Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Building LLM Powered  Applications

You're reading from   Building LLM Powered Applications Create intelligent apps and agents with large language models

Arrow left icon
Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Length 342 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Valentina Alto Valentina Alto
Author Profile Icon Valentina Alto
Valentina Alto
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Introduction to Large Language Models 2. LLMs for AI-Powered Applications FREE CHAPTER 3. Choosing an LLM for Your Application 4. Prompt Engineering 5. Embedding LLMs within Your Applications 6. Building Conversational Applications 7. Search and Recommendation Engines with LLMs 8. Using LLMs with Structured Data 9. Working with Code 10. Building Multimodal Applications with LLMs 11. Fine-Tuning Large Language Models 12. Responsible AI 13. Emerging Trends and Innovations 14. Other Books You May Enjoy
15. Index

Summary

In this chapter, we introduced the concept of multimodality and how to achieve it even without multimodal models. We explored three different ways of achieving the objective of a multimodal application: an agentic approach with a pre-built toolkit, an agentic approach with the combination of single tools, and a hard-coded approach with chained models.

We delved into the concrete implementation of three applications with the above methods, examining the pros and cons of each approach. We saw, for example, how an agentic approach gives higher flexibility to the end user at the price of less control of the backend plan of action.

Finally, we implemented a front-end with Streamlit to build a consumable application with the hard-coded approach.

With this chapter, we conclude Part 2 of the book, where we examined hands-on scenarios and built LLMs-powered applications. In the next chapter, we will focus on how to customize your LLMs even more with the process of fine...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime