Create a Highly Accurate Knowledge Base in Voiceflow using Tags API

Summary

This video tutorial guides viewers on creating an accurate knowledge base for AI agents or chatbots using Voiceflow's Tags API. It explains the concept of tagging as a method to efficiently retrieve information, akin to organizing books in a library. The host demonstrates setting up tags in Voiceflow, structuring data for clarity, and using the Tags API to query the knowledge base effectively. The aim is to enhance the AI's ability to provide precise answers by directing it to the right documents based on user queries.

Takeaways

• 📚 The video is a tutorial on creating an accurate knowledge base using Voice Lo tags API, which is essential for AI agents and chatbots.
• 🏷️ Tags are compared to stickers on books in a library, helping AI quickly find relevant information without searching through every document.
• 🛠️ The presenter demonstrates setting up tags in Voice Flow using the Voice Flow tags API, emphasizing the value of a well-structured knowledge base.
• 📝 The process involves creating an assistant in Voice Flow, attaching knowledge-based documents, and then tagging these documents for efficient AI referencing.
• 🌐 The use of a wellness website called Vikasa as an example to illustrate the organization and structuring of a knowledge base.
• 🔍 The importance of clean data input into Voice Flow is stressed, with text files being preferred over PDFs, docs, and URLs to avoid information bloat.
• 📑 The video guides through the steps of uploading documents to Voice Flow, cleaning the data, and attaching them to tags for organized knowledge base management.
• 🔑 An API key is used to connect the Voice Flow assistant with the knowledge base, pulling in the necessary documents for tagging.
• 📝 The creation of tags using the Voice Flow tags API is demonstrated, showing how to assign tags to specific documents for targeted AI queries.
• 🔄 The video includes testing the API to ensure that questions posed to the AI are answered accurately based on the attached tags and documents.
• 🤖 Finally, the script outlines integrating this functionality into a Voice Flow chatbot, allowing it to query the knowledge base effectively using the API.

Q & A

What is the main purpose of creating a knowledge base for AI agents or chatbots?

The main purpose of creating a knowledge base for AI agents or chatbots is to provide them with a structured and organized source of information that they can reference to give accurate and relevant responses to user queries.

What is the analogy used in the script to explain the concept of tags in a knowledge base?

The analogy used in the script is that of a librarian in a big library. Tags are like special stickers on certain books that help the librarian (or AI) know exactly which books to look for first when someone asks a question, making the search faster and more accurate.

Why is it important to have a well-structured knowledge base for an AI agent?

A well-structured knowledge base is crucial because it ensures that the AI agent can provide the right or the best possible answers to queries. Without it, the AI might not be able to find the correct information or might provide inaccurate answers.

What are the recommended data sources for uploading documents to a knowledge base in Voice Flow?

The recommended data sources for uploading documents to a knowledge base in Voice Flow are text files, followed by PDFs, DOCs, and then URLs. Text files are preferred because they are the cleanest and easiest for the AI to read and reference.

How does the script suggest organizing the data for an effective knowledge base?

The script suggests organizing the data in a clean and precise format, with a preference for plain text files. This helps in reducing information bloat and makes it easier for the AI to read the knowledge base correctly and provide accurate answers.

What is the role of tags in structuring a knowledge base for an AI agent?

Tags play a crucial role in structuring a knowledge base by directing the AI agent to reference specific documents for particular questions. This ensures that the AI agent provides accurate and relevant information without getting confused or providing wrong information.

How does the script describe the process of attaching tags to documents in Voice Flow?

The script describes the process of attaching tags to documents in Voice Flow by first creating an assistant and attaching knowledge-based documents. Then, it explains how to use the Voice Flow tags API to create tags and attach them to specific documents, which helps in organizing the knowledge base effectively.

What is the significance of using the Voice Flow tags API in the process of setting up a knowledge base?

The Voice Flow tags API is significant in the process of setting up a knowledge base as it allows for the creation and management of tags. These tags help in categorizing and linking specific documents to particular topics or queries, ensuring that the AI agent can retrieve the correct information efficiently.

How does the script guide the viewer in testing the knowledge base setup using the Voice Flow API?

