Zenith

Zenith is a high-performance, visual interface for tracking humanity's presence in the cosmos. It combines real-time orbital tracking of Low Earth Orbit (LEO) satellites with a deep-space network monitor for interplanetary missions.

Table of Contents

• Tech Stack
• Features
  • Space Intelligence Dashboard
  • Orbital Radar (LEO)
  • Space Weather (Aurora)
  • Deep Space Network (DSN)
  • Launch Gateway
• Architecture & Data Flow
• Setup
• Docker Setup
• Automation
  • 1. NASA JPL Horizons (Deep Space)
  • 2. CelesTrak (LEO Satellites)
  • 3. Launch Library 2 (The Space Devs)
  • 4. NOAA Aurora Forecast
  • 5. AI Intelligence Agent

Tech Stack

• Engine: React 19, TypeScript
• Build: Vite 7
• Styling: Tailwind CSS v4
• Runtime: Bun 1.x (1.3+ in Docker)
• Intelligence: OpenAI (gpt-4.1)
• Infrastructure: Docker Compose

Features

Space Intelligence Dashboard

• AI-curated daily overview of the most significant space events.
• Top 3 Events: Launches, aurora opportunities, and satellite events ranked by importance.
• Quick Stats: Next launch countdown, current Kp index, weekly statistics.
• Active Alerts: Time-sensitive notifications for exceptional events.
• Smart Navigation: Click events to navigate directly to detailed views.

Orbital Radar (LEO)

• Real-time tracking of the ISS, Tiangong, and Starlink constellations.
• Azimuth/Elevation projection relative to your location.
• Visual pass predictions and sky plotting.

Space Weather (Aurora)

• Real-time Kp Index monitoring from NOAA Space Weather Prediction Center.
• 3-Day Aurora Forecast with hourly Kp predictions.
• Location-based visibility thresholds (automatically calculates if aurora is visible at your latitude).
• Observer Location: Set your location via GPS or search.

Deep Space Network (DSN)

• Tracking of legendary interstellar probes: Voyager 1, Voyager 2, New Horizons, and James Webb.
• Real-Time Data: Positions (Distance, Velocity, RA/DEC) fetched directly from NASA JPL Horizons.
• Dual Visualization Modes:
  • Linear Scale: Logarithmic distance timeline.
  • Radial Map (2D): Polar plot showing the solar system scale and spacecraft directions relative to Earth.
• Ping Simulation: Visualizes the light-speed communication delay.

Launch Gateway

• Countdown to the next major space launches worldwide.
• Detailed mission profiles including rocket configurations, launch sites, and mission descriptions.
• Data provided by The Space Devs (Launch Library 2).

Architecture & Data Flow

Zenith uses a hybrid approach to ensure performance and data freshness without hitting rate limits on client-side keys.

graph TD
    NASA[NASA JPL Horizons API]
    DSN[NASA DSN XML]
    CelesTrak[CelesTrak API]
    LL2[Launch Library 2 API]
    NOAA[NOAA SWPC API]
    OpenAI[OpenAI GPT-4.1]
    
    Script_Horizons[scripts/fetch-spacecraft.ts]
    Script_TLE["bash (curl)"]
    Script_Launches[scripts/fetch-launches.ts]
    Script_Aurora[scripts/fetch-aurora.ts]
    Script_Agent[agents/zenith-intelligence-agent.ts]
    
    JSON_Spacecraft[public/data/spacecraft.json]
    TXT_TLE[public/data/tles.txt]
    JSON_Launches[public/data/launches.json]
    JSON_Aurora[public/data/aurora.json]
    JSON_Insights[public/data/daily-insights.json]
    
    App[React Application]
    Action_Horizons["GitHub Action: update-spacecraft.yml"]
    Action_TLE["GitHub Action: update-tle.yml"]
    Action_Launches["GitHub Action: update-launches.yml"]
    Action_Aurora["GitHub Action: update-aurora.yml"]
    Action_Agent["GitHub Action: run-agent.yml"]

    subgraph "Automated Backend (Build Time)"
    Action_Horizons -- "Every 6h" --> Script_Horizons
    Script_Horizons -- "Queries (RA/DEC/Range)" --> NASA
    NASA -- "CSV Response" --> Script_Horizons
    
