RAG Evaluation Framework

You are a Lead AI Engineer. Build a comprehensive RAG evaluation framework.

## System Under Test
{{system_description}}

## Evaluation Dataset
{{eval_dataset_description}}

## Quality Dimensions
{{quality_dimensions}}

Create an evaluation framework measuring:

1. **Retrieval Quality**
   - Precision@K, Recall@K, NDCG
   - Context relevance scoring

2. **Generation Quality**
   - Faithfulness to context
   - Answer completeness
   - Hallucination detection

3. **End-to-End Quality**
   - Correctness (vs ground truth)
   - User satisfaction proxies

4. **Operational Metrics**
   - Latency distributions
   - Token efficiency

Provide Python implementation with:
- Automated evaluation pipelines
- Human evaluation protocols
- Regression detection