A full-stack real estate platform where you can browse & list properties, book viewings, and run AI-powered searches that scrape live listings from 99acres, MagicBricks & NoBroker in real time. You bring a free Firecrawl key — the AI runs on the server.

🏠 What is BuildEstate?

BuildEstate is a complete real-estate website for India — think of a mini 99acres/MagicBricks with an AI twist. In plain words, here is what you can do on it:

• Browse properties listed on the platform, filter them, view photo galleries, and book a property viewing (works even without an account)
• List your own property for sale or rent from your user dashboard — an admin reviews it before it goes live
• Use the AI Property Hub — enter a city, budget, and home type, and the AI searches live listings on 99acres, MagicBricks & NoBroker, then ranks the best matches with value verdicts and red-flag warnings
• See market trends — price per sq.ft, rental yields, and appreciation outlook for localities in any major Indian city

For the site owner there is a full admin panel: a review queue for user-submitted listings, appointment management, user management, an analytics dashboard, and AI model configuration.

This repo contains all three apps: the user website (frontend/), the admin panel (admin/), and the REST API (backend/).

📸 Platform Preview

📋 Table of Contents

🧠 Why BuildEstate?

Most real-estate aggregators show you generic listings. BuildEstate is different:

| Problem | BuildEstate Solution | |---|---| | Generic search results with mixed content | Multi-source search — 99acres, MagicBricks, Housing.com results deduplicated & ranked | | No AI intelligence in traditional portals | Multi-model AI analysis — best-value picks, investment insights, red-flag detection, with a user-selectable model (GLM, Nemotron & more) | | API costs borne by the developer | Bring-your-own Firecrawl key — scraping runs on the user's free key; AI analysis runs server-side | | Search-page bot protection ruins results | Individual listing scraping — firecrawl.search() → per-property URLs → clean data | | Search breaks on proxy/rate errors | Auto-retry with exponential backoff — proxy → rate-limit → server errors all handled |

TL;DR — This is not another property listing site. It's an AI-first platform that turns raw web data into actionable real estate insights.

🤖 AI Property Hub

The headline feature. Search any Indian city + property type + budget → get live scraped properties with AI analysis.

  

🎬 Watch It In Action

https://github.com/user-attachments/assets/43cefb8a-0e75-4680-85e9-2eb099db0fc8

📹 _Demo video coming soon — a full AI search from form to ranked results in ~30 seconds._

How It Works

The new search pipeline uses Google-indexed URLs as the filter, scraping individual property pages in parallel:

sequenceDiagram
    participant User as User<br/>(Browser)
    participant Backend as Express<br/>Backend
    participant Firecrawl as Firecrawl API
    participant Sources as 99acres<br/>MagicBricks<br/>Housing.com
    participant AI as GitHub Models<br/>(GPT-4.1)
    
    User->>Backend: POST /api/ai/search<br/>(city, locality, bhk, budget, possession)
    Backend->>Backend: Build 3 search queries
    
    par Multi-Source Search
        Backend->>Firecrawl: Search: "2BHK flat for sale in Powai<br/>Mumbai under ₹2Cr site:99acres.com"
        Backend->>Firecrawl: Search: "...site:magicbricks.com"
        Backend->>Firecrawl: Search: "...site:housing.com"
    end
    
    Firecrawl->>Sources: Google API returns listing URLs
    Sources->>Firecrawl: Returns 8-10 URLs per source
    
    par Parallel Scraping
        Firecrawl->>Sources: Full browser render of each URL
        Firecrawl->>Sources: LLM extracts structured JSON
    end
    
    Backend->>Backend: Deduplicate by address + building name<br/>Code-side filter: reject rentals/PG
    
    Backend->>AI: Send clean properties for ranking
    AI->>Backend: Return ranked with insights
    
    Backend->>User: { properties, analysis, source_badges }

Search Query Construction

The backend builds rich search queries that leverage Google's index as the filter:

User fills form:
  City: Mumbai
  Locality: Powai
  BHK: 2BHK
  Budget: ₹1.5 - ₹2.5 Cr
  Possession: Ready
                         ↓
Search query:
  "2BHK flat for sale in Powai Mumbai ready
   under 2.5 crore site:99acres.com"
                         ↓
firecrawl.search() → returns 10 individual property listing URLs
                         ↓
Scrape each URL in parallel (each = exactly ONE property)
                         ↓
Code-side filter: reject anything with "/month" or "rental"