The script guides the viewer in testing the knowledge base setup by demonstrating how to use the query API in Voice Flow. It shows how to input a question and the relevant tag, and then how to interpret the output to ensure that the AI agent is retrieving the correct information from the knowledge base.

What is the final step described in the script for integrating the knowledge base with a Voice Flow chatbot?

The final step described in the script is to configure the API in Voice Flow to connect the chatbot with the knowledge base. This involves setting up the API step with the correct URL, headers, and parameters, and then testing the system to ensure that it can provide accurate responses based on user queries and the associated tags.

Outlines

00:00

📚 Introduction to Creating a Knowledge Base with Voiceflow

The video introduces the process of creating a highly accurate knowledge base using Voiceflow's tags API. It emphasizes the importance of tags in structuring a knowledge base, comparing it to a library where tags act as stickers on books, directing the AI to the right information quickly. The necessity of a well-structured knowledge base for effective AI agents or chatbots is highlighted, and the video promises a step-by-step guide on setting up tags in Voiceflow.

05:01

🌐 Setting Up the Knowledge Base with Voiceflow

The speaker details the initial steps for setting up a knowledge base in Voiceflow, starting with creating an assistant and attaching knowledge-based documents. The use of a wellness website called 'vikasa' is demonstrated as an example of an organized knowledge base. The process involves copying URLs from the website, importing them into Voiceflow, and emphasizing the importance of clean data for effective AI operation.

10:02

🔍 The Importance of Clean Data for AI Accuracy

This section discusses the challenges of using URLs as data sources due to potential information bloat, which can confuse AI agents. The speaker recommends using text files for sensitive data to maintain the quality of answers. The process of reformatting web data into clean documents is shown, and the newly formatted documents are re-uploaded to Voiceflow for a more accurate knowledge base.

15:03

🏷️ Utilizing Tags to Organize the Knowledge Base

The explanation of tags continues, with the creation of tags using Voiceflow's tags API. The process involves listing documents, obtaining an API key, and using it to connect the API with the knowledge base. The speaker demonstrates how to create tags for different documents and emphasizes the importance of associating tags with the correct documents to guide the AI agent in providing accurate information.

20:03

📝 Attaching Tags to Documents for Specific Queries

The video script outlines the process of attaching tags to specific documents within the knowledge base. This step is crucial for directing the AI agent to the appropriate document when a query is made. The speaker shows how to use the 'attach KB tags to the document' feature in the tags API, ensuring that each document is associated with the correct tag for precise information retrieval.

25:05

🤖 Testing the Knowledge Base with Query API

The speaker describes how to test the knowledge base using the query API to ensure that the tags are correctly associated with the documents and that the AI can retrieve accurate information. The process involves sending a query with specified tags to the API and receiving the correct response based on the tagged documents. The testing interface is used to ask questions and receive answers directly from the knowledge base.

30:07

🔄 Implementing the Knowledge Base in Voiceflow Chatbot

The final steps involve implementing the knowledge base functionality into a Voiceflow chatbot. The speaker discusses creating buttons for different programs within the chatbot and using variables to store user selections. The process of capturing user input and sending it to the knowledge base for a response is detailed, including setting up API calls within Voiceflow to interact with the knowledge base.

35:08

🔑 Configuring API for Voiceflow Chatbot Integration

This section covers the technical configuration of the API within Voiceflow for the chatbot. The speaker explains how to set up the API step, including the method type, URL, headers with API key, and parameters for the request body. The importance of correct formatting, especially with JSON and double quotes, is highlighted to ensure the API functions correctly with Voiceflow.

40:10

📈 Demonstrating the Effectiveness of Tagging in Knowledge Retrieval

The speaker concludes by demonstrating the effectiveness of tagging in retrieving accurate information from the knowledge base. The video shows how the chatbot can provide specific pricing information for different yoga programs based on the tags associated with the user's query. The demonstration reinforces the importance of a well-organized knowledge base with proper tagging for AI accuracy.

🎬 Conclusion and Additional Resources

The video concludes with a summary of the process and an invitation for viewers to engage with the content. The speaker offers help through their AI agency for those needing assistance with AI projects and encourages viewers to explore additional resources, such as other instructional videos on creating chatbots or lead generation systems.

