Beyond Prompt Caching: 5 More Things You Should Cache in RAG Pipelines

1. 1Identify bottlenecks in the RAG pipeline
2. 2Determine which layers to cache, such as query embeddings or full query-response pairs
3. 3Implement caching mechanisms for the chosen layers
4. 4Monitor and adjust caching strategies for optimal performance
5. 5Evaluate the impact of caching on model efficiency and accuracy

ML engineers and researchers can benefit from caching to optimize RAG pipeline efficiency, while data scientists can apply these techniques to improve model performance

💡 Caching multiple layers in RAG pipelines can significantly improve model efficiency and accuracy

🚀 Boost RAG pipeline performance by caching more than just prompts!