Practical Guide to Prompt Compression: Essential Optimization for RAG-Based Applications

Are you looking to reduce costs by 10x to 20x while still maintaining the accuracy of your RAG-based applications? Prompt compression is an indispensable strategy for achieving this. It’s not just a cost-saving measure; it’s a necessity for efficient and effective application performance.

1. Introduction

In the evolving world of natural language processing, efficiency and precision are paramount. This tutorial delves into the practical application of prompt compression in RAG (Retrieval-Augmented Generation) based applications, highlighting its indispensable role in performance enhancement. LLMLingua, developed by Microsoft Research experts, is a standout in this sector.

2. What are Prompt Compression and LLMLingua?

Prompt compression is a technique used to make the retrieved context to language models more concise and focused. This is particularly beneficial in RAG-based applications where efficient information retrieval and processing are crucial.

LLMLingua, a Microsoft innovation, optimizes the efficiency of RAG (Retrieval-Augmented Generation) through prompt compression. This method uses smaller models like GPT2-small or LLaMA-7B to identify and…