    Script_Horizons -- "Check Status" --> DSN
    DSN -- "XML Response" --> Script_Horizons
    
    Script_Horizons -- Writes --> JSON_Spacecraft

    Action_TLE -- Every 6h --> Script_TLE
    Script_TLE -- Fetches GP Elements --> CelesTrak
    CelesTrak -- TLE Response --> Script_TLE
    Script_TLE -- Writes --> TXT_TLE

    Action_Launches -- "Every 30m" --> Script_Launches
    Script_Launches -- "Queries" --> LL2
    LL2 -- "JSON Response" --> Script_Launches
    Script_Launches -- Writes --> JSON_Launches

    Action_Aurora -- "Every 6h" --> Script_Aurora
    Script_Aurora -- "Queries Kp Forecast" --> NOAA
    NOAA -- "JSON Response" --> Script_Aurora
    Script_Aurora -- Writes --> JSON_Aurora

    Action_Agent -- "Every 12h" --> Script_Agent
    Script_Agent -- Reads --> JSON_Launches
    Script_Agent -- Reads --> JSON_Aurora
    Script_Agent -- "Analyzes & Enriches" --> OpenAI
    OpenAI -- "AI Insights" --> Script_Agent
    Script_Agent -- Writes --> JSON_Insights
    end

    subgraph "Frontend (Runtime)"
    App -- Fetches --> JSON_Spacecraft
    App -- Fetches --> TXT_TLE
    App -- Fetches --> JSON_Launches
    App -- Fetches --> JSON_Aurora
    App -- Fetches --> JSON_Insights
    App -- Renders --> UI[UI / Canvas]
    end

Loading

Setup

This project uses Bun as the package manager and runtime.

# Install dependencies
bun install

# Start development server
bun start

# Build for production
bun run build

Docker Setup

Alternatively to a local Bun installation, you can run the entire Zenith ecosystem using Docker Compose. This is highly recommended for testing the data automation pipeline in a consistent environment.

1. Start Frontend

By default, only the Vite dev server starts:

docker compose up

The application will be available at: http://localhost:5173/zenith/

2. Run Automation Tools

Sync data or run the AI agent on demand using Docker profiles:

• Data Sync: docker compose run --rm sync
• AI Agent: docker compose run --rm agent

3. Cleanup & Reset

To stop all containers and remove persistent volumes (e.g., to solve permission issues):

docker compose down -v

Tip

Use docker compose --profile tools up to start the frontend and run all automation tools once.

Automation

The project includes custom scripts and workflows to bridge external data sources.

1. NASA JPL Horizons (Deep Space)

• Source: scripts/fetch-spacecraft.ts queries NASA Horizons for ephemeris and NASA DSN XML for real-time signal status.
• Schedule: Updates every 6 hours via update-spacecraft.yml.
• Output: public/data/spacecraft.json.

2. CelesTrak (LEO Satellites)

• Source: update-tle.yml uses curl to fetch General Perturbation (GP) elements for "Visual" and "Stations" groups.
• Schedule: Updates every 6 hours.
• Output: public/data/tles.txt (Local mirror to prevent rate-limiting).

3. Launch Library 2 (The Space Devs)

• Source: scripts/fetch-launches.ts queries the Launch Library 2 API for upcoming orbital launches.
• Schedule: Updates every 30 minutes via update-launches.yml.
• Output: public/data/launches.json.

4. NOAA Aurora Forecast

• Source: scripts/fetch-aurora.ts queries the NOAA SWPC for 3-day Kp index forecasts.
• Schedule: Updates every 6 hours via update-aurora.yml.
• Output: public/data/aurora.json.

5. AI Intelligence Agent

• Source: agents/zenith-intelligence-agent.ts uses OpenAI GPT-4.1 to analyze space data.
• Schedule: Runs every 12 hours via run-agent.yml.
• Capabilities:
  • Analyzes upcoming launches and rates importance (1-10 scale)
  • Evaluates aurora forecasts and identifies optimal viewing windows
  • Generates daily summaries with top 3 events
  • Creates time-sensitive alerts for exceptional events
• Output: public/data/daily-insights.json, public/data/enriched-launches.json.
• Configuration: Set OPENAI_API_KEY and MODEL_NAME in environment variables.