Naden just dropped their new chat hub

which lets you talk to all the different

chat models that you already know and

love in one spot and it also lets you

talk to and trigger your Naden AI

agents. So in today's video I'm going to

be talking about what chat hub is and

how you can start using it right away.

So here we are in my Nadn and we are in

the new chat hub which as you can see

kind of looks like a chatbt or a typical

cloud interface where you've got past

conversations on the left and you can

start a new conversation right here in

the middle. [music] If you're wondering

how I got here in your typical end

environment, you can see there's a

little chat bubble in the bottom left.

And if you don't see this down here,

then you probably just need to update

your end instance. So, there's a few

things that I wanted to break down once

you are in this environment. So, right

here, you can see that I'm talking to

Claude Haiku 4.5. So, I could just go

ahead and say, "Tell me a joke." And

what it's going to do is it's going to

use that chat model in order to actually

say something to us. And the way that I

was able to connect to Claude was up

here. I just basically put in my

anthropic API key. And if you already

have that credential configured in your

end, then it will already be there. But

what's cool is now that we're already

mid-con conversation, I could go ahead

and switch the model if I wanted to. So,

as you can see, I just switched over to

GPT5 Mini and I can say, "Super funny,

tell me another one." And now it has

switched over the model to an OpenAI

model. And of course, you could also go

ahead and connect to Open Router, which

has basically all these other models

already inside. So, I just switched to

Google Gemini 2.5 Pro from Open Router.

And now you can see that it's switched

the model successfully down here. But

what I wanted to show you guys was the

memory of basically this context window.

So as you can see, even though we've

switched models every time, whatever

model you're currently talking to is

going to be able to read the

conversation that you've already been

having in this thread. And that's why

it's stored over here as a tell me a

joke thread. So there's a couple other

things you can do here. You can see

under each of these little elements, we

have the ability to copy. We have the

ability to read aloud. And then for some

reason, we can also edit the AI's

response. Not sure exactly what the use

case is there, but if I wanted to change

what the AI said, I could. And then we

also could just regenerate a new

response if we didn't like it. So, when

you speak the AI's response out loud, it

actually just speaks it. I'll show that

real quick.

>> Of course, so far in our conversation,

I've told you these two jokes.

>> Okay, so it doesn't really sound great.

It's not like a 11 Labs or a really nice

voice model, but it will read it aloud.

So, I'm sure you guys are also wondering

at the bottom, you can see that there is

a tool section. And right now our only

tool is Gina AAI, but that lets you

basically access the web, access URLs,

and do web search. So here is what

Gina.ai looks like. And then all I did

was I went up to the top right and I

made an account. And when I did that, it

gave me this free API key that gives me

a million tokens to play around with

before I have to top up. So I took that

API key, I came into Nitn, and I

basically just created a new GINA

credential and pasted my API key right

in there. Now, if I wanted to open up a

new workflow and actually use the tool,

I could connect to my Gina credential.

And now I could do real web search. And

now that I have the web search tool

enabled, I could go ahead and ask, "What

is the Chicago Bears current record?"

And it has to actually go search the web

in order to pull that live information

back. So, we have that first little line

that basically indicates that it was

able to call a tool and work. And now

the model is responding to us. So, as

you can see, as of December 11th, 2025,

which is today, the Bears are 9 and4.

But what happened is I asked it to

summarize this article and I gave it a

URL and it was unable to do so. And

that's because we didn't enable the tool

that lets Gina read URL content. But now

that I've enabled the tool that actually

allows us to read URLs, now it can look

at that for me. All right. So that's

basically the same thing that you guys

are already used to with your typical

large language models like Gemini,

Claude, CHBT, whatever it is. But now

you can also see that we have the

ability to talk to our custom agents.

And you can see I have one right here

called get agent logs tool. I could also

come down here and click on custom

agents and we can see all of the edit

and workflows that we've actually

configured. Now you could also basically

create a custom GPT or project in here

too. It doesn't have to be an edit and

workflow cuz I could click on new agent.

