Complete n8n Masterclass: From Beginner to AI Agent Builder

all right today we've got a very exciting one this is the nadn master class where ideally I'm taking you from

a beginner in nadn all the way to an AI agent Builder by the end of this or even just someone who wants to implement AI

automations into their daily life or into their work so I was about to say grab a pen and a piece of paper but more

realistically since you're here grab some sort of AI notetaker and let's dive into this one this is a master class so

we're going to start at the bottom start with the basics and we'll continuously work our way up but just want to start

off here with what is any so at this point I'm sure you guys have been hearing the term low code no code

tools and nadn is a low code no code automation tool so that just basically means that nadn allows users to automate

processes build workflows with minimal coding knowledge and the key idea behind this is that low code means it's very

easy to develop things with a very userfriendly interface where people can just go in there and drag and drop

different components different nodes is what they're called in nadn to create these flows without having to come in

here and type a bunch of JavaScript or python this is so significant because it's going to allow anyone to be able to

get an in and get up and running with building automations even if you don't have you know a background in computer

science or programming the barrier entry to this is so low it's very very accessible for anyone to get in here and

start playing around with stuff but even though it's very simple it also retains a lot of flexibility for more advanced

users who do have coding background and they're able to come in here and take some of the basic principles and also

come come on top of that with you know custom code or different type of logic and Integrations and it's a very very

powerful tool you can build tools directly in NAD as you see here and that's a little bit different from other

things like make or zappier because you can build let's say an agent that's able to call four or five tools and these

tools you built within NN itself which is just super super cool stuff what about the importance of automating workf

flows so we've got five points here I'll touch on real quick increasing efficiency and productivity automation

is going to eliminate repetitive tasks it's going to reduce human error and it's going to allow you and your team to

focus on higher value work it's also going to save time and money of course automating workflows is going to reduce

operational risk free up Time by completing tasks faster than manual scalability and adaptability you can

scale a lot more effortlessly you can focus on your growth as a business and these Solutions these automation

Solutions can be customized or adjusted to meet your changing needs you've also got improved data handling automation is

going to integrate data from various sources it's going to provide real-time insights for better decision making and

then the last benefit I wanted to hit on here was enhanced customer experience you're going to be able to respond

faster to your clients or automatically to your clients personalize interactions through automated workflows and all of

this is just going to lead to better customer satisfaction and Customer Loyalty moving on here we've got why

should you learn nadn so when I was building the slide I had so many thoughts and I tried to put them all

under three main bullets and so this first first one here is nadn empowers non-developers with Automation and I

know we've touched on this a little bit with the whole low code no code stuff but it's just so powerful that anyone

can pretty much come into NN and start building things in 15 20 minutes that's actually going to automate real work

that they would do on a daily basis so even if you're not a programmer you can come in here create workflows it's going

to save you time make your life easier for example you could very easily get up a workflow that is going to

automatically move data from one app to another like ually copying contacts from one spreadsheet to another without

having to do it every time it's like having a digital assistant that can handle these repetitive tasks for you

and you don't really need the technical skills to set it up so super cool stuff the second one we've got access to over

300 built-in Integrations which is insane andn comes with a ton of Integrations ton of connections to

popular tools that you probably use every day like Gmail um Google Sheets slack Twitter we got Microsoft stuff too

if you want to connect to teams or Outlook it's super super cool what you can do these Integrations let you

connect quickly to these tools and you can connect tools to other tools without needing to like code in between that for

example you could set up a workflow where every time you receive an email it's going to automatically add that

information to some sort of spreadsheet and then it's going to send you a notification on slack or teams and all

of that will take place without you needing to be in there and doing it manually then this last one you can

connect to almost any tool so kind of similar to the second point but if there's something that you want want to

connect to that there's not a built-in integration to you can still pretty much connect to it whether that's through an

API or a web hook um these ones are a little more technical but for the most part um you know a quick YouTube video

or using chat gbt even you'll be able to get them up and running and connect to almost anything you want a little bit of

custom code and um really when you realize you can connect to almost anything then you have almost endless

possibilities of what you want to automate all right we're going to be moving into part one of this master

class here which is just very simple getting started with NN we're going to talk about how you set it up the

different ways you can set it up and then we'll just get into the interface and start actually learning what it

looks like and what everything does the first thing I think that we should talk about when it comes to setting up your

NN is if you want to set it up self-hosted or if you want to Cloud host and I'm going to run through a few

features of each of these two different options and then we'll talk about which one you should choose so first with

self-hosted some of the things that it's going to offer you are control and flexibility you're going to have full

control over your environment you can customize your server integrate with any internal system you have the ability to

adjust your configurations as needed we've got data ownership so all the data and workflows are going to stay on your

private server so this is ideal if you need to comply with privacy regulations or you want to keep sensitive data

in-house cost self-hosting can be more cost effective in the long run it depends on the server and maintenance

costs but there's no ongoing subscription fee to naden like if you were to do Cloud hosted but with the

cost as aspect you may need to account for infrastructure with like database management or server hosting and you

also may need to have some sort of team that will help you maintain it but who knows fourth with self-hosting is

installation and maintenance you are going to be responsible for setting up and managing and updating your instance

this also includes backups and scaling so this is going to require more technical knowledge then finally we've

got customization so you can modify the source code you can add custom features that might not be available in the cloud

environment so this is cool if you want complete freedom to modify the system as you want and now moving on to the cloud

environment here are some features of cloud it's going to be easier to use because it's managed by nadn itself so

there's no need to worry about setup updates scaling maintenance stuff like that so good for beginners you've also

got availability and reliability so the NN cloud is hosted on a scalable and reliable infrastructure it's going to be

maintained by Ann's team so they're always going to keep stuff up to date with the latest features and Bug fixes

the security is a little different it's going to be managed security so SSL certificates or you know secure API

handling and that's going to be done by the N team and then also this is going to be more suitable for users who don't

want to handle server security now when it comes to cost of nadn it's really not that bad either way the cloud version

comes with a subscription model that's going to be based on usage tiers how many products you want how many seats

you want on your you know an inn environment and so you'll be basically paying based on that so in the long run

it could be more expensive if you have a ton of users and a ton of projects going on but if that's the case then hopefully

you're either saving a ton of money or you're making a ton of money so balance is out then finally we have data

handling different than self-hosted data is going to be stored and processed in the cloud so like I said if you're a

business dealing with highly sensitive data this may be a limitation due to the server dependencies okay so at this

point you may already have an idea of which one you're going to choose but if you don't real quick you should go with

self-hosted if you need full control over your data and your infrastructure if you want to integrate any in deeply

with other on premise systems and if you're technically comfortable handling server maintenance and management or you

have a dedicated team that will do that for you and then you're going to want to go with Cloud if you prefer Simplicity

and you don't want to handle infrastructure or server maintenance you want a quick setup and reliable hosting

it's going to be managed by the NN team and you're okay with paying for a subscription for a managed service and

you don't mind being handled by a third party provider okay so before we actually hop into NN and we look around

at the interface probably important to understand the difference between workflows nodes and executions so I'm

going to break this down as simple as I can pretend you're in a restaurant we've got workflows which are going to be the

recipes nodes are going to be the ingredients the steps within each recipe and then executions are going to be

every time someone sits down and orders that specific recipe or workflow so the workflow think of it as like a set of

instructions that you're going to be giving to nadn in order to automate a task so for this example we'll say that

the workflow is a a chocolate cake then we'll move down to nodes nodes are like the building blocks of the workflow each

node is going to represent a single step a single action within a workflow so one node might send an email one might

update a spreadsheet one might pull data and then you can kind of Link those together in order to make the chocolate

cake so you know eggs flour baking soda we're going to put those together then we have the execution which is simply

just running your workflow in nadn this can happen by different triggers whether you want to do that manually or whether

you want the automation to take place every time you update a row in a spreadsheet but in the example like I

said just picture someone coming to the restaurant and ordering a piece of chocolate cake and then you kind of

start that process of making the cake and delivering the cake all right now that we've covered the three main

building blocks that go into pretty much every automation let's actually get into nadn look around a little bit at the

user interface see what I'm talking about when I say drag and drop we'll talk about accessing Community Resources

Community templates stuff like that and it'll really start to make more sense all right so we're in nadn as you can

see as what we're looking at right now is we're just on my homepage so it's going to show me a ton of the different

workflows that I've been working on um we've got our projects right here so I only have the one right now it's called

Nate testing so in here it's pretty much just everything I have but if you had a specific project for a specific client

or a specific project for an actual specific project at work you could add them here so you can keep everything

organized honestly my stuff is not too organized but here's what it looks like we've got stuff on the Le hand side we

can see we have an admin panel we have templates we have variables we can see executions of each workflow we've got

some help and then you have your profile down here as long as well as you know I'm Cloud hosted so I can see that

there's some updates here with some bug fixes that I'll I'm going to be able to just go in and install real quick let's

just add a new workflow right here and see what the interface sort of looks like so this is the canvas that I was

talking about where I said it was a very userfriendly drag and drop interface the first thing you're going to see is that

you have and add First Step button so we'll get into different types of nodes after this and we'll talk about triggers

and all that but first step is always going to be a trigger so you'll click on that and it will list up you know some

triggers trigger manually just means that you'll be hitting test workflow button down here in order to run the

workflow execute the workflow every single time you can schedule it you can do um on chat message you can call it by

another workflow so that's where all the stuff is super powerful we'll just add a manual one so you guys can see what it

looks like this is where you hit test workflow in order to run it and you know obviously nothing's coming through but

it didn't fail so that's good then from here you would want to add different nodes to connect to so you could do that

from either clicking on this plus button where it says click to add node or drag to connect or up in the top right you

can click up here and it will pull up this panel for you to search through nodes you know by category or you can

just search for them if you want um another cool thing with the triggers is there's not just those triggers there's

different triggers for each app so let's say that you wanted to run a workflow every time you got an email you can

click on on Gmail down at the bottom you'd see different triggers and this one says on message received so this

would execute the workflow every time you get an email and you can tell a trigger if it has this little lightning

bolt so that's a trigger node but anyways let's just say that we wanted to put some fake data in here so I would

just come in here and I could either type for the the node that I want or I know I'm looking for an edit Fields node

so I can come to data transformation and I would see edit Fields right here this is where I could configure stuff so let

me just quickly pretend um we're going to make make a field called name and we'll just put in my name and what's

really cool about NN is that you can test each step individually as you're going through and automating something

so rather than having to run the whole workflow you could just test step right here we'll see that what's coming out of

this node is Nate um in the field called name so we have that information running through but it's nice to know because

you'll always see on the left of this configuration panel you'll see data that's coming in and then you'll see

data that's coming out so it makes it really easy to troubleshoot and test each step individually which is really

cool but you have to make sure that your your um nodes are connected because let's say

you know I didn't drag this one right here and connect it to the edit Fields if I was to run

this nothing would come through the edit Fields there's no output as you can see it says wire me up this node can only

receive input data if you connect it to another node and yeah so that's how that's going to work I say this is

probably all we'll do for now in here we'll get into some Community templates and just show you how that all works but

as far as just basic setting up a workflow and seeing what um the interface looks like how easy it is to

just drag and drop stuff that's what we've got so back in the homepage we've got workflows you all can also look at

your credentials so this is just different things that you've connected to like I said there's so many

Integrations so it can easily access my Google Drive my telegram my Google Sheets all that kind of stuff so that's

where you can sort of see and manage your credentials and then down here the only thing I'll touch on real quick will

be the templates you can click into templates and it will pull up nad's website where there's sort of like this

community where people can upload cool things they're building or you can search for specific use cases

specific um you know tools that you want to use so it's a really great place to get in here and learn but as you can see

we have you know learn by doing so you can download these templates which is really cool sometimes it's you know it's

nice to watch a tutorial on YouTube but being able to really learn you have to just get in there and you have to let

things fail in order to figure out why they're failing so right here we have you know AI agent chat we can download

from NN we can click here we can look at it um and we can see what's going on we could click this button here to download

it and um start playing around with it in our own nadn we have this one where you can click in here and a lot of times

people will annotate like what's going on so you can see how to set it up you can see which you know what's taking

place in each scenario so that's super super useful and then I'll just show you real quick let say you wanted to use

this one we could just import the template to my cloud environment and as that loads up it's

pretty much just going to put it right into my workspace so I've got this information here I can now test this

data I can look at what's going through each step we can see right here we've got um you know this information's

coming through and then it comes out as you know flour eggs milk which is interesting because I just did a you

know a little example about cake so um seems like it's meant to be but either way you can start to see actual data

moving through which is how you're really going to be able to wrap your head around what's going on another

great thing about nnn is there's so much documentation it's super easy to get help so if you come down here you can

see help we've got a lot of stuff here they even have a course that you can go through through but documentation if you

click on here you can see pretty much anything you need to find like there there's quick starts there is um

Concepts about flow logic Concepts about data so like I said super easy to learn about all this kind of stuff you can

look at you know what each node is doing specifically so let's say you were confused about the loop node you could

come in here read about looping you could see you know how the node works you could maybe see some

examples of how people are using it and yeah like at the bottom it's probably going to throw you in some you know

templates of actual workflows with loops but super easy to get help Within naden part two of the master class we're going

to be talking about some Core Concepts so we just saw what the interface looked like we saw a few nodes but now we

actually need to dive into different types of nodes and what they do and then we're going to end this section of the

master class with an actual example where we'll get into nadn I'll do a live build of a really quick Automation and

then we'll talk about the different type of nodes and how data is moving through so it should be pretty cool to see so

before we in nadn and we build out our first automation we really need to understand these sort of four main types

of nodes so we've got Trigger action data transformation and logic so let's just break these down real quick

starting off here with trigger nodes because a trigger node is pretty much going to be what starts every workflow

we just saw these in nadn they were the ones with the little lightning bolt next to them anyways different types of

trigger nodes we can look at something like a web hook trigger um an email trigger like I showed you anything

that's going to start the the workflow whether that's going to be manual or on a chat or on an event or I have called

by another workflow bolded here because it's sort of the power of NN you can build a workflow that will be called by

another workflow and then you can build an agent that can call that workflow as well as maybe this agent can call like

10 other workflows so super powerful stuff here next we've got action nodes these are the actual doers they're going

to perform a very specific task within your workflow so it's like an assembly line this guy is going to to um you know

put the present in the Box this guy's going to wrap the present this guy's going to put the bow on the present all

that sort of stuff but they can do different things like you know send email create a record make an API

request they can get a text message they can set your calendar um almost anything that you could do on your computer on

your phone manually you could have some sort of action node to do this thing third we have data transformation nodes

these are going to help you change or process your data in some way so that it flows through the whole process and you

get the end result as you want want it so these type of nodes can do things like set that can add Fields change

values within Fields it can do some sort of processing your data you've got something like an aggregate where you

can combine a ton of data into a single output or something like a merge where you can combine data from two different

sources and put them into one the last type I'm going to touch on real quick are logic nodes these are sort of the

decision makers they're going to help n and figure out what path to take how to handle a different situation so we've

got something like an if node it's going to check if a specific condition is true or false is you know this value higher

than 10 it's going to go this way otherwise it's going to go this way we've got a switch node which is going

to allow you to put multiple conditions in there and it's going to be checked and direct the workflow to a specific

action based on that conditional check and then something like a weit node which is going to pause the workflow

let's say you wanted to pause the workflow until you come back and respond like yes that's good to go then it will

continue to move on through the rest of the process or you could have it like wait for 20 seconds um what whatever you

want it to do all right now it's time to finally hop back into NAD in hopefully these slides weren't too boring but

we're going to be building an example workflow here it's going to be really simple it's just going to automatically

process customer orders and then it's going to summarize it and send us a report automatically every time we get a

new order so super cool stuff let's hop into how we're going to build this thing all right we are in a Google sheet this

is going to be the customer order data that we'll be using for this example so I had chat gbt make up some data for us

we've got stuff like order ID customer name product quantity price order date and the status of that order so every

time a new row is put into this Google sheet it's going to run through nadn automatically it's going to get

summarized by some sort of large language model like chat gbt or Claude and then that summarization is going to

be emailed off back to us or back to our team automatically so this will be a nice simple example but it's going to

feature different types of nodes and we'll be able to see the data move through real time so it'll give us a

really good base we are now in n8n this is the canvas we'll be working on and this is the workflow that we'll be

building here um NN masterclass customer orders so we know the first step that we always need to do is add some sort of

trigger we'll click in here and we can see different triggers like manual um on app event called by another workflow we

talked about this but in this case we want to make this one automatic so we're going to be doing a Google Sheets

trigger Google Sheets has three triggers it's got on row added on row updated or on row added or updated so we'll do this

one because that way if you have to go in there and change some sort of information about an order like let's

say one goes from you know the status is pending to shipped or something we'll also get an email about that so we have

to set up the Google Sheets account um this is where you're going to have to set up a credential and I'll walk you

guys through how to do this so you're going to click create new credential and you'll see this screen pop up where we

need to grab a client ID and a client secret um this looks a little confusing and I was definitely confused when I

first saw the screen so what we need to do is right here um I talked about how nadn has is really good at having

documentation that explains stuff so we'll click on open docs right here we will see that the prerequisite we need

is a Google Cloud account so we'll go in here and make a Google Cloud account um and then we can see that it's going to

walk you through step by step so if my explanation isn't good enough you can come in here and grab the docs but

hopefully I'll show you real quick how to do this so we'll come into Google Cloud um this is what it's going to look

like you'll have to sign in make an account then you want to go to your console once you're in your console

you'll see the screen you might not know what to look at but all we want to do is we're going to

create a project so mine right here is just called my first project make sure you're in your project and then you want

to come in this left hand side to apis and services we're going to click on enabled apis and services and at this

point you just need to search for a Google Sheets so we're going to type in Google um okay we need to do sheets be

more specific so Google Sheets we can see Google Sheets API we'll click in here and then all you need to do is just

enable this API so we've got ours enabled already um there will be a button right here

it's just as simple as that so get that enabled and then you're going to come in here go back to your apis and services

and then we want to go to credentials once we're in credentials um this is where you can set up your client

IDs to get an ID and a secret so I'll just walk you guys through how we're going to do this one you're going to

click create credentials up here you'll go to ooth client ID once that loads up you want to choose

the application type this is going to be a web app you can name it whatever you want we'll call this one demo for for

the sake of this video and then all you need to do here is add a redirect URI so this is where you see in nadn you've got

this UD redirect URL um we're just going to click here to copy go back into Google cloud and we're going to add this

right in here just just paste it in and then you'll hit create you'll get the screen pop up with um your client ID and

your client secret so it's as simple as copying the ID pasting that into the ID field in NN going back to Cloud grabbing

your secret and pasting it into the secret then you want to sign in with Google so this screen's going to pop up

it's just going to be a simple prompt to sign in with Google like you would normally have um so I'll drag this in

right here and now it says that Google hasn't verified this app so this is where you need to set up your ooth

consent screen um so back in here you've got your ID and your secret now you need to go back in your credentials right

here ooth consent screen all you need to do here is either make sure that your app is published so um you need to make

make sure the app is published so that it has you know access to actually go through and grab information out of your

Google Sheets your drive your email whatever it is or you can add yourself as a test user so I've got my emails

down here as test users this also will allow these emails to sign in and go through but if you're getting blocked

for some reason it's probably because you didn't set this up right so just make sure it's published or that you're

in there as a test user so back into nadn um we've got this signin field we'll hit continue just

make sure you give this email access to everything give NAD access and then you'll hit continue and then pretty much

you'll be good to go you'll see we got this account created right here it's green we're good so we will come out and

now we're connected so now that we're connected we can configure the rest of this node it's

going to be running every minute and that's when it's going to be checking for if a row was added or updated now we

can select the document that we want so it's really nice you can choose from a list you can enter the URL or the ID of

your document but list is so much easier it's just going to access your Google Drive and see what sheets you've got so

we're going to do customer orders um there's only one sheet in this document so we'll grab that sheet and it's going

to trigger on row added or updated so if we can fetch a test event here we'll see some of our sample data coming through

so as you can see we've got um five items we've got the columns up here and then we have all of these orders that we

just had right here in Google Sheets so we've got John Jane Mike Emily Robert Brown and in here you can see we've got

John Jane Mike Emily and Robert Brown so this node's working we've got our information coming through into NN now

we want to add an open AI node so we'll just click on this plus right here or click on the plus up in this top right

corner and you can search for a new node we're going to grab open AI you could use a different large language model if

you wanted to but I'm going to be using open AI you can see we've got 15 different actions within this node what

we want to do here is message a model basically just means that we're going to be talking to chat GPT just call this no

summarize and now we need to hook up this node with our credentials so at this point if you don't have an open AI

account you need to do so and then once you do that you can come in here click create new credential this time all we

need is a single API key so once you have your open AI account you'll come into it on left hand side you'll see all

the stuff but we just want to go to API Keys up in the top right you can click create new key give it a name and then

it will give you a value to copy so pretty simple same thing you just want to come in here and copy that

information in or sorry past that information in hit save and it will go green once you're all good um so that is

all you got to do but pretty much every time that you need to configure a node you're going to have to grab some sort

of key so just keep that in mind so as you can see the resource is text the operation is messaging a model and now

we need to choose what model we want to message so I'm going to come in here and grab GPT 40 right there and now we need

to configure the rest of this node so this is the message that we're sending to GPT 40 you have a couple options here

