Multilingual Real Estate Listing Platform

I need a full-stack web application that lets private landlords and agencies publish rooms, shared rooms, apartments, houses and even small B&B or hostel units. The heart of the site is a property-listing module with rich descriptions, so visitors can filter by location, price, bedrooms and bathrooms while browsing clear, well-scaled photos.

Key functions
• Advertiser dashboard – create an account, add or edit listings, and flip the status between “available” and “rented” with one click.
• Listings database – stores all property fields (location, price, bedroom/bath count, free-text description) and enforces a minimum image resolution while compressing files to keep storage lean.
• i18n multilanguage layer – at launch English/Spanish and Portuguese plus room for additional locales via standard gettext/JSON files; text strings grouped for easy translation.
• Responsive front-end – modern UI that works on mobile and desktop, built with React or Vue and tied to an Express / Django / Laravel API (I’m open to your preferred stack as long as it is widely supported).
• Hosting & deployment – configure everything on my Namecheap shared or VPS plan: SSL, environment variables, automated backups and a simple CI pipeline for future updates.

Deliverables
1. Source code in Git with clear README and environment file.
2. SQL (or NoSQL) schema script plus seed data.
3. Live site running on my Namecheap account with domain and HTTPS ready.
4. One-page admin guide covering user creation, language file editing and routine maintenance.

Acceptance criteria:
• An advertiser can register, log in and publish a listing containing all essential details in ≤3 minutes.
• Switching a listing to “rented” immediately hides it from public search and marks it in the admin panel.
• Image upload rejects files below the set minimum resolution and compresses accepted files automatically.
• Selecting a second language from the UI reloads static text in that language without page refresh.
• Lighthouse mobile performance score ≥80.

Let me know which stack you recommend, any third-party libraries you plan to use for i18n and image processing, and your estimated timeline for each milestone.