Vector Dispatch

Real-time flight operations dashboard with AI-powered risk assessment.

Prerequisites

• Bun >= 1.0
• Flight-Engine (optional, for real flight data)

Environment Setup

1. Copy the environment template:

   cp .env.example .env
   cp vector-dispatch/.env.example vector-dispatch/.env.local

2. Configure your environment variables in .env:

   # MongoDB Atlas
   MONGODB_URI=mongodb+srv://...
   
   # Flight-Engine API (optional)
   FLIGHT_ENGINE_URL=http://localhost:3030
   
   # AI Services
   LOCAL_AI_BASE_URL=http://127.0.0.1:8045/v1
   GOOGLE_AI_API_KEY=your-key-here
   

Note: If Flight-Engine is not available, the system falls back to MongoDB, then mock data. If AI services are unavailable, the system uses rule-based MEL decision logic.

Flight-Engine Integration

Vector Dispatch integrates with American Airlines Flight-Engine for real flight data.

Setup Flight-Engine

# Clone and run Flight-Engine
git clone https://github.com/AmericanAirlines/Flight-Engine.git
cd Flight-Engine
npm install
npm start

Flight-Engine runs on port 3030 by default. Set FLIGHT_ENGINE_URL in your .env if using a different port.

Data Priority

The socket server loads flight data in this order:

1. Flight-Engine API - Real flight schedules (if available)
2. MongoDB - Persisted flight state (if connected)
3. Mock Data - Generated test flights (fallback)

Installation

bun install

Running the Application

Start both the Next.js frontend and Socket.io server:

bun run dev:all

Or run them separately:

# Terminal 1: Socket server
bun run dev:socket

# Terminal 2: Next.js frontend
bun run dev

Testing

bun test