you can have it be a user message an assistant message or system message you can see the differen is right here

usually when you're going to be prompting the node how to act we're going to choose system so in here I'm

going to type a quick prompt and I'll be right back to explain it all right here is the system prompt that I came up with

just typed this out really quick so I said you are in charge of client orders your job is to take incoming information

regarding new orders and give a nice summary that will be emailed to the team the email should be signed off from

customer success team and then we want to give it the information from the previous Google Sheets trigger that's

coming in here on the left we need to actually give it the information to summarize so it's going to be getting

order ID customer name product quantity price order date and status and so all we need to do is come in here and drag

and drop each of the fields into the prompt and it will be a variable so it will change for each one

so I'll just show you guys order ID we drag this in and I don't know why it does that um we want to make sure that

right here with order ID so first of all first thing to note this is a green variable with the two curly brackets

around it that just means that it's a JavaScript variable so this doesn't involve any coding it's as simple as

dragging and dropping but this just means that it's going to change based on whatever value is in this field so as

you can see in the result tab right here we've got the the json. order ID is coming through as 101 because that's the

first order and you can see similar things when we drag in customer name we'll get in the the results we got John

Doe um we'll drag in everything else and then I'll show you guys so we're just going to drag in product quantity price

order date and Status so that's assigned wherever it needs to be and then as you can see in the result we've got here's

the information on client orders we've got the correct order ID name price quantity all this kind of stuff we have

the actual information coming through as you can see and then the last thing that we wanted to say was please output the

following parameters So based on this information that it's getting right here that it's going to sum summarize it's

going to Output an email subject for us and an email body for us so we can go ahead here and hit test step and I'll

show you one thing about how we want to Output this content as Json so I didn't check this yet and so that means that

this is going to execute and it's going to all come out in one sort of like large string so as you can see we've got

um for the first order email subject new order confirmation order ID 101 here actually let me make this a little

bigger so it says hello team we have a new order that has been successfully processed and shipped below are the

details so it's going to summarize out for us and then it signs off thank you for your attention best regards customer

success team but this is coming through as one big chunk of text called content so what we want to do is output the

content as Json we'll test the step again and now it's going to come through as two separate Fields one will be the

email subject and then one will be the email body and this is just important so that we can drag and drop the next

Fields later when we want to configure the actual Gmail node so as you can see right here we've got the subject and

then we've got the body and we've got the subject and the body we'll read one more real quick so order 103 we've got

the subject and then the body says we have a new order summary order ID 103 Mike Johnson you got headphones at $200

just one pair please let us know if you need further details so as you can see these are all coming through as an email

subject and an email body and this will be important when we set up this next node here which is going to be a Gmail

node this time we're going to add the node by clicking the plus up here it's the same thing as this plus but just

wanted to show you guys different ways we're going to grab a Gmail node and there's 25 actions within Gmail as you

can see there's a lot of stuff you can do which is just awesome but here we're going to be sending a message so we'll

click on send a message um real quick let's just make sure we wire this one up otherwise it's

not going to work and then we'll come back into the node and we can configure it so first thing you got to do is

obviously set up your new credential you'll come in here just got to grab that same client ID and secret from the

previous one so we'll come back into um our enabled apis and services you want to go to

credentials and then you can click into that um client ID that we just made and then all you got to do once again is

copy and paste that information in so let me just do this real quick we'll grab the

secret paste that in there and then once again just sign in with Gmail it's again going to make you

verify the app we'll go through give access to everything and then we go green because we're good to go so we've

got that set up now all we need to do is configure the rest of this node so as you can see the resource is a message

the operation is that we're sending a message now you can see why it's so important that we set up the email

subject and the email body as two separate Fields because we output it as Json so all we got to do is drag in this

subject right here where it says subject so the subject of this Gmail being sent off will be order confirmation 101 for

John Doe and then same thing with body you're going to grab that and put that in the message field where this is the

actual message that's going to be sent in the email we we want to make the email type is text that's just how I

usually like to do it and then for the sake of this example we will just put in my email so we can see this email coming

through and you could make this variable you could make this change based on the order if you wanted to but right now

let's keep it simple we're just going to send it to nerk [email protected] every time and finally you've got some options here

you could attach things you could CC people you could change the sender name variably whatever you want to do here I

usually just will come in here and click append and add an attribution and make sure I turn that off otherwise at the

bottom of the email it'll just say this email was generated by nadn or sent by nadn so this looks good to go we can

test this step and it will it should be firing off five emails because we have five emails um in the sample data so you

can see these came through it's just giving us a message ID and a thread ID which right now we don't need but you

can see that all of these got sent so let's hop over to the email I will refresh and we should see five new

emails in my inbox so yeah we've got order um 101 102 103 104 and 105 so this is information from all the orders as

you can see this one says new order from Robert Brown he got a tablet three of them actually 600 per unit so the total

price was 1,800 it was on August 28th and the status is still pending so thank you best regards customer success team

so all that came through exactly how we wanted it so that's good to see now we're back in n8n and we're

pretty much done with this workflow we've got three nodes in here and we can save it and now what we want to do is

check this box to inactive or sorry to active so all this means is that now that the workflow is activated it will

regularly check Google Sheets for events and then it will trigger executions each time that um a row is added or

updated and they won't show immediately in the editor so that means like we won't be seeing like these turn green

every time it actually is going through but they will'll be going through so let's hop into the Google Sheets real

quick add a new row and then let's let's wait for the email okay so I've got this information I'm about to paste into here

