- Added `cache-configuration.md` under `docs/guides`:
- Detailed multi-level cache system (hot, warm, cold) overview.
- Explained new adaptive tuning capabilities:
- Memory-based adjustments across Node.js, Browser, and Worker environments.
- Dynamic sizing for read-heavy/write-heavy workloads.
- Environment-specific configurations for optimal caching.
- Included best practices for large datasets, memory-constrained and read-only environments.
- Added monitoring and advanced manual tuning instructions.
- Modified `cacheManager.ts`:
- Introduced `environmentConfig` for tailored per-environment cache settings.
- Enhanced auto-tuning with support for dynamic memory detection and cache hit/miss ratio.
- Added fine-grained tuning for eviction thresholds, TTLs, and batch sizes based on workload characteristics.
- Improved adaptive tuning with async memory detection and detailed cache statistics tracking.
**Purpose**: Provide developers with detailed guidance and dynamic tools for optimizing Brainy's cache system, ensuring better performance across diverse environments and workloads.
David Snelling
69f8b999ea