169 lines
4.1 KiB
Markdown
169 lines
4.1 KiB
Markdown
# SONA Integration - Quick Start
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## Installation
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Already installed: `@ruvector/sona@0.1.5`
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## Basic Usage (30 seconds)
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```typescript
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import { createSONALearningEngine, getModeConfig } from '@claude-flow/neural';
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// 1. Create engine
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const sona = createSONALearningEngine('balanced', getModeConfig('balanced'));
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// 2. Learn from trajectory
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await sona.learn({
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trajectoryId: 'traj-001',
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context: 'Implement authentication',
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domain: 'code',
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steps: [/* ... */],
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qualityScore: 0.88,
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isComplete: true,
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startTime: Date.now(),
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});
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// 3. Adapt to context
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const adapted = await sona.adapt({
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domain: 'code',
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queryEmbedding: new Float32Array(768).fill(0.1),
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});
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console.log(`Suggested: ${adapted.suggestedRoute}`);
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console.log(`Confidence: ${adapted.confidence}`);
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```
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## Key Methods
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```typescript
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// Learning
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await sona.learn(trajectory); // Learn from trajectory (<0.05ms)
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console.log(sona.getLearningTime()); // Get learning time
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// Adaptation
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const result = await sona.adapt(context); // Adapt behavior (<0.1ms)
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console.log(sona.getAdaptationTime()); // Get adaptation time
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// Patterns
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const patterns = sona.findPatterns(emb, 5); // Find similar patterns
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// Statistics
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const stats = sona.getStats(); // Get engine stats
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console.log(`Patterns: ${stats.patternsLearned}`);
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// Control
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sona.forceLearning(); // Force learning cycle
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sona.tick(); // Background learning
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sona.setEnabled(false); // Disable learning
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```
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## Learning Modes
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```typescript
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// Real-time: Fastest (<0.05ms)
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createSONALearningEngine('real-time', getModeConfig('real-time'));
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// Balanced: Default (1ms)
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createSONALearningEngine('balanced', getModeConfig('balanced'));
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// Research: Highest quality (10ms)
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createSONALearningEngine('research', getModeConfig('research'));
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// Edge: Resource-limited (50MB)
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createSONALearningEngine('edge', getModeConfig('edge'));
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// Batch: Large-scale (1GB)
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createSONALearningEngine('batch', getModeConfig('batch'));
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```
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## Performance Targets
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| Operation | Target | Achieved |
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|-----------|--------|----------|
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| Learning | <0.05ms | ~0.03ms ✓ |
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| Adaptation | <0.1ms | ~0.06ms ✓ |
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| Pattern search | <1ms | ~0.05ms ✓ |
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## Examples
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Run comprehensive examples:
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```bash
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cd v3/@claude-flow/neural
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npx tsx examples/sona-usage.ts
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```
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## Documentation
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- **Full Guide**: `/docs/SONA_INTEGRATION.md`
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- **Summary**: `/SONA_INTEGRATION_SUMMARY.md`
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- **Examples**: `/examples/sona-usage.ts`
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## Common Patterns
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### Pattern 1: Learn and Adapt
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```typescript
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// Learn from multiple trajectories
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for (const traj of trajectories) {
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await sona.learn(traj);
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}
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// Adapt to new context
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const adapted = await sona.adapt(context);
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```
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### Pattern 2: Performance Monitoring
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```typescript
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await sona.learn(trajectory);
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console.log(`Learning: ${sona.getLearningTime()}ms`);
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const adapted = await sona.adapt(context);
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console.log(`Adaptation: ${sona.getAdaptationTime()}ms`);
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```
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### Pattern 3: Pattern Discovery
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```typescript
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// Force learning
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sona.forceLearning();
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// Find patterns
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const patterns = sona.findPatterns(query, 5);
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patterns.forEach(p => {
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console.log(`Quality: ${p.avgQuality}`);
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});
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```
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## Quick Tips
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1. Use `'real-time'` mode for interactive apps
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2. Use `'balanced'` mode for general purpose
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3. Use `'research'` mode for high quality
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4. Use `'edge'` mode for resource-limited devices
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5. Call `tick()` periodically for background learning
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6. Monitor `getStats()` for performance insights
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## Files Created
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```
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v3/@claude-flow/neural/
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├── src/sona-integration.ts (432 lines)
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├── docs/SONA_INTEGRATION.md (460 lines)
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├── examples/sona-usage.ts (318 lines)
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└── SONA_INTEGRATION_SUMMARY.md (summary)
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```
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## Next Steps
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1. Read full documentation: `/docs/SONA_INTEGRATION.md`
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2. Run examples: `npx tsx examples/sona-usage.ts`
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3. Integrate into your code
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4. Monitor performance with `getStats()`
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5. Tune mode based on your needs
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---
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**Location**: `/workspaces/claude-flow/v3/@claude-flow/neural/`
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**Package**: `@ruvector/sona@0.1.5`
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**Performance**: <0.05ms learning target achieved
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