Why this works:

• Individual listing pages have light bot protection (not heavily scraped)
• Google's index is the filtering engine — query says "ready" so only ready properties return
• One page = one property = zero mixed-content problem
• URL of the page you scraped IS the property listing URL — always correct

Supported Coverage

| Category | Coverage | |---|---| | 🏙️ Cities | 30+ — Mumbai, Delhi, Bangalore, Pune, Chennai, Hyderabad, Ahmedabad, Kolkata, Jaipur, Lucknow, and more | | 🏠 Property Types | Flat, House, Villa, Plot, Penthouse, Studio, Commercial | | 💰 Budget Range | ₹5 Lakhs → ₹25+ Crores (user-defined min/max) | | 📍 Multi-Source | 99acres.com, MagicBricks.com, Housing.com searched in parallel | | 🏷️ Deduplication | Same property across portals = shown once with source badges | | 🔄 Retry Logic | Auto-retry on proxy failures, rate limits (429), and server errors (502/503) | | 🔧 Advanced Filters | Locality, BHK (1/2/3/4/Any), Possession status (Ready/Under Const/Any) |

Advanced Search Form Fields

The redesigned form captures buyer intent more precisely:

| Field | Type | Values | Impact | |-------|------|--------|--------| | City | Dropdown | 30+ Indian cities | Primary market | | Locality ✨ | Text autocomplete | "Powai", "Andheri West", etc. | Highest relevance gain | | Property Type | Pill buttons | Flat / House / Villa / Plot | Property category | | BHK Config ✨ | Pill selector | 1BHK / 2BHK / 3BHK / 4BHK+ / Any | Unit size | | Budget | Dual slider | ₹X Lakhs → ₹Y Crores | Price range | | Possession ✨ | Radio group | Ready / Under Const / Any | Timeline preference |

Locality is the biggest improvement — Indians buy in neighborhoods, not cities. "Powai" → 10x better results than just "Mumbai".

🔑 Bring Your Own Firecrawl Key

Users provide their own free Firecrawl key in the browser — it lives in localStorage only, never on the server. AI analysis runs server-side through a multi-model fallback chain (NVIDIA NIM → GitHub Models), and users pick the model (GLM-5.2, Nemotron Nano/Ultra, Mistral…) right in the search form.

User's browser (localStorage)
  buildestate_firecrawl_key = "fc-xxx"
         │
         │  X-Firecrawl-Key header on every AI request
         ▼
  Backend creates a per-request Firecrawl instance
  (scraping ALWAYS uses the user's key — server AI keys
   are used only for the analysis step)

Get your free key in ~2 minutes:

| Service | Link | Free Tier | |---|---|---| | Firecrawl (web scraping) | firecrawl.dev | 500 free credits/month |

🌟 Features

✨ AI Property Hub (Redesigned)

Search across 3+ property portals in parallel, get deduplicated results ranked by AI insights.

🏡 Property Browsing & Booking

Rich filters, detailed galleries (up to 4 images per property via ImageKit CDN), and instant appointment scheduling.

👤 User Dashboard

Every registered user gets a personal dashboard — list a property for sale/rent, track its review status, and manage viewing appointments.

📊 Admin Dashboard

Full control — review user-submitted listings, manage properties & users, track appointments, and monitor analytics.

🏗️ Architecture

Multi-source AI Property Search Pipeline:

graph TD
    A["React Frontend<br/>(TypeScript + Vite)"] -->|POST /api/ai/search| B["Express Backend<br/>(Node.js + Helmet + CORS)"]
    
    B -->|Build 3 parallel queries| C["Firecrawl API"]
    
    C -->|Query 1:<br/>site:99acres.com| D1["99acres"]  
    C -->|Query 2:<br/>site:magicbricks.com| D2["MagicBricks"]
    C -->|Query 3:<br/>site:housing.com| D3["Housing.com"]
    
    D1 -->|8-10 URLs| E["Parallel<br/>Scraping"]
    D2 -->|8-10 URLs| E
    D3 -->|8-10 URLs| E
    
    E -->|Full browser render<br/>per property| F["Firecrawl<br/>scrapeUrl"] 
    F -->|Structured JSON| G["Backend<br/>Processing"]
    