Keywords

💡Knowledge Base

A knowledge base is a structured collection of information that is used to support decision-making and provide answers to queries. In the context of the video, the knowledge base is likened to a library of books, where each book contains specific information that an AI agent or chatbot can reference to answer questions accurately. The script emphasizes the importance of a well-structured knowledge base for the AI to provide the right answers.

💡Voice Lo tags API

The Voice Lo tags API is a tool mentioned in the script that is used to create tags within a knowledge base. Tags are used to categorize and organize information, making it easier for AI agents to retrieve relevant data. The script explains that using this API helps in setting up a highly accurate knowledge base by tagging specific documents, which is crucial for the AI's efficiency in providing information.

💡AI Agents

AI Agents, or artificial intelligence agents, are autonomous systems that can perform tasks, make decisions, or provide information based on programmed instructions and data inputs. In the video, AI agents are being trained to use the knowledge base effectively by referencing tags to find answers to user queries, such as information about yoga programs.

💡Chatbots

Chatbots are computer programs designed to simulate conversation with human users. They are often used for customer service or information provision. The script discusses creating AI chatbots that utilize a knowledge base to provide accurate and quick responses to user inquiries, with tags playing a key role in directing the chatbot to the correct information.

💡Tags

In the context of the video, tags are labels or markers that are applied to specific documents within a knowledge base to categorize the information they contain. The script uses the analogy of stickers on books in a library to explain how tags help an AI quickly locate relevant information when a question is asked, streamlining the process and improving accuracy.

💡Voice Flow

Voice Flow is a platform mentioned in the script that is used to create AI agents and chatbots. It allows users to design workflows and upload knowledge base documents that the AI can reference. The script demonstrates how to use Voice Flow to create an assistant, attach documents, and utilize the Voice Lo tags API for effective knowledge base management.

💡Data Structure

Data structure refers to the way data is organized, stored, and manipulated in a database or system. The script highlights the importance of structuring data correctly within the knowledge base, as this impacts the AI's ability to provide accurate answers. The video provides guidance on organizing data in a clean and precise format for optimal AI performance.

💡API Key

An API key is a unique code used to authenticate requests to an API (Application Programming Interface). In the script, the API key is used to connect the Voice Lo tags API with the knowledge base in Voice Flow, allowing the AI agent to access and utilize the tagged documents for answering queries.

💡Workflow

In the context of AI and chatbot creation, a workflow refers to the sequence of actions or steps that an AI agent takes to complete a task or respond to a user query. The script discusses designing workflows in Voice Flow, which includes setting up the AI agent to interact with the knowledge base and use tags to find relevant information.

💡Variable

In programming and AI design, a variable is a storage location paired with a name, which holds information that can be changed or manipulated. The script explains using variables in Voice Flow to store user selections and inputs, such as the program selected by the user or the question asked, which are then used to query the knowledge base.

💡Capture Step

A capture step is a part of a workflow where user input is recorded or 'captured' for further processing. In the script, the capture step is used to record the user's question after they have selected a program from the provided options, which is then used to query the knowledge base for an accurate response.

💡Query API

A query API is an interface that allows users to send requests to a system and receive responses based on those requests. In the video script, the query API is used to send the user's question and the selected program to the knowledge base, which then returns the relevant information from the tagged documents.

Highlights

Introduction to creating a highly accurate knowledge base using voice Lo tags API, essential for AI agents or chatbots.

Explanation of tags as a method to enhance the accuracy of information retrieval from a knowledge base.

Analogy of tags to stickers on books in a library to prioritize search by an AI, making it faster and more accurate.

Importance of a well-structured knowledge base for providing the right answers in AI systems.

Demonstration of setting up tags in Voice Flow using the Voice Flow tags API.

Use of a wellness website 'vikasa' as an example to illustrate the knowledge base structuring process.

Instructions on creating an assistant in Voice Flow to attach knowledge-based documents for tagging.

Importance of data cleanliness and structure for effective knowledge base operation.

Comparison of different data sources for knowledge base input, emphasizing plain text as the most effective.

Process of uploading and organizing data into Voice Flow for a cleaner knowledge base.

Explanation of attaching documents to tags to ensure the AI references the correct information.

Step-by-step guide on creating tags using the tags API in Voice Flow.

