# Real-Time Inference Guide

## 🎯 Overview

Real-time inference mode runs your trained model on **live streaming data** from the DataProvider, updating charts every second and displaying model predictions in real-time.

---

##  Starting Real-Time Inference

### Step 1: Select Model
Choose the model you want to run from the dropdown in the training panel.

### Step 2: Click "Start Live Inference"
- Button turns red: "Stop Inference"
- Live mode banner appears at top
- Charts begin updating every second
- Model predictions displayed

### Visual Indicators
- **🔴 LIVE banner** at top of page
- **Green status box** in training panel
- **Update counter** showing number of updates
- **Signal markers** on charts (🔵 BUY, 🔴 SELL)

---

## 📊 What Updates in Real-Time

### Charts (Every 1 Second)
- **All 4 timeframes** update with latest data
- **Candlesticks** show new price action
- **Volume bars** update with new volume
- **Smooth updates** without page refresh

### Model Signals
- **Latest prediction** displayed (BUY/SELL/HOLD)
- **Confidence level** shown as percentage
- **Signal markers** added to charts
- **Last 10 signals** kept visible

### Data Source
- Uses **DataProvider's cached data**
- Same data as main trading system
- Updates from exchange feeds
- 1-second resolution

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## 🎨 Visual Elements

### Live Mode Banner
```
🔴 LIVE | Real-Time Inference Active
Charts updating with live data every second
[X updates]
```

### Signal Markers on Charts
- **🔵 BUY** - Green marker with arrow
- **🔴 SELL** - Red marker with arrow
- **Timestamp** - When signal was generated
- **Price** - Price at signal time

### Training Panel Status
```
🔴 LIVE
Signal: BUY
Confidence: 75.3%
Charts updating every 1s
```

---

## 🛑 Stopping Real-Time Inference

### Click "Stop Inference"
- Live mode banner disappears
- Charts stop updating
- Signal markers remain visible
- Can review final signals

### What Happens
- Inference loop terminates
- Chart updates stop
- Last 100 signals saved
- Model remains loaded

---

## 📈 Monitoring Performance

### Watch For
- **Signal frequency** - How often model signals
- **Confidence levels** - Higher is better (>70%)
- **Signal accuracy** - Do signals make sense?
- **False positives** - Signals that shouldn't happen

### Good Signs
-  Signals at key levels (support/resistance)
-  High confidence (>70%)
-  Signals match your analysis
-  Few false positives

### Warning Signs
-  Too many signals (every second)
-  Low confidence (<50%)
-  Random signals
-  Signals don't match patterns

---

## 🔧 Technical Details

### Update Frequency
- **Charts**: 1 second
- **Signals**: 1 second
- **Model inference**: 1 second

### Data Flow
```
DataProvider (Live Data)
    ↓
Latest Market State (4 timeframes)
    ↓
Model Inference
    ↓
Prediction (Action + Confidence)
    ↓
Update Charts + Display Signal
```

### Performance
- **Latency**: ~100-200ms per update
- **CPU Usage**: Moderate (model inference)
- **Memory**: Stable (no leaks)
- **Network**: Minimal (uses cached data)

---

## 💡 Tips & Tricks

### Tip 1: Watch Multiple Timeframes
All 4 charts update simultaneously. Watch for:
- Alignment across timeframes
- Divergences between timeframes
- Pattern confirmation

### Tip 2: Monitor Confidence
- **>80%**: Very strong signal
- **70-80%**: Strong signal
- **50-70%**: Moderate signal
- **<50%**: Weak signal (ignore)

### Tip 3: Compare with Annotations
- Do live signals match your annotations?
- Are signals at similar price levels?
- Is timing similar to your trades?

### Tip 4: Test Different Models
- Try CNN vs DQN vs Transformer
- Compare signal quality
- Note which performs best

### Tip 5: Use for Validation
- After training, test with live inference
- Verify model learned correctly
- Check for overfitting

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## 🐛 Troubleshooting

### Charts Not Updating
**Issue**: Live mode active but charts frozen

**Solutions**:
- Check browser console for errors
- Verify DataProvider has live data
- Refresh page and restart inference
- Check network tab for failed requests

### No Signals Generated
**Issue**: Status shows "HOLD" constantly

**Solutions**:
- Model may need more training
- Check model is loaded correctly
- Verify market conditions (model may correctly hold)
- Try different model

### Signals Too Frequent
**Issue**: Signal every second

**Solutions**:
- Model may be overtrained
- Need more negative examples in training
- Adjust confidence threshold
- Retrain with better annotations

### Performance Issues
**Issue**: Browser slow/laggy

**Solutions**:
- Close other tabs
- Reduce number of visible timeframes
- Stop inference when not needed
- Clear browser cache

---

## 📊 Example Session

### Scenario: Testing CNN After Training

**1. Preparation**
- Trained CNN on 20 breakout annotations
- Model learned breakout patterns
- Ready to test on live data

**2. Start Inference**
- Select "StandardizedCNN"
- Click "Start Live Inference"
- 🔴 LIVE banner appears
- Charts begin updating

**3. Observation (5 minutes)**
- Charts update smoothly
- Model generates 2 BUY signals
- Both at resistance breakouts
- Confidence: 78% and 82%

**4. Validation**
- Signals match training patterns
- Timing is precise
- No false positives
- Model learned correctly 

**5. Stop Inference**
- Click "Stop Inference"
- Review signal history
- Model performs well
- Ready for production

---

## 🎯 Best Practices

### Before Starting
-  Train model first
-  Verify model loaded
-  Check DataProvider has data
-  Close unnecessary tabs

### During Inference
-  Monitor all timeframes
-  Note signal quality
-  Check confidence levels
-  Compare with your analysis

### After Stopping
-  Review signal history
-  Note performance
-  Identify improvements
-  Adjust training if needed

---

##  Summary

Real-time inference provides:

 **Live chart updates** (1/second)  
 **Model predictions** in real-time  
 **Signal markers** on charts  
 **Confidence levels** displayed  
 **Performance monitoring** built-in  

Use it to:
- **Validate training** - Check model learned correctly
- **Test models** - Compare different models
- **Monitor performance** - Track signal quality
- **Debug issues** - Identify problems

**Result**: Confidence that your model works correctly before deploying to production! 🎯