Dynamic Retrieval Configuration

Build a system for dynamically configuring retrieval parameters based on query characteristics.

## Query Types
{{query_types}}

## Configuration Options
{{config_options}}

## Performance Targets
{{performance_targets}}

Implement dynamic configuration:

```python
class DynamicRetrievalConfig:
    def analyze_query(self, query: str) -> QueryProfile:
        """
        Profile includes:
        - Complexity level
        - Expected result type
        - Precision vs recall preference
        - Latency sensitivity
        """
        pass
    
    def generate_config(self, profile: QueryProfile) -> RetrievalConfig:
        """
        Configure:
        - top_k
        - similarity_threshold
        - reranking enabled
        - hybrid search weights
        """
        pass
    
    def learn_from_feedback(self, query: str, config: RetrievalConfig, success: bool) -> None:
        """Update configuration policy"""
        pass
```

Include:
- Query classification model
- Configuration policy learning
- Performance monitoring