Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Generative AI with LangChain
  • Table Of Contents Toc
Generative AI with LangChain

Generative AI with LangChain

By : Ben Auffarth
4.1 (33)
close
close
Generative AI with LangChain

Generative AI with LangChain

4.1 (33)
By: Ben Auffarth

Overview of this book

ChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.
Table of Contents (14 chapters)
close
close
12
Other Books You May Enjoy
13
Index

Conditioning LLMs

While base models such as GPT-4 can generate impressive text on a wide range of topics, conditioning them can enhance their capabilities in terms of task relevance, specificity, and coherence, and can guide the model’s behavior to be in line with what is considered ethical and appropriate. Conditioning refers to a collection of methods used to direct the model’s generation of outputs. This includes not only prompt crafting but also more systemic techniques, such as fine-tuning the model on specific datasets to adapt its responses to certain topics or styles persistently. In the later sections of this chapter, we’ll focus on fine-tuning and prompt techniques as two methods of conditioning.

Conditioning techniques enable LLMs to comprehend and execute complex instructions, delivering content that closely matches our expectations. This ranges from off-the-cuff interactions to systematic training that orients a model’s behavior toward...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Generative AI with LangChain
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon