Design a comprehensive caching layer for a RAG system. ## RAG Pipeline {{rag_pipeline}} ## Traffic Patterns {{traffic_patterns}} ## Cache Infrastructure {{cache_infrastructure}} Design multi-level caching: **Level 1: Query Cache** - Exact query match - Semantic similarity cache - TTL and invalidation strategy **Level 2: Embedding Cache** - Pre-computed query embeddings - Document embeddings - Cache key design **Level 3: Retrieval Result Cache** - Query-to-results mapping - Partial result caching - Freshness vs latency trade-off **Level 4: LLM Response Cache** - Prompt-response pairs - Context-aware caching - Output variability handling **Cache Orchestration** - Cache lookup order - Cache population strategy - Metrics and monitoring Provide implementation architecture and expected hit rates.
Caching Layer Design for RAG
U
@
Design a multi-level caching layer for RAG covering query, embedding, retrieval, and response caches with orchestration strategy.
29 copies0 forks
Details
Category
AnalysisUse Cases
Cache designRAG optimizationLatency reduction
Works Best With
claude-sonnet-4-20250514gpt-4o
Created Shared