we've got order 106 for Phil dumpy he ordered 500 crayons $5 for each one we've got the date and we got the status

so now we're just going to hop into our email and I'll just refresh and we should see the new email coming

through okay so I just refreshed and we can see this new New Order we've received the New Order from Phil dumpy

here are the details 106 Phil dumpy 500 crayons $5 per unit we've got the date and then we have the status so um as you

can see the date is actually coming through is January 20 2025 um and we did not put January 2025

so what you can do here is because there's you know a discrepancy we will go back and N ITN we will go to our

executions over here or right here so executions we can see this is the most recent execution we'll click into here

and we can see what's actually taking place so as you can see the trigger went off

it grabbed one new item we'll open up this message and model node so we can see the information coming through and

you can see the date come through here as 45585 so that's not what we want um

that's why it's coming through as um January 20 2025 so what we need to do is come in here and fix this specific node

because we see exactly where the issue is happening I think the issue here was just weird formatting with numbers

coming through as far as dates so let's just try this one again I just out of this row so it should be working right

now to fire off this email to us but we kept this one as just plain text so hopefully it reads through an n and end

as plain text but let's take a look at the email and then we'll take a look at the actual execution okay just refreshed

got this new order it's coming through order 106 and we got the date correctly as October 20th 2024 which is what we

put right here so let's go back into Ed and let's refresh this page so we can get the most recent execution and making

sure all the data is coming through exactly how we want it and it's a great thing to keep in mind that you're able

to go into the executions you can see exactly how stuff's coming through so from the Google Sheets trigger we're

getting this information and the date's now coming through correctly how we want it previously it was coming through as

just like 4554 whatever sometimes in sheets it can be weird with date formatting and then it's being able to

come through correctly order date and it's giving us a nice summarization right here we've received New Order with

the following details order ID 106 for Phil dumpy crayons 500 all this kind of stuff and then it's just going to take

that subject and and um body and put it into a Gmail node which is being sent over to Nate herk [email protected]

which is what we see right here so that was it for this first example I know it was very simple we just utilized three

nodes to build this workflow that automatically takes data every time a row is added in your Google Sheets it's

going to summarize it with a large language model of chat gbt 40 and then it's going to move into the Gmail node

which actually sends it off and this was one execution of this work worklow okay now we're moving into part three of this

master class which is going to be talking about Rag and Vector databases I'm sure you've heard these terms but

maybe you don't completely understand them so I'm here to break it down for you and then we're going to end this

part with going back into nadn building out a simple rag AI agent and this will include you know actually uploading

information into a vector database and then being able to use an agent and rag in order to go talk to that PDF or file

and get answers back okay so what is is rag rag stands for retrieval augmented generation and it's a very powerful

technique that's going to combine two different approaches the first part is retrieval and then the second part is

Generation so this technique really helps AI models provide accurate and relevant answers especially when you

need upto-date or specialized information so the first part here is retrieval when you ask the AI a question

instead of it making up answers based on its training data it's going to retrieve relevant information from um external

sources so in this case the pine cone Vector database that we're going to be setting up um so this is obviously going

to be the database but it could be other documents or it could be websites and then the generation aspect of it is

after it retrieves back this information that's relevant and accurate and up to date then the AI model will use this

information to generate an answer so this is where the AI actually crafts a human readable response with the

information if you don't already understand from that previous slide why rag matters let's break it down real

quick let's say for this example you're using an AI assistant that needs to answer questions about your company's

internal policies you don't want this thing to just guess um answers based on its training data it might be out of

date because you're going to update policies stuff like that so in this case the AI assistant will use rag to

retrieve the most relevant information from the system it's going to generate an answer based on that specific

information which makes the AI far more reliable and up toate for your needs okay rag is a pretty simple concept to

wrap your head around now we're going to move into databases which I think are a little more complicated but once you

really break them down not that bad so in order to make rag work the system needs a way to store and retrieve data

efficiently this is where the vector databases are going to come into play so in simple terms Vector databases store

data in the form of vectors which are just numbers that represent the meanings of words or text or whatever it is and

it's going to store these vectors into a multidimens dimensional database so these vectors are going to help us find

find similar or related information much quicker than sort of like a relational um structured database this one's going

to be using a lot more unstructured data so even if the words are not the exact same for example you're asking about

cars the vector database might also help you find related information about vehicles or automobiles as you can see

in this picture down here we've got um wolf dog cat and then the query is a kitten so it's going to be searching for

a kitten information about kittens and it will kind of be um in this three-dimensional

database store it'll be seeing like similarities based on characteristics of these things and as you can see like

we've got fruits over here and then you might have vehicles down here and you might have like you know information

related to certain types of products up here so that's kind of how this works just as like from a visual perspective

so if you're wondering how Vector databases work in relation to rag the AI is going to convert documents or text

into Vector stores and it's going to put them in the vector database where they need to be then when a question is asked

the system is going going to look for similar vectors and sort of search out the right area to pull information back

um you know relevant documents or data and then once it finds these most relevant vectors it's going to retrieve

that information and then finally it's going to generate an answer for the human once you understand what a vector

database is what Vector stores are you need to understand how can you actually get information into a vector store so

this next slide is going to talk about sort of embeddings and stuff like that all right so embedding data into a

vector database this this slide is going to be kind of tailored towards doing this in n8n there's other ways to but NN

is the way I do it so real quick let's just break down this picture so what's going on here is we're testing the

workflow it's going to be searching a Google Drive for a specific file it's going to pull that file and then we need

