"It takes 20 years to build a reputation and five minutes to ruin it. If you think about that, you'll do things differently." - Warren Buffett

Artificial Intelligence holds tremendous promise for almost any business or a brand. At the same time it can also be a existential threat to the reputation of any organization that throws caution to the wind and unleashes unrestrained AI. The whole purpose of Generative AI is to generate a conversation between your company, your organization, your brand and your customers, partners, users etc. This conversation must be conducted in a respectful, inclusive, and polite way and it must be on topic that is acceptable to both you and your audience. "Guardrails" is the term used to describe technology to keep AI conversations on topic and with the proper tone to protect your organization's reputation. In our opinion, no AI should be deployed in production without proper guardrails in place.
     
In this project you will learn what "guardrails" are in the context in Artificial Intelligence (AI), and how you can implement them on your own AI using open-source tools. By the end of this guided project, you will know:

This guided project requires basic knowledge of Python, LangChain, and Git. In the third section we will delve into details of guardrails implementations, and familiarity with open-source development and debugging could come in handy.

However, don't worry if you don't have much experience with the above. This project will explain each step along the way, and you may learn as-you-need along the way.

IBM Skills Network Labs environment also comes with many technical requisites pre-installed to save the hassle of setting everything up, so we won't be dealing with any environment issues.