Advanced RAG: Query Optimisation and Context Compression

This is an Advanced Retrieval-Augmented Generation (RAG) tutorial! In this video, we dive deep into the techniques of query optimization and context compression to enhance the performance and accuracy of RAG models.

🚀 What You'll Learn:

🕹️Query Optimization: Techniques to refine your queries for better retrieval results, including the use of semantic search and relevance feedback to enhance the precision and recall of retrieved documents.

🕹️Context Compression: Methods to compress context without losing crucial information, such as using extractive summarization and dimensionality reduction to maintain essential content while reducing the input size.
Implementation Steps: Detailed, step-by-step instructions on implementing these techniques in your RAG model.

💡 Key Takeaways

🦾Learn how to enhance your RAG model’s query performance.

🤖Understand how to compress context efficiently to maintain model accuracy.

🦿Gain hands-on experience with practical examples and code walkthroughs.

Source Code: https://github.com/jay-ogayon/RAG-dem...