Response Module Refactoring Summary

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The `@packages/dlm/response/` module has been enhanced and refactored to improve performance, maintainability, type safety, and developer experience while maintaining full backward compatibility. #### 1. **config.py** - Centralized Configuration Management - `ResponseConfig`: Main configuration container - `TokenConfig`: Token limit settings - `IRCPConfig`: I-RCP propagation parameters - `ContextArchivalConfig`: Context archival settings - `ContextReorderingConfig`: Context reordering options - `SynthesisTechniqueConfig`: Synthesis technique parameters - **Presets**: `create_default()`, `create_performance_optimized()`, `create_quality_optimized()` #### 2. **validators.py** - Comprehensive Input Validation - `ValidationError`: Custom exception with detailed messages - `ContentValidator`: Validates Content objects and text - `CoordinateValidator`: Validates ChainCoordinate objects - `ChainTypeValidator`: Validates chain types (system/assistant/user) - `ConversationDataValidator`: Validates conversation data structures - `ParameterValidator`: Validates numeric and enum parameters - `EmbeddingValidator`: Validates embeddings and similarity scores #### 3. **utils.py** - Performance Utilities - `LRUCache[K, V]`: Generic LRU cache with TTL support - `EmbeddingCache`: Specialized cache for text embeddings with MD5 hashing - `BatchProcessor`: Batch processing utility for operations - `AttentionWeightCache`: Specialized cache for I-RCP attention weights - `cosine_similarity_batch()`: Vectorized similarity computation - `normalize_coordinates()`: Coordinate normalization - `compute_coordinate_distance()`: Distance computation - `memoize_with_ttl()`: Function memoization decorator #### 4. **embedding_provider.py** - Enhanced Embedding Interface - `EmbeddingProviderProtocol`: Protocol for embedding providers - `BaseEmbeddingProvider`: Abstract base with caching and batching - `SimpleEmbeddingProvider`: Wrapper for existing embedding functions - Features: - Automatic caching with configurable capacity and TTL - Batch processing for efficiency - Advanced similarity computation with I-RCP support - Cache statistics tracking

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