Testing the created tags and their functionality in querying the knowledge base.

Integration of the knowledge base with Voice Flow's chatbot for practical application.

Use of variables in Voice Flow to store user selections and questions for the knowledge base query.

Configuration of the API in Voice Flow to connect with the knowledge base and retrieve answers.

Final testing of the Voice Flow chatbot with the knowledge base to ensure accurate response retrieval.

Conclusion summarizing the process of creating a highly accurate knowledge base in Voice Flow using tags.

Transcripts

hello and welcome in this video I'll

show you how to create a highly accurate

knowledge base using voice Lo tags API

there's a must watch video if you are

creating AI agents or AI chat Bots using

voice law you must probably be wondering

what are tags and how they help you get

accurate information from the knowledge

base let me explain with an example

let's imagine your knowledge base is

like a big Library filled books okay so

when someone asks a question it's like

searching through all the books to find

the answer using tags is like putting

special stickers on those certain books

these stickers help the librarian that

is your AI know exactly which books to

look for at first when someone asks a

question this way the librarian or the

AI doesn't have to search through every

single book but can go straight to the

ones with the special stickers making

the search much more faster and more

accurate so if you asked a question

about yoga the librarian would only look

at books with the yoga sticker on them

this makes finding the right answer much

quicker and easier a knowledge base is

the heart and soul of any AI agent or

chatbot and without a well structured

knowledge base you won't get the right

or the best possible answer for your

query okay now let's see how to set up

tags in voice flow so for this video we

will use voice flow and the voice flow

tags API and I'll leave the links to

both in the description so let's get

started all right this video is going to

be a bit long because we have a lot lot

to cover but I promise you it will be

very valuable and worth your time so

close all your tabs grab a cup of coffee

or your favorite drink and let's get

started don't forget to add this video

to your favorites so you can easily come

back to it later for reference as always

all the links prompts and responses will

be available for free on the source Hub

and I'll leave a link to that in the

description below okay perfect so the

first thing we need to do is we need to

create an assistant in voice flow okay

and the reason we need to create an

assistant is so that we can attach the

voice uh the knowledge based documents

and those knowledge based document is

what we will be tagging it'll all become

very clear once I start doing it okay so

the thing is that so for the knowledge

base what we'll do is we'll actually uh

you you can use any site uh for the

purpose of this video I'm going to use a

website called vikasa they're very

beautifully organized it's a wellness

website uh okay so let's go

there all

right so as you can see out here they

have uh they have multiple programs but

for this video what we'll do is we

uh use like if you go to the foundation

yoga training it has the dates it has uh

you

know all the information about uh this

particular program as well as the

pricing so if you go

down and you can see the pricing as well

okay so it is very very clearly

organized and same thing if you go back

and you say Okay 300 are Advanced and

then it is organized again the same way

you have the dates as well as the

details and the pricing so this is a

perfect example if it is actually the

knowledge base is like this okay so for

the purpose of this video what I'm going

to do is I am going to take the four 1 2

3 and four these four pages okay and uh

so let's copy the URLs and then I'll

show you how to actually add them to

voice flow so this is the first so I

have all the four URLs now let's go back

to voice flow we'll create an assistant

and we will attach this in the knowledge

base all right so

let's go to the assistant and send new

assistant because uh uh knowledge based

test all right modality is going to be

CH since we are using that and then go

to English and let's say

continue okay perfect so now we in the

workspace

okay once you go back you can actually

see within this assistant this is arasa

KB test which we just created you have

something called workflow and knowledge

base so the workflow is where we design

the AI agent and the knowledge base is

where we upload the documents which we

want the AI agent to reference to okay

so to add documents you have multiple

sources here so I'm going to use the URL

since we just copied the URL

and copy this paste it let's say it

doesn't matter let's say monthly to

refresh rate

okay and let's

import so it's importing right now all

right so I want to mention that your

data source needs to be as clean as

possible and structuring your data

correctly is very very important for an

effective knowledge base so when you

input data into voice flow the best type

is text files followed by PDFs and docs

and then only URLs this is important

because when a bot scrapes a web page it

often picks up unnecessary spaces

characters and irrelevant links because

of this this information bloat it can

get harder for an AI to read the

knowledge base correctly and provide

