# Setup Notes & Architecture

## Environment Variables Reference

### Backend (.env)
```bash
# Required
ALPHA_VANTAGE_API_KEY=your_key      # Get from alphavantage.co
OPENROUTER_API_KEY=your_key         # Get from openrouter.ai

# Database
DATABASE_URL=postgresql://postgres:postgres@localhost:5432/gold_trading_db

# Optional - defaults work fine
APP_ENV=development
DEBUG=True
CORS_ORIGINS=http://localhost:3000,http://127.0.0.1:3000
HOST=0.0.0.0
PORT=8000
```

### Frontend (.env)
```bash
# Required - points to backend API
VITE_API_URL=http://localhost:8000/api

# Optional - only if you want direct frontend calls (not recommended)
VITE_ALPHA_VANTAGE_API_KEY=your_key
```

## Architecture Overview

```
┌─────────────────────────────────────────────────────────────┐
│                     Browser (Port 3000)                      │
│  ┌────────────┐  ┌─────────────┐  ┌──────────────────────┐ │
│  │   Chart    │  │ Trade Panel │  │  Portfolio Tracker   │ │
│  │ Component  │  │  Component  │  │     Component        │ │
│  └────────────┘  └─────────────┘  └──────────────────────┘ │
│         │                │                    │              │
│         └────────────────┴────────────────────┘              │
│                          │                                   │
│                     API Service                              │
│                          │                                   │
└──────────────────────────┼───────────────────────────────────┘
                           │ HTTP/REST
                           ▼
┌─────────────────────────────────────────────────────────────┐
│              FastAPI Backend (Port 8000)                     │
│  ┌─────────────┐  ┌──────────────┐  ┌──────────────────┐  │
│  │  /api/market│  │ /api/trading │  │   /api/ai        │  │
│  │  endpoints  │  │  endpoints   │  │  endpoints       │  │
│  └─────────────┘  └──────────────┘  └──────────────────┘  │
│         │                │                    │              │
│         ▼                ▼                    ▼              │
│  ┌─────────────┐  ┌──────────────┐  ┌──────────────────┐  │
│  │ Alpha       │  │ In-memory    │  │  OpenRouter      │  │
│  │ Vantage     │  │ Trading      │  │  Service         │  │
│  │ Service     │  │ State (MVP)  │  │  (Claude 3.5)    │  │
│  └─────────────┘  └──────────────┘  └──────────────────┘  │
└─────────────────────────────────────────────────────────────┘
         │                                      │
         ▼                                      ▼
┌──────────────────┐              ┌────────────────────────┐
│  Alpha Vantage   │              │     OpenRouter API      │
│      API         │              │  (Claude 3.5 Sonnet)   │
│  (Market Data)   │              │   (AI Analysis)         │
└──────────────────┘              └────────────────────────┘

         │
         ▼
┌──────────────────────────────────┐
│   PostgreSQL Database             │
│   (Port 5432 - Docker)           │
│  ┌──────────────────────────────┐│
│  │ Tables (for Phase 2):        ││
│  │  - simulations               ││
│  │  - trades                    ││
│  │  - positions                 ││
│  │  - ai_analysis_logs          ││
│  └──────────────────────────────┘│
└──────────────────────────────────┘
```

## Data Flow

### 1. Loading Historical Data
```
Browser → GET /api/market/gold/history
         ↓
FastAPI → Alpha Vantage Service
         ↓
Alpha Vantage API (XAU/USD daily data)
         ↓
Transform to PriceData[]
         ↓
Calculate SMA(50) in frontend
         ↓
Render with Lightweight Charts
```

### 2. Executing Trade
```
User clicks "Buy" → POST to local state (MVP)
                   ↓
Update portfolio state
                   ↓
Recalculate P&L
                   ↓
Update UI components
```

### 3. AI Analysis
```
User clicks "AI Analysis" → Gather context:
                           - Last 50 price points
                           - Current indicators
                           - Current price
                           ↓
POST /api/ai/analyze
                           ↓
OpenRouter Service → Claude 3.5 Sonnet
                           ↓
Parse JSON response
                           ↓
Return AIAnalysisResponse
                           ↓
Display in AIAnalysisPanel
```

## Technology Choices Explained

### Why Lightweight Charts?
- **Optimized for trading:** Built by TradingView specifically for financial data
- **Performance:** Can handle 10,000+ candles smoothly
- **Size:** Only 35KB gzipped
- **Free:** Apache 2.0 license, no restrictions

### Why Alpha Vantage?
- **Free tier:** 500 calls/day is plenty for development
- **Forex data:** Includes XAU/USD (gold) out of the box
- **Reliability:** Industry-standard data provider
- **No credit card:** Instant API key

### Why OpenRouter + Claude?
- **Best reasoning:** Claude 3.5 Sonnet > GPT-4o for complex analysis
- **Pay-per-use:** No monthly subscription
- **Unified API:** Access 400+ models through one endpoint
- **OpenAI-compatible:** Easy migration if needed

### Why FastAPI?
- **Speed:** 3x faster than Flask for async operations
- **Type safety:** Pydantic schemas ensure data validation
- **Auto docs:** Swagger UI at /docs
- **Modern:** Async/await throughout

### Why PostgreSQL?
- **Reliability:** Production-grade ACID compliance
- **Time-series:** Works well with TimescaleDB extension (future)
- **JSON support:** Flexible for evolving schemas
- **Free:** Open source forever

## MVP vs. Future Phases

### MVP (Current) - In-Memory State
```python
# backend/app/api/trading.py
simulation_state = {
    "cash": 100000.0,
    "position": None,
    "trades": []
}
```

**Pros:**
- Fast to implement
- No database setup issues
- Perfect for testing

**Cons:**
- Resets on server restart
- Single user only
- No historical analysis

### Phase 2 - Database Persistence
```python
# Future implementation
@router.post("/execute")
async def execute_trade(trade: TradeCreate, db: Session = Depends(get_db)):
    # Save to PostgreSQL
    db_trade = Trade(**trade.dict())
    db.add(db_trade)
    db.commit()
    return db_trade
```

**Benefits:**
- Persistent across restarts
- Multi-user support
- Historical backtesting
- Advanced analytics

## API Rate Limits

### Alpha Vantage Free Tier
- **5 calls/minute**
- **500 calls/day**
- **Strategy:** Cache aggressively, use `compact` output for development

### OpenRouter (Pay-per-use)
- **No rate limit** (reasonable use)
- **Cost per analysis:** ~$0.01-0.05
- **Strategy:** User-initiated only, no auto-refresh

## Security Considerations

### Current (Development)
- API keys in `.env` files
- CORS restricted to localhost
- No authentication

### Production Requirements
- **Environment variables** from secrets manager (AWS Secrets Manager, etc.)
- **HTTPS** for all connections
- **JWT authentication** for users
- **Rate limiting** per IP/user
- **API key rotation** policy
- **Input validation** on all endpoints

## Performance Metrics

### Expected Response Times
- Market data endpoint: 200-500ms (Alpha Vantage)
- Trading execute: <10ms (in-memory)
- AI analysis: 3-10 seconds (Claude API)

### Optimization Opportunities
1. **Redis caching** for market data (reduce API calls)
2. **WebSocket** for real-time updates (future)
3. **CDN** for frontend static assets
4. **Database indexes** on frequently queried fields
5. **Connection pooling** for PostgreSQL

## Monitoring & Debugging

### Backend Logs
```bash
# Watch backend logs
cd backend
source venv/bin/activate
python -m app.main

# Look for:
# - API call patterns
# - Error traces
# - Response times
```

### Frontend Console
```javascript
// Browser console (F12)
// Network tab shows API calls
// Console shows React errors
```

### Database Queries
```bash
# Connect to PostgreSQL
docker exec -it gold_trading_db psql -U postgres -d gold_trading_db

# Useful commands:
\dt                    # List tables
\d simulations        # Describe table
SELECT COUNT(*) FROM trades;
```

## Common Development Workflows

### Adding a New Indicator
1. Create calculation function in `frontend/src/utils/indicators.ts`
2. Add to chart component state
3. Create line series in chart
4. Add toggle in UI

### Adding a New API Endpoint
1. Define schema in `backend/app/schemas/schemas.py`
2. Create route in appropriate `backend/app/api/*.py`
3. Add service method if needed
4. Update frontend API service
5. Create React hook for data fetching

### Database Schema Changes
1. Update model in `backend/app/models/models.py`
2. Create Alembic migration (future)
3. Run migration
4. Update schemas and routes

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This completes the comprehensive setup and architecture documentation!
