A minimalist Google Maps application with AI-powered landmark discovery and 3D exploration experience.

• New addition: Search Nearby airports, Search Internet Radio stations
• Moving Map: MSFS (Microsoft Flight Simulator) integration for aircraft marker tracking effect
• Landmark Discovery: Google Places nearby search + OpenAI landmark query + Wikipedia images
• Location Search: Google Places text search + OpenAI location query + User Geolocation
• Photorealistic 3D Maps: Google Earth-style 3D navigation + Cinematic flyovers for each landmarks
• World ready: Automatically adapts LLM content and UI translation to browser's language setting

• Frontend: Map integration, landmark visualization, location navigation, browser-side caching and test runner
• Backend: Flask API connecting to MSFS via SimConnect proxy to fetch real-time aircraft telemetry
• LLM: OpenAI selects landmarks from Google results, generates descriptions, adapts language to location
• Caching: Proximity-based keys with coordinate rounding + location matching + TTL expiration
• Auto Translation: Support JSON resource, string changes detection, local TM (Translation Memory), secondary locale for multi-lingual users
• Configuration: Map defaults, test mode mock data on config.json, LLM prompt templates on prompts.js

• Google Maps API: Core mapping functionality with 3D support
• Google Places API: Location search and nearby places discovery
• OpenAI API: LLM generated translations and landmark information
• Wikipedia API: Landmark and location photos

src/
├── app.js          # Init Google Maps application
├── search.js       # Location and landmark search
├── landmark.js     # Landmark display, markers, and 3D overlays
├── gmap.js         # Google Maps API wrappers
├── openai.js       # OpenAI prompting
├── prompts.js      # LLM Prompt templates
├── lion.js         # i18n/L10n with auto-translations
├── cache.js        # On-browser localStorage caching
├── components.js   # reusable UI components
├── simconnect.js   # connect to MSFS via SimConnect
└── test_runner.js  # Client-side testing

Prerequisites

• Install Node.js (https://nodejs.org/).
• Clone this repository and install dependencies (see package.json)

git clone <repository-url>
cd <my-project>
npm install

Create environment file

Create your own .env file and add your API keys for local development. Vite exposes variables prefixed with VITE_ to the browser app

VITE_GOOGLE_MAPS_API_KEY=your_google_maps_api_key
VITE_OPENAI_API_KEY=your_openai_api_key

As an open-source project targeting technical users, this client-only web-app is designed to run on user's keys. The user is responsible for:

1. Creating their own Google Cloud project Maps API key (required), and OpenAI API key (optional)
2. Securing their key by restricting it to their own domains (localhost for testing, their deployment domain for production).
3. The costs associated with their usage, respecting Google Maps and OpenAI terms of service.

Generate API keys

• Google Maps API Key

  1. Visit the Google Cloud Console → Create or select a project → Go to Google Maps Platform (See Also).
  2. Enable “Map Tiles API”, “Maps JavaScript API”, “Geocoding API” and “Places API (New)” under APIs & Services.
  3. Create an API key under Keys & Credentials. For local development restrict HTTP referrer to localhost.

• OpenAI API Key

  1. Visit the OpenAI dashboard.
  2. Create a new secret key and copy it for later use; it won't be shown again.

Start Vite development server

npm run dev

Enter API keys in the app

• Open http://localhost:5001 in your browser.
• Click the gear icon (⚙️ Settings UI) in the bottom‑left corner.
• Fill in GOOGLE_MAPS_API_KEY and OPENAI_API_KEY, then close to save.
• Settings are stored in localStorage under APP_SETTINGS.
• In Chrome, view them under DevTools → Application → Local Storage; landmark caches use keys starting with landmark_.

Start server proxy for MSFS "moving map"

• Install Python with UV and dependencies (see pyproject.toml)
• Relies on the Python‑SimConnect library
• Install and run it alongside with MSFS on the same PC

uv pip install .
python server.py

• Pan and zoom the Google map. Use 🔍 Location Search to search a city or place.
• Click 🏛️ Landmarks to discover nearby points of interest around the map center.
• Select a landmark card to read the AI-generated description and see a Wiki photo.
• Click [3D] on landmark cards to explore with a photorealistic 3D map view.
• Use 📍 My Location to center the map at current geolocation per browser detection.
• Open the gear icon (⚙️ Settings) to update API keys or clear stored values.
• Use 🌐 Locale to toggle between multiple preferred locales per browser setting.
• Click aircraft ✈️ icon to sync aircraft position when connected to MSFS.

• Frontend Test Runner - standalone test script running direct function testing
• Built-in test mode with mock data from config.json, skipping API calls
• Runnable on both browser console and Node.js CLI via npm test
• Append ?test=true to the URL to auto-run tests on-browser

You can ask a LLM to read this source code and answer most questions about this project. For example, try pasting these prompts directly into ChatGPT:

• In the GitHub public repo cozymos/mini-moving-map, can you show me how to install and run it on the same PC that runs MSFS, starting with step-by-step how to generate a Google API key.
• The README of cozymos/mini-moving-map is too complex. Please describe, in simple steps in plain language, how a non-technical person can open and use the app on an Oculus headset. Ask me questions to help fill gaps.
• Review the source code of https://github.com/cozymos/mini-moving-map — is it safe to enter my OpenAI API key in the browser? Does the repo send my API keys anywhere?