Summary

In this chapter, we explored customizing and enhancing RAG workflows with LlamaIndex. We covered techniques to leverage open source LLMs such as Zephyr using tools such as LM Studio, offering cost-effective and privacy-focused alternatives to commercial models. The chapter discussed intelligent routing across multiple LLMs with services such as Neutrino and OpenRouter for optimized performance. Community-built Llama Packs were highlighted as powerful ways to rapidly prototype and build advanced components, and the chapter introduced the Llama CLI for streamlining RAG development and deployment workflows.

We talked about advanced tracing with Phoenix, allowing us to gain deep insight into application execution flows and pinpoint problems through visualization. The evaluation of RAG systems was covered using Phoenix’s relevance, hallucination, and QA correctness evaluators, ensuring the robust performance of our LlamaIndex apps. Streamlit’s deployment options...