    G -->|Deduplicate<br/>by address| H["Code-side Filter<br/>Reject rentals/PG"]
    H -->|Clean properties| I["GitHub Models<br/>GPT-4.1"]
    
    I -->|Ranked + Insights| J["Response<br/>to Frontend"]
    
    J -->|Display with<br/>source badges| K["Rich Property<br/>Cards"]
    
    B --> L[("MongoDB<br/>Atlas")]
    C --> M["User API Keys<br/>(localStorage)"]
    F --> N["ImageKit CDN<br/>(Images)"]
    
    style B fill:#4A90E2
    style E fill:#FF6B6B
    style I fill:#7C3AED
    style K fill:#10B981

Complete System Architecture:

flowchart LR
    subgraph Client["CLIENT LAYER"]
        FE["Frontend<br/>React 18 + TS<br/>Vercel"]
      AD["Admin Panel<br/>React + JS<br/>Vercel"]
    end
    
    subgraph API["API LAYER (Render)"]
        BE["Express.js<br/>Helmet + CORS<br/>Rate Limiter"]
    end
    
    subgraph Data["DATA & SERVICES"]
        DB[("MongoDB Atlas<br/>Database")]
        IK["ImageKit CDN<br/>Images"]
        FC["Firecrawl API<br/>Web Scraping<br/>Multi-source"]
        AI["AI Models<br/>NVIDIA NIM + GPT-4.1<br/>Ranking & Insights"]
        EMAIL["Brevo SMTP<br/>Email Service"]
    end
    
    FE -->|Axios| BE
    AD -->|Axios| BE
    BE -->|JWT Auth| DB
    BE -->|Upload| IK
    BE -->|Scrape| FC
    BE -->|Rank Props| AI
    BE -->|Send Mail| EMAIL
    
    style Client fill:#E8F4F8
    style API fill:#F0E8FF
    style Data fill:#FFF4E8

💻 Tech Stack

Frontend

Backend

AI & Infrastructure

🚀 Getting Started

Prerequisites

• Node.js 18+ and npm 8+
• MongoDB Atlas free account (or local MongoDB)
• ImageKit free account (10GB free tier)
• Brevo free SMTP account (for email notifications)

1. Clone the Repository

git clone https://github.com/AAYUSH412/Real-Estate-Website.git
cd Real-Estate-Website
Install dependencies per app:
cd backend && npm install
cd ../frontend && npm install
cd ../admin && npm install

cd backend
npm install
cp .env.example .env.local

# Essential Configuration (Required)
MONGO_URI=mongodb+srv://username:[email protected]/buildestate?retryWrites=true&w=majority
JWT_SECRET=your_super_secure_jwt_secret_here  # Generate with: openssl rand -base64 32
[email protected]
ADMIN_PASSWORD=your_secure_admin_password
Email Service (Brevo SMTP - Free tier available)
SMTP_USER=your_brevo_smtp_login
SMTP_PASS=your_brevo_smtp_password
[email protected]
BREVO_API_KEY=your_brevo_api_key
Frontend URL (for CORS + password reset emails)
WEBSITE_URL=http://localhost:5173
FRONTEND_URL=http://localhost:5173
ADMIN_URL=http://localhost:5174
LOCAL_URLS=http://localhost:5173,http://localhost:5174,http://localhost:4000
Optional: Image Storage (ImageKit - Free 10GB tier)
IMAGEKIT_PUBLIC_KEY=public_your_imagekit_public_key
IMAGEKIT_PRIVATE_KEY=private_your_imagekit_private_key
IMAGEKIT_URL_ENDPOINT=https://ik.imagekit.io/your_imagekit_id
Optional: AI Services (for AI Property Hub)
Users can provide their own keys via frontend, these are server fallbacks
FIRECRAWL_API_KEY=fc-your_firecrawl_api_key
GITHUB_MODELS_API_KEY=github_pat_your_github_token

npm run dev   # Starts backend on http://localhost:4000

cd ../frontend
npm install
cp .env.example .env.local

# Backend API URL
VITE_API_BASE_URL=http://localhost:4000
Feature flags
VITE_ENABLE_AI_HUB=true

npm run dev   # Starts frontend on http://localhost:5173

cd ../admin
npm install
cp .env.example .env.local

# Backend API URL (must match your backend)
VITE_BACKEND_URL=http://localhost:4000

npm run dev   # Starts admin panel on http://localhost:5174

🔌 API Endpoints

🌐 Deployment

📖 For detailed deployment instructions, see DEPLOYMENT.md

🚀 Quick Deploy (5 minutes):

