Self-Consistency Voting Aggregator

Implement a self-consistency voting system for improved LLM accuracy.

## Task Type
{{task_type}}

## Sample Size
{{num_samples}}

## Aggregation Goals
{{aggregation_goals}}

Build the voting system:

```python
class SelfConsistencyAggregator:
    def generate_samples(self, prompt: str, n: int, temperature: float) -> List[str]:
        """Generate diverse response samples"""
        pass
    
    def majority_vote(self, responses: List[str]) -> VoteResult:
        """Simple majority voting"""
        pass
    
    def weighted_vote(self, responses: List[str], confidences: List[float]) -> VoteResult:
        """Confidence-weighted voting"""
        pass
    
    def semantic_clustering(self, responses: List[str]) -> List[Cluster]:
        """Group semantically similar responses"""
        pass
    
    def extract_consensus(self, clusters: List[Cluster]) -> ConsensusResult:
        """Extract consensus from clusters"""
        pass
```

Include:
- Equivalence detection
- Uncertainty quantification
- Cost-accuracy trade-offs
- Adaptive sampling