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RAG-Driven Generative AI

You're reading from   RAG-Driven Generative AI Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781836200918
Length 334 pages
Edition 1st Edition
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Toc

Table of Contents (14) Chapters Close

Preface 1. Why Retrieval Augmented Generation? FREE CHAPTER 2. RAG Embedding Vector Stores with Deep Lake and OpenAI 3. Building Index-Based RAG with LlamaIndex, Deep Lake, and OpenAI 4. Multimodal Modular RAG for Drone Technology 5. Boosting RAG Performance with Expert Human Feedback 6. Scaling RAG Bank Customer Data with Pinecone 7. Building Scalable Knowledge-Graph-Based RAG with Wikipedia API and LlamaIndex 8. Dynamic RAG with Chroma and Hugging Face Llama 9. Empowering AI Models: Fine-Tuning RAG Data and Human Feedback 10. RAG for Video Stock Production with Pinecone and OpenAI 11. Other Books You May Enjoy
12. Index
Appendix

Summary

This chapter explored the transformative impact of index-based search on RAG and introduced a pivotal advancement: full traceability. The documents become nodes that contain chunks of data, with the source of a query leading us all the way back to the original data. Indexes also increase the speed of retrievals, which is critical as the volume of datasets increases. Another pivotal advance is the integration of technologies such as LlamaIndex, Deep Lake, and OpenAI, which are emerging in another era of AI. The most advanced AI models, such as OpenAI GPT-4o, Hugging Face, and Cohere, are becoming seamless components in a RAG-driven generative AI pipeline, like GPUs in a computer.

We started by detailing the architecture of an index-based RAG generative AI pipeline, illustrating how these sophisticated technologies can be seamlessly integrated to boost the creation of advanced indexing and retrieval systems. The complexity of AI implementation is changing the way we organize...

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