Live Deployments

• 🌐 Frontend: buildestate.vercel.app (Vercel)
• ⚙️ Backend: real-estate-website-backend-zfu7.onrender.com (Render)

VITE_API_BASE_URL=https://your-backend-domain.onrender.com
   VITE_ENABLE_AI_HUB=false  # Disable for production (users provide own keys)
   VITE_SITE_URL=https://your-domain.vercel.app
   [email protected]

NODE_ENV=production
   MONGO_URI=your_mongodb_atlas_uri
   JWT_SECRET=your_secure_jwt_secret
   [email protected]
   ADMIN_PASSWORD=your_secure_password
   WEBSITE_URL=https://your-frontend.vercel.app
  FRONTEND_URL=https://your-frontend.vercel.app
  ADMIN_URL=https://your-admin.vercel.app
  LOCAL_URLS=
   # ... add other variables as needed

VITE_BACKEND_URL=https://your-backend.onrender.com

🔧 Alternative Deployment Options:

• Backend: Heroku, Railway, DigitalOcean App Platform, AWS/Google Cloud
• Frontend: Netlify, GitHub Pages, Surge.sh
• Database: Local MongoDB, DigitalOcean MongoDB, AWS DocumentDB

📂 Project Structure

Real-Estate-Website/
├── frontend/          → User-facing website (React + TypeScript + Vite)
├── admin/             → Admin dashboard (React + Vite)
├── backend/           → REST API server (Node.js + Express)
├── Image/             → README screenshots
└── .github/           → Issue templates, PR template, CODEOWNERS

├── components/
│   ├── ai-hub/            → AI Property Hub (search form, results, trends)
│   ├── common/            → Navbar, Footer, SEO, PageTransition
│   ├── home/              → Homepage sections
│   ├── properties/        → Filter sidebar, property cards
│   ├── property-details/  → Gallery, amenities, booking form
│   ├── about/             → About page sections
│   └── contact/           → Contact page sections
├── contexts/              → AuthContext (JWT state management)
├── hooks/                 → useSEO
├── pages/                 → All pages (lazy loaded via React.lazy)
└── services/              → api.ts (Axios client + API key injection)

├── config/         → MongoDB, ImageKit, Nodemailer config
├── controller/     → Route handlers (property, appointment, AI search)
├── middleware/      → JWT auth, Multer uploads, stats tracking, request transform
├── models/         → Mongoose schemas (Property, User, Appointment, Stats)
├── routes/         → Express route definitions
├── services/
│   ├── firecrawlService.js  → Smart 99acres scraping (30+ cities, URL construction, retry logic)
│   └── aiService.js         → GPT-4.1 property analysis + location trends
├── utils/          → AI response validation & safe parsing
└── server.js       → Entry point (Helmet, CORS, rate limiting)

├── components/     → Login, Sidebar, ProtectedRoute, modals
├── config/         → Property types, amenities constants
├── contexts/       → AuthContext (admin JWT state)
└── pages/          → Dashboard, PendingListings (review queue), List,
                      Users, UserDetails, Appointments, AIModels,
                      ActivityLogs, Add, Update

📜 Available Scripts

| Directory | Command | Description | |---|---|---| | backend/ | npm run dev | Start with nodemon (auto-reload) | | backend/ | npm start | Start production server | | frontend/ | npm run dev | Start Vite dev server | | frontend/ | npm run build | Production build | | admin/ | npm run dev | Start Vite dev server | | admin/ | npm run build | Production build |

🤝 Contributing

Contributions are welcome! Please read the Contributing Guide first.

# 1. Fork the repository
2. Create your branch
git checkout -b feature/your-feature
3. Commit your changes
git commit -m "feat: add your feature"
4. Push and open a PR
git push origin feature/your-feature

See also: Code of Conduct · Security Policy

📝 License

MIT License — see LICENSE for details.

👨‍💻 Author

Aayush Vaghela

If this project helped you, please give it a ⭐