Retrieval Diversity Optimizer

Optimize retrieval diversity to improve RAG response quality.

## Current Retrieval Behavior
{{current_behavior}}

## Diversity Issues
{{diversity_issues}}

## Quality Goals
{{quality_goals}}

Implement diversity optimization:

```python
class DiversityOptimizer:
    def diversify_mmr(self, query_embedding: List[float], candidates: List[Document], lambda_param: float, k: int) -> List[Document]:
        """Maximal Marginal Relevance"""
        pass
    
    def diversify_clustering(self, candidates: List[Document], k: int, clusters: int) -> List[Document]:
        """Cluster-based selection"""
        pass
    
    def diversify_aspect(self, query: str, candidates: List[Document], aspects: List[str]) -> List[Document]:
        """Aspect-based coverage"""
        pass
```

Include:
- Lambda parameter tuning
- Diversity metrics (ILS, coverage)
- Quality vs diversity trade-off analysis
- A/B test design