I would name it and give it a system

prompt. Choose a model and then I could

allow the same GINA tools in here as

well. So basically a custom GBT but of

course like I said you can connect and

workflows. And if I clicked into this

one you can see that it is in fact an

NIN AI agent that I've got. So I'm going

to show you guys how we can talk to it

and what it can do. So in this

particular example, we've got an AI

agent that I'm calling a data analyst

and it's basically able to search

through our own end data table which has

workflow executions. So this is

obviously mock data, but you can see

we've got a date, we've got a workflow

name, we have the input, the tools

called, the tokens used, and then the

final output. So basically, let's just

say you have all of these workflow

executions running. Now you have this

easy chat interface in nitn where you

can talk to it and basically get some

insights and analysis from those

execution logs. So I just shot off how

many times did the customer support

workflow run in October. And so this

agent over here basically just got that

message. It's going to use its tools and

maybe its calculator to look up the

information and then it's going to

respond to us in the actual chat

interface right over here. So anyways,

you can see it did a few tool calls

here. That's why we're getting these

different lines. But then what happened

is it gives us a concise answer which is

that the customer support workflow ran

four times in October and then I told it

to give us a detailed breakdown so we

could actually validate that it is

correct and it's not hallucinating. So

if I switch over to the data set we

should be able to see that in October

which is all of these runs right here

the customer support workflow got called

four times which as you can see it did

execute four times in October. So now

I'm asking how many total tokens did we

spend with our code reviewer agent? And

it should be smart enough to understand

we're talking about the code review

assistant workflow. And what it's going

to do is it's going to find all of those

actual executions and then total up all

the tokens and it's going to explain to

us how it actually got there. So here we

go. The code review assistant used a

total of 10,260 tokens across all

retrieved log entries. Then once again

it gives us a detailed breakdown and it

basically just had to sum up all of

those executions. 890 plus 3,400 plus

120 plus 1450 and that's how we got to

10 to 60. And as you can see in the data

set, I summed up all of these rows

myself and we did get 10,260. So it did

its job right. But now what I want to do

is real quick just show you that it

actually did call this workflow. So this

is the agent that we were just talking

to. If I go to executions, you can see

that the two most recent runs, the first

one that we asked was about the customer

support flow. So how many times did the

customer support flow run in October?

And then it got us the answer that we

saw in that chat interface. And the

second one was how many total tokens did

we use on the code reviewer agent as you

can see right here. So the question now

is how do you actually go make an edit

in workflow and then let yourself talk

to it through this interface? Because

when you click on custom agents, this is

what you see. So I'm going to go back to

my workflows and open up a new one. And

basically all you have to do is have a

workflow that you talk to or that's

triggered by the chat trigger. So, if I

open up an AI agent right here, and I

basically just by default get the

connected chat trigger node, I'm going

to add a chat model real quick. So,

we'll just go with the basic 4.1 mini

from open router. And all I'm going to

do in here is I'm just going to add a

system message that says, "You are super

mean and rude and sarcastic." And so,

that's how we'll basically be able to

validate that it is in fact talking to

this workflow. Now, what it did is I

saved this, but what you'll notice is if

I go back into the chat, we don't see

anything here. Even if I refresh, we

don't see that workflow. So, there's a

couple things that you do have to do.

So, the first one is that you have to go

into the chat trigger and you have to

make it available in edit and chat. As

you can see, it says whether to make the

agent available in an end chat. And this

is where you can give it a name and a

description. And so, the other thing

that you have to do before it can show

up is you have to publish your workflow.

So, I'm going to go up and hit publish.

I'll just call this version one. And now

that it's actually a live published

workflow, we should be able to go back

to the chat. And if I just give this a

quick refresh, we should see that mean

workflow now. And I can go ahead and

chat with it. So I'll click into this

and I'll just say, hey, I am feeling

sad. And now this should be running

through that main agent. Oh, Boohoo.

Welcome to the club sunshine. Everyone

feels sad sometimes. Want a medal or

just some cheesy sympathy? Get over it.

So that was pretty rude. But if I open

up the workflow and I go to executions,

we will of course see that that is the

chat that just triggered this end

workflow. So hopefully you're starting

to get some ideas of different workflows

that you have in NADN. That would be

really nice if you could just kind of

use them right in here, especially if

you're able to switch between all of

these different chat models in the other

threads. Now, one thing that I really,

really hope is coming to this soon is

being able to call NIDEN's instance

level MCP right here. If you haven't

watched my video about that, I'll go

ahead and tag it right up here. But in

that video, I showed how I could use it

in my own chatbt or claude. As you can

see here, I have these tools right here

that let us search workflows, get

workflow details, and execute those

workflows. So, I can always stay in my

cloud environment if I'm working on a

project and just say, "Hey, use nitn to

go do that or go do this in nit." And

that would be really cool if we could

have that plugged in here so that while

we were having these messages with

whatever chat models we wanted in nit,

we could say, "Oh, okay. I have an agent

for that or I have a workflow that does

that. Just go find it and go execute it

for me." And so I imagine it will be

super easy and by the time you're

watching this video, it may already be

here because all you have to do is

essentially give the client this server

URL. And so we could easily just plug

that in here. Or because this is an NEN

product within your own, you know,

environment, it should be able to just

see everything either way and execute

them. But anyways, that's going to do it

for today. I know it was a super quick

one, but I wanted to update you guys

about this new ChatHub feature. and I'd

love to see some of the use cases that

you guys are thinking about of actually

plugging in your workflows right into

this environment in NADN. If you're

looking to learn more about AI

automation and NIDN, then definitely

check out my plus community. The link

for that's down in the description.

We've got a great community of members

who are building with NIDN and building

businesses every day with NIDN. And we

celebrate some awesome wins in here as

you can see. So, just a great place to

be surrounded by like-minded

individuals. But anyways, I would love

to see you guys in the live calls in

here. I'd love to see you in the

community. But that's going to do it for

today. So, if you enjoyed the video or

you learned something new, please give

it a like. It definitely helps me out a

ton. And as always, I appreciate you

guys making it to the end of the video.

I'll see you on the next one.