E-book details

Building Data-Driven Applications with LlamaIndex. A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Building Data-Driven Applications with LlamaIndex. A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Andrei Gheorghiu

Ebook
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Discover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.
  • 1. Understanding Large Language Models
  • 2. LlamaIndex: The Hidden Jewel - An Introduction to the LlamaIndex Ecosystem
  • 3. Kickstarting Your Journey with LlamaIndex
  • 4. Ingesting Data into Our RAG Workflow
  • 5. Indexing with LlamaIndex
  • 6. Querying Our Data, Part 1 – Context Retrieval
  • 7. Querying Our Data, Part 2 – Postprocessing and Response Synthesis
  • 8. Building Chatbots and Agents with LlamaIndex
  • 9. Customizing and Deploying Our LlamaIndex Project
  • 10. Prompt Engineering Guidelines and Best Practices
  • 11. Conclusions and Additional Resources
  • Title: Building Data-Driven Applications with LlamaIndex. A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications
  • Author: Andrei Gheorghiu
  • Original title: Building Data-Driven Applications with LlamaIndex. A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications
  • ISBN: 9781805124405, 9781805124405
  • Date of issue: 2024-05-10
  • Format: Ebook
  • Item ID: e_3urz
  • Publisher: Packt Publishing