wifi-densepose/npm/packages/agentic-synth/training/QUICK_START.md

# DSPy.ts Integration - Quick Start Guide

## 🚀 5-Minute Start

### 1. Install & Setup

```bash
cd /home/user/ruvector/packages/agentic-synth

# Set API key
export OPENAI_API_KEY="sk-your-key-here"
```

### 2. Run the Example

```bash
# Run the built-in example
npx tsx training/dspy-real-integration.ts
```

### 3. Use in Your Code

```typescript
import { DSPyAgenticSynthTrainer } from './training/dspy-real-integration.js';

// Define schema
const schema = {
  type: 'object',
  properties: {
    name: { type: 'string' },
    age: { type: 'number' },
    email: { type: 'string' }
  }
};

// Training examples
const examples = [{
  input: JSON.stringify(schema),
  output: JSON.stringify({ name: 'Alice', age: 28, email: 'alice@example.com' }),
  quality: 0.9
}];

// Create & initialize trainer
const trainer = new DSPyAgenticSynthTrainer({
  models: ['gpt-3.5-turbo'],
  optimizationRounds: 5,
  minQualityScore: 0.8
});

await trainer.initialize();

// Train with optimization
const result = await trainer.trainWithOptimization(schema, examples);
console.log(`Improvement: ${result.improvements.improvement}%`);

// Generate optimized data
const data = await trainer.generateOptimizedData(100, schema);
console.log(`Generated ${data.length} optimized samples`);
```

## 📋 Key Configuration Options

```typescript
{
  models: ['gpt-3.5-turbo'],     // Models to use
  optimizationRounds: 5,          // Number of optimization iterations
  minQualityScore: 0.8,          // Quality threshold
  batchSize: 10,                 // Samples per iteration
  maxExamples: 50,               // Max training examples
  enableCaching: true,           // Cache results
  hooks: {                       // Event callbacks
    onIterationComplete: (iter, metrics) => { },
    onOptimizationComplete: (result) => { }
  }
}
```

## 🎯 Main Methods

| Method | Purpose |
|--------|---------|
| `initialize()` | Setup DSPy.ts models |
| `trainWithOptimization(schema, examples)` | Train with auto-optimization |
| `generateOptimizedData(count, schema?)` | Generate quality data |
| `evaluateQuality(data)` | Assess data quality |
| `getStatistics()` | Get training stats |

## 📊 Expected Results

```
Initial Quality:  0.70-0.75
Optimized:        0.85-0.90
Improvement:      15-25%
Convergence:      3-5 rounds
Speed:            2-5s/iteration
```

## 🔧 Environment Variables

```bash
# Required for OpenAI models
export OPENAI_API_KEY="sk-..."

# Optional for Claude models
export ANTHROPIC_API_KEY="sk-ant-..."
```

## 📚 Files Reference

| File | Description |
|------|-------------|
| `dspy-real-integration.ts` | Main implementation (868 lines) |
| `DSPY_INTEGRATION_README.md` | Full documentation |
| `test-dspy-integration.ts` | Simple test |
| `INTEGRATION_COMPLETE.md` | Implementation summary |
| `QUICK_START.md` | This file |

## 🧪 Quick Test

```bash
# Test without API key (structure check only)
npx tsx training/test-dspy-integration.ts

# Test with API key (full test)
export OPENAI_API_KEY="sk-..."
npx tsx training/test-dspy-integration.ts
```

## ⚡ Common Patterns

### Monitor Progress

```typescript
trainer.on('status', msg => console.log('Status:', msg));
trainer.on('progress', ({current, total}) => {
  console.log(`Progress: ${current}/${total}`);
});
```

### Handle Errors

```typescript
trainer.on('error', error => {
  console.error('Training error:', error);
});
```

### Multi-Model Training

```typescript
const trainer = new DSPyAgenticSynthTrainer({
  models: [
    'gpt-3.5-turbo',              // Fast baseline
    'gpt-4',                      // High quality
    'claude-3-sonnet-20240229'   // Alternative
  ]
});
```

## 🎨 Example Schemas

### User Profile
```typescript
{
  type: 'object',
  properties: {
    userId: { type: 'string' },
    name: { type: 'string' },
    email: { type: 'string', format: 'email' },
    age: { type: 'number' }
  }
}
```

### E-commerce Product
```typescript
{
  type: 'object',
  properties: {
    productId: { type: 'string' },
    name: { type: 'string' },
    price: { type: 'number' },
    category: { type: 'string' }
  }
}
```

### Time Series
```typescript
{
  type: 'object',
  properties: {
    timestamp: { type: 'string', format: 'date-time' },
    metric: { type: 'string' },
    value: { type: 'number' }
  }
}
```

## 🐛 Troubleshooting

| Issue | Solution |
|-------|----------|
| API Key Error | Set `OPENAI_API_KEY` environment variable |
| Import Error | Check Node.js version >= 18 |
| Low Quality | Provide better training examples |
| Slow Performance | Reduce `batchSize` or use faster model |

## 📖 Learn More

- Full API Reference: `DSPY_INTEGRATION_README.md`
- Implementation Details: `INTEGRATION_COMPLETE.md`
- Source Code: `dspy-real-integration.ts`

## 💡 Pro Tips

1. **Start Simple**: Begin with one model and few rounds
2. **Good Examples**: Provide high-quality training examples (>0.8 score)
3. **Monitor Progress**: Use event hooks to track improvement
4. **Tune Threshold**: Adjust `minQualityScore` based on your needs
5. **Cache Results**: Enable caching for repeated runs

---

**Ready to go! Start with the example and customize from there.** 🚀