Context Compression Techniques

Implement context compression techniques to fit more information in LLM context windows.

## Current Context Usage
{{context_usage}}

## Content Types
{{content_types}}

## Quality Requirements
{{quality_requirements}}

Implement compression strategies:

```python
class ContextCompressor:
    def summarize_documents(self, docs: List[str], target_ratio: float) -> List[str]:
        """Abstractive summarization"""
        pass
    
    def extract_key_sentences(self, doc: str, query: str, k: int) -> str:
        """Query-focused extraction"""
        pass
    
    def compress_dialogue(self, history: List[Message], keep_recent: int) -> List[Message]:
        """Dialogue compression"""
        pass
```

Techniques to implement:
- LLMLingua-style compression
- Query-aware summarization
- Hierarchical compression
- Token-level pruning

Include quality evaluation methodology.