to embed it into the pine cone Vector Store Pine Cone is just a vector store database that we use um it just seems to

be you know very cheap very easy to use so this is the one we're using but there's other Vector databases out there

you might have heard of something like super base but this one's really simple then what it's going to do is it needs

to load the information so the type of information coming through whether it's Json or binary it's going to load that

it needs to be able to split it up you know it's going to chunk it up and then it's going to use the open AI model to

embed it into the actual Vector store so I know that this stuff may not make sense yet we'll get into an actual

example in NN where we're building this out and we're getting real PDFs from our Google Drive up into pine cone and we'll

see all that take place but we just wanted to give you a quick visual real quick quick so you can understand what's

going through the first thing I'll touch on real quick um is the default data loader aspect of this so in NN when we

connect the vector store we have to load the data this node is basically just going to allow us to load data from a

previous step flowing through um you know right here and then we need to load it into here so that we can actually

chunk it up and get it embedded into the vector store so this note is pretty much just going to be looking at what kind of

data we're loading in um if it's like Json or if it's binary that sort of stuff and then we can just you know

configure how much we want to pass through stuff like that and then we move into actually text splitting so right

here I have a recursive character text splitter as you can see right here the three options in NN will be character

recursive character or by tokens so the first option is character text splitter this is just going to split the text

into chunks based on a set number of characters so you might want to use this when you want to break down text into

equally sized pieces regardless of where sentences or paragraphs end um and then the next one we have is recursive

character text splitter which I seem to use the most because this one is going to split text by characters but it does

so intelligently because it's going to break down logical points like after a sentence or in between paragraphs stuff

like that but same concept of just chunking stuff down so this is recommended when you want to keep the

text meaningful instead of cutting off a sentence in the middle it's going to split at natural breaks like after you

know a period or a comma something like that and then finally the token splitter this is going to split text based on

tokens which are usually words or subwords that the model understands and you kind of want to use this when you're

working directly with a language model like Chachi BT because it's going to process text in terms of tokens and you

know it's going to chunk It Down based on how the AI model reads the text so you know if you're processing data for a

model it's going to split the text accordingly hopefully I didn't confuse you guys too much maybe I went into too

much detail but just wanted to break down those different types of splitting but best practic is a lot of times you

can just use recursive character so the information stays meaningful but um just a quick summary here so the rag is going

to be um retrieving information from documents right here that we're putting into a vector store in order to give us

intelligent answers then the vector database is going to store text in a way that allows us to quickly and

efficiently search based on meaning not just exact words that are you know hardcoded in we're looking at stuff

that's related to specific meanings of words and then we're going to use a text splitter to um help break down the large

documents into manageable pieces in order to put them into to the vector database and then open I AI here in this

case is just going to embed it into the vector store so that is basically how it's going to work and we'll hop into NN

and actually show you guys this as you can see what we're going to do here is build an RG rag AI agent and in this

workflow we'll be using a Nike earnings PDF and we're going to put that into pine cone which is the vector database

that we'll be using and then we can chat with the agent in order for it to retrieve information about Nike earning

so that we don't have to read through the PDF we you can just ask questions about it all right like I said we're

going to be looking at this PDF of Nike earnings reports so we're going to see this is the PDF that we're looking for

it's 10 pages we don't want to really have to read this thing we want to be able to just chat with an agent and it

can pull the information for us so first up here get some sort of document that you want to put into pine cone Vector

store then as you can see I have this in my Google Drive right here so that we're able to actually you know call this

information and push it into pine cone through nn and then you want to go into pine cone it's just type in Pine cone.

it's free to get started you want to set one up you'll come into here and all you want to do is you're going to create an

index so you can name it whatever you want um I'm pretty much just going to keep everything as is the only thing

that you want to make sure that you set up here is right here you want to set it up by model and you want to choose text

embedding three small so you'll set that configuration and then you'll just hit create index your index is going to pop

up right here if you click into it you can see that there's no information you can see that there's no name spaces in

here um just a really quick explanation of name spaces you can have different name spaces within each index like let's

say I was in here and I had one for um internal documents and then I had one for um client a and then I had one for

client B that's just going to help your agent be able to search for the information quicker because it can sort

of break it down by okay I need to go to this index and I need to go to this namespace and then here's all relevant

information regarding this project or client once you've got all that information set up we are good to hop

into to NN and start pushing information into that pine cone Vector store so the first thing that we're going to do here

is I'm just going to make this a manual trigger in the future you could have this where every time you upload a

document to a certain drive it would do a Google Drive trigger and then it would automatically push that information into

pine cone which is super cool because then your database is going to you know stay up to date every single day every

single time you add more information but right now we're just going to be doing a manual trigger next thing we need to do

is add a Google Drive node because we need to get that information from Google Drive drive into NN so we're going to

click on this plus button going to type in Google and we will see Google drive right here once again lots of actions

the Integrations are awesome but what we're going to do here is download a file so if you haven't got this node

configured yet it should be super easy because you've already set up your consent screen and your client ID and

secret and all that but in here you just need to go and make sure that you have enabled the right API so as you can see

here I've got Google Sheets Google Drive Gmail Google Docs custom search all the different apis that I can use within in

