A personalized crypto investor dashboard that learns your preferences and serves daily AI-curated content — live prices, real news, an AI insight, and a fun meme. Built as a full-stack web application for the Moveo coding assignment.
- Auth & Security — Register/login with JWT. Forgot password flow with email reset via Resend.
- Onboarding — Short quiz to determine crypto interests, investor type, content preferences, and an avatar emoji.
- 8 Dynamic Widgets — Rendered in a responsive Masonry Layout, updated on every load:
- 📈 Coin Prices — Live data from CoinGecko (price + 24h change)
- 📰 Market News — Real posts from r/CryptoCurrency via Reddit API
- 🤖 AI Insight of the Day — LLM-generated tip (OpenRouter), personalized to your investor type and selected coins
- 😂 Fun Crypto Meme — Random image from r/cryptocurrencymemes
- 😨 Fear & Greed Index — Live market sentiment gauge (Alternative.me API)
- 🧮 Interactive ROI Calculator — Select a coin to dynamically calculate what a $1,000 investment 1 year ago is worth today
- 🖼️ Trending NFTs — Top NFT collections by 24h floor price change
- 🐳 Whale Alerts — Simulated massive on-chain crypto transfers
- Premium UI/UX — Glassmorphism cards, animated mesh background, skeleton loaders, and
react-hot-toastnotifications. - Dark / Light Mode — Toggle from any page; preference persisted to
localStorage; flicker-free via inline<head>script. - Price Alerts — Set per-coin price thresholds;
node-cronchecks every 10 min; Resend sends a styled HTML email when triggered. - Drag & Drop Customization — Reorder and resize (S/M/L) dashboard widgets in Profile; order and sizes persisted to the DB.
- Voting System (RLHF) — Thumbs up/down on every section. Votes are stored in the DB for future machine learning model improvements.
| Dark Dashboard | Light Dashboard |
 |
 |
| Profile & Widget Layout | Price Alerts Modal |
 |
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| Login Page | Email Alert Notification |
 |
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| Layer | Technology |
|---|---|
| Frontend | React (Vite) + Tailwind CSS v4 |
| Backend | Node.js + Express v5 |
| Database | PostgreSQL (Neon serverless) |
| Auth | JWT + bcrypt |
| Resend API | |
| Deployment | Vercel (frontend) + Render (backend) |
- Node.js 18+
- A Neon PostgreSQL database (free tier)
git clone https://github.com/Am1its/Crypto-advisor.git
cd Crypto-advisorBackend
cd server
cp .env.example .env # fill in your keys (see below)
npm install
npm run migrate # creates all tables
npm run dev # runs on http://localhost:3001Frontend
cd client
npm install
npm run dev # runs on http://localhost:5173Create server/.env based on server/.env.example:
PORT=3001
CLIENT_URL=http://localhost:5173
DATABASE_URL=postgresql://... # Neon connection string
JWT_SECRET=your_long_random_secret
COINGECKO_API_KEY= # free at coingecko.com/developers
OPENROUTER_API_KEY= # free at openrouter.ai
RESEND_API_KEY= # free at resend.com (optional — shows link on screen if missing)| Method | Endpoint | Auth | Description |
|---|---|---|---|
| POST | /api/auth/register |
— | Register, returns JWT |
| POST | /api/auth/login |
— | Login, returns JWT |
| POST | /api/auth/forgot-password |
— | Send password reset email |
| POST | /api/auth/reset-password |
— | Reset password via token |
| POST | /api/onboarding |
✓ | Save user preferences |
| GET | /api/dashboard |
✓ | Fetch all 8 widgets in parallel |
| POST | /api/votes |
✓ | Submit thumbs up/down |
| GET | /api/profile |
✓ | Get user + preferences |
| PUT | /api/profile |
✓ | Update name, preferences, widget sizes |
| PUT | /api/profile/password |
✓ | Change password |
| GET | /api/alerts |
✓ | List active price alerts |
| POST | /api/alerts |
✓ | Create a price alert |
| DELETE | /api/alerts/:id |
✓ | Deactivate a price alert |
| GET | /health |
— | Server health check |
| Service | Settings |
|---|---|
| Vercel | Root dir: client · Add env var VITE_API_URL=<your-render-url> |
| Render | Root dir: server · Build: npm install · Start: node server.js · Add all env vars |
The thumbs up/down votes (stored per user, per content item) create a naturally labeled dataset for future model improvements:
- Feature engineering — encode
(user_preferences, content_metadata)as vectors - Model — train a ranking model (
P(vote=up | user, content)) starting with logistic regression, graduating to a neural ranker as data grows - Re-ranking — surface content each user is most likely to upvote
- Retraining — weekly batch job on Render; deploy only if the new model beats baseline on a held-out set
- Cold start — new users fall back to global popularity until their vote history accumulates
The onboarding quiz provides a strong prior signal before any votes exist — mirroring how Netflix and Spotify bootstrap from explicit preferences before shifting to behavioral signals.
For the full interaction log and architecture notes see docs/AI_INTERACTIONS.md.