocket Event Flow

Durable Object
    ↓ (WebSocket)
API Route /ws
    ↓
useAgentWebSocket hook
    ↓ (handleAgentEvent)
Terminal/Chat UI updates

State Persistence

Active State: Durable Object (in-memory)
Checkpoints: Durable Object storage
Metadata: D1 Database (when configured)
Logs: R2 Bucket (when configured)

🎨 UI Features

• Retro Terminal Aesthetic: Scan lines, grid patterns, CRT-style
• Dual Panels: Terminal (left) + Agent Chat (right)
• Real-time Updates: WebSocket streaming
• Status Indicators: Connection, run state, level progress
• Model Selection: 10+ LLM models via OpenRouter
• Manual Control: Pause, resume, manual commands
• Keyboard Navigation: Ctrl+K/J panel switching, arrow keys for history

🔐 Security

• SSH target hardcoded to bandit.labs.overthewire.org:2220
• Command allowlist enforcement
• Password redaction in logs
• R2 encryption for sensitive data
• Rate limiting (to be implemented)
• Automatic cleanup of stale runs

📊 Next Steps

1. Deploy SSH Proxy - Build from SSH-PROXY-README.md
2. Test Integration - Run end-to-end test with a simple level
3. Refine LangGraph - Ensure Workers compatibility
4. Add D1/R2 - Set up persistent storage
5. Production Deploy - Deploy to Cloudflare Workers
6. Monitor & Iterate - Track performance, costs, success rates

🎉 What's Amazing

• Full LangGraph.js in Cloudflare Durable Objects
• Multi-LLM Support via OpenRouter (10+ models)
• Beautiful UI with retro terminal aesthetic
• Real-time Streaming via WebSocket
• Pause/Resume with state checkpointing
• Manual Intervention for debugging
• Extensible architecture for future features

🙏 Acknowledgments

• Built on Next.js, OpenNext, Cloudflare Workers
• Powered by LangGraph.js and LangChain
• UI components from shadcn/ui
• Inspired by the OverTheWire Bandit wargame