NN so set that up make sure you're connected to the right account and then we're going to be downloading is the

operation and we're grabbing a file the resource and once again we can choose from a list which is awesome we're going

to come in here and look for the Nike press release PDF so I'll grab that and then what we're going to do is just hit

test step because then we can see the information coming back so on the output you can see that

we're getting this information one thing that's really important to know is that it's not coming through as Json there's

no information here it's coming through as binary so we don't have to get too technical on what exactly that means but

we have to just make sure we know how this information is coming through so that later when we want to embed it into

the vector store we can make sure it's getting loaded correctly and I'll I'll show you guys that later but for now

just remember that this PDF is coming through as binary so we can view this PDF make sure it's the right one as you

can see it's Nike earnings so we're good to go here and we can move on to the next step we've got our file next we

need to add the actual pine cone Vector store so so we can push the information into pine cone so we're going to add

this we've got four actions within pine cone right now we're just going to be adding documents to a vector store but

as you can see you could also retrieve you could update all that sort of stuff and we will be retrieving later in order

to actually chat with our agent about this PDF once again it's a little Annoying to have to set up the

credentials for everything but once you have them you're good to go so in here we need to set up the pine cone I'm

going to create new credential and as you can see we need to grab an API key once you hop back into pine cone you can

see obvious you've got your indexes on the left hand side you can go down to API keys and then all you're going to do

is just copy this value with this button right here copy that and then you're just going to really quickly paste that

into the API key hit save and it should go green because our connection is successful now we're actually able to

insert documents to the index so the index that we want to insert to is called sample and for the sake of this

video let's add it to a namespace so click on ADD option Pine code namespace and we will just call this one

Nike and now we're good to go with this node but what we need to do is we need to set up like I talked about earlier

the the default document loader how we're going to check Chunk Up the text and then the actual embedding so first

we will do the embedding I'm going to use open AI you you should have your credential already set up and then we

need to choose the model so if you remember when we set up our pine cone index we set up the model of text

embedding three small so we don't want to do Ada O2 we want to come in here and grab three small so that it's being

being embedded properly then we need to choose this plus button and we're going to do the

default data loader like we mentioned now here is what I talked about with we need to remember how the information is

coming through this Google Drive so remember we came in here we see the output is binary not Json so binary is

how we want the information to come through so in the data loader we need to make sure we're selecting the type of

data is going to be binary otherwise you're probably not going to get any information put into pine cone so we're

good to go here the last step is just to set up the text splitter so like I talked about the differences between

these three as you can see there's also a short little description here so if you forget you can always come in here

and read what they do but we're going to choose recursive character text splitter the chunk size like we talked about is

just how many characters are going to be within each chunk and the overlap um we don't want to have any overlap and chunk

size 1 th I'm sure that's fine for now the PDF is pretty big but we can see how this works so let's just hit save and

then we will test out this workflow so it's a manual trigger so we're going to hit test workflow it's going to grab the

file download the PDF as you can see it went through the data loader it went in here and then it had to embed it until

it came into the actual Vector store so let's hop back over to Pine Cone let's go to our database let's go to the index

called sample we can see that we have information in here now and if we click on names spaces we will see that we just

created a name space called Nike and there are 29 vectors in here and as you can see 29 items left the pine cone

Vector store node all right our information has been successfully put from Google Drive into pine cone now we

need to build an agent workflow that we'll be able to chat with in order to get answers from this PDF all right

we're in a new workflow here and once again we got to add a trigger so the first step is going to be a chat message

because we want to talk to the agent in order for the workflow to start execution so we'll click on chat message

we can leave this as is because we'll be using this button down here to actually you know talk to the agent and that

that's how it's going to work but we have our chat message trigger now we're going to add a new node we can come in

here to Advanced Ai and we see there's a ton of different AI things we can do um there's even some templates up here to

see you know what's possible and you can download those and start playing with them but we're just going to come in

here and grab an AI agent now within this AI agent you have different types of Agents you can use

you've got tool conversational or openi functions agent you can read a little bit about what each of these do but

because we're giving these agent different tools I think that we'll just keep this one as a tools agent come in

here and call this guy our Nike agent and then you can also do things like add a system message you can return

immediate steps you can have him have a max amount of iterations we will add a system message right now it's just going

to say you're helpful assistant we can set this up in a sec once we get all the tools configured but this is where we

sort of tell the agent you know this is your job here's background information here are the tools that you have here's

how you use them here's like an example flow so we'll talk about all that after we get the rest of this workflow

configured we've got our Nike agent and then you can see there's different things we need to set up so the first

one is going to be the chat model I'm going to grab an open AI chat model and connect our credential once again and

then we choose the type of model we want since this is going to be pretty conversational I think I'm going to use

40 it just seems to be the most consistent it's kind of the one that I'm pretty loyal to but sometimes for

smaller things like if you're just labeling emails or if you're um doing some sort of classifier where you just

need to parse the information and see um like a category maybe then you could come in here and grab you know 35 or 40

mini but don't get too caught up on what each model's good at but right now 40 is kind of the most expensive but it is the

most powerful so we set that up with 40 now let's really quickly add a memory so

this is super super easy we just want to grab a window buffer memory um this is super easy because that's all we have to

do we don't have to set anything up you could change the context window length but five chats is how many the model is

going to remember so I'm fine with that but this is a really easy way to give the agent some context of what's going

on otherwise when you're chatting with it let's say you asked um what was Nike's earnings in you know quarter 3

and then if it came back with the information and then you said okay what about quarter 4 it would be like what

are you talking about quarter 4 for what so that's going to give context of oh he just asked about earnings now he wants

to know about quarter the next quarter so just just going to give context to your agent super easy way to add that

memory then finally this is where all the magic happens this is where you can add different tools So within here we

have you know different things that we can give our agent access to of course we've looked at all the different nodes