Hey there.
Eden here.
And in this video I want to talk to you about user experience and user interface in generative AI applications.
So building the back ends of our generative AI applications is one challenge.
And we can spend a lot of time in the back end building our agent and building our rack system and making
sure that the output that we give the user is the correct output, that it's trustworthy, and a quality
output.
However, this is just one piece of the puzzle.
In order to have our application complete, we need to create a beautiful user interface and a very
natural user experience for our users.
To be able to trust our application and trust between users and generative AI applications is something
that we need to work for, because users know that generative applications are, let's just say, flaky
and they not always yielding the correct responses.
And they can fail sometimes.
And there is a huge challenge of doing this correctly.
And in this video I will be featuring copilot kit and copilot kit is an amazing open source which helps
us bridge this gap of creating beautiful interfaces, but more importantly, more natural user experiences
in our generative AI applications.
And I think Copilot Kit offers us today the best building blocks for building a beautiful generative
UI.
And when I talk about generative UI, I mean, in general, the user interface of our generative AI
application, which is based on Dlrm.
And I think that in order to create this trust between the user and our system, then we need to be
transparent.
So the user needs to know where does the answer come from.
And for example, if we're building an agent then we need to be transparent on which tools does the
agent have and which tools the agent is using to generate the answer.
Why did he chose that tool?
So the reasoning behind the agent may be some intermediate calculations until we get the final answer.
So we can see how the final answer is being curated.
And even in a Rag application, we need to be transparent and to show the user which documents did we
use to generate the answer so it will know where it's grounded from.
And all of this is going to create better trust between the user and our generative AI application.
All right.
Let's talk now about copilot Kit.
And by the way, all of the demos you saw in this video are taken from the copilot kit documentation.
They're open source.
And in my opinion, they're pioneering right now the landscape of generative UI and generative UX.
So in their repository you can skim around and you can find some starter kits to help you implement
beautiful front ends for your back end generative AI applications.
So this is not a full stack course, so I won't be going into that deeply.
I'm simply introducing now the topics, but overall they simply introduce a bunch of components and
hooks that we can use in our front ends, which makes it super easy to build generative UI and to build
very good user experience on top of our generative AI applications, which is powered with link chain
or with land graph, etc..
I want to elaborate on the support for link chain and link graph applications, and they introduce co
agents which seamlessly integrates with lane graph backends.
And I think the video here by Ariel from copilot Kit, which I will link in this video, is demonstrating
this beautifully.
And when we have a lane graph application, so a lot of things and a lot of moving parts are happening.
We have the state which is constantly changing.
We have intermediate results in that state.
We have nodes that are executing, maybe nodes that are executing in parallel.
We also have human in the loop where we stop the execution of the graph and we go to take the user input.
And then we want to resume the execution of the graph.
So a lot of moving parts here.
And to build a frontend for this.
To be honest it sounds like a nightmare.
But copilot kit did a very good job to implement components for all of that I discussed all built on
top of lane graph applications, which I think is super important and it's super easy to integrate both
lane graph with copilot kit.
I just want to be clear, I don't have any affiliation with copilot kit.
I genuinely believe this is a good project, and I think they're doing an amazing job in the field of
generative UI.