accurate answers make sure you have a

well structured text file for sensitive

data such as uh pricing or dates Etc

this will greatly improve the quality of

your ansers so now you have green marks

next to all the URLs that basically

means that it is a voice flow has

actually uploaded those documents okay

so now if you click on the white portion

next to the URL you will see how voice

flow is storing this data

okay and it's in chunks and as you can

see it is a lot of garbage basically

because you have all of these

TTS uh you know it's not not good at all

actually so uh um yeah the the most

important part is that especially when

you creating an AI agent the AI agent is

as good as the data it gets okay so if

you give garbage it is going to spit out

garbage so we need to make sure that the

data is actually valid and it's in a

very clean format so as I explained

earlier in the video when you're are

uploading data to knowledge base it

needs to be very clean and very precise

okay and the way the voice FL is the

best data is the plain text if you can

actually just get text and put it out

there uh it is very easy for the AI

agent to actually reference the data

okay so then of course is the PDF files

or the doc files and then comes URLs

because the problem with URL is there is

a lot of bloating okay so there's

information bloating because as you can

see uh you know it is chunked out so

first of all there's a lot of probably

this is because of the spaces or and

this has got a lot of URLs as well

because a page also has URLs and other

links as well so probably it is not the

best way to do it okay okay so what I'm

going to do is I will actually create um

you know for these four documents for

these four URLs I'll create a clean

document so if you go to Foundation yoga

what I'm going to do is actually I'm

going to uh you know right click and uh

copy it and put it in a text so that we

can actually use this so the same thing

out here as well just right click and

copy and put it into a text file so it

can be used all right all right so I

have created these four documents now uh

you know if you see this is now the

documents look much cleaner these are

doc files so I copied all of the

information from the website and then

sort of organized it in a way that uh

the AI can easily read it and reference

it okay so I did it for these four and

it's advisable that if you're doing it

for your clients or or for yourself uh

as well for your business it is always

advisable that you actually U you know

take the data and put in a very clean

format so that yeahi can actually read

it and then give right answers rather

than total garbage okay all right so

what I'm going to do is now I'm going to

actually uh delete these

for okay so now what I'll do is I'm

going to reupload uh it in plain text so

that is as I said that was preferable so

let's go back to the documents and I'm

going to open this that's opening in the

text file just copy this and then put it

out

there so this is the document just say

import all right great so now I've

uploaded all the four documents as you

can see uh you know and uh if you click

on these

documents look at the way it is stored

now you know as compared to earlier

because it is so clean and it's very

well formatted so it's much easier for

the AI agent to actually reference the

document and get the right information

okay so the next thing is that we need

to attach these documents to tags now

what you need to understand is what what

are tags and why are they important okay

so a tag is something like it tells the

AI that okay you need to reference only

this particular document for this

particular question so this is what

happens so now when someone asks a

question about uh to the AI agent about

the foundation yoga it will reference

only this particular document this is

the foundation yoga teacher which has

got all the information so it doesn't

get confused and it does not get uh

wrong information you know so it is not

giving if somebody asked pricing for the

yoga uh Foundation yoga teacher training

program it is not giving you pricing for

the advanced okay because they are

structured in a certain way basically so

if you see this is the dates for the

foundation and if you go out

here this is a nicely organized site

that's the reason I'm taking this as

example so if you go to Advanced the

same thing out here it has got the dates

so if somebody is asking for dates for

the foundation yoga program you don't

want the AI to give dates for the

advanced okay so that's where tagging

helps so tagging tells the a agent that

only look at this particular document to

answer this question which is for the

foundation yoga program okay so let's go

ahead and create some tags all right so

the step one in creating tag is so we'll

go to to create tags basically we will

be using uh the tags API which is from

voice FL

okay so I'm going to leave this

particular Link in the description uh so

you can easily uh go to this so the

first thing we need to do is we need to

create a document we'll need to go and

check out a document list all right so

don't worry about this I'm going to

actually uh guide you through this whole

process step by step there is no coding

involved it is a no code solution but of

course I mean you know so don't get uh

bothered by the code which you see out

here uh this is just for reference all

right okay so the first thing we need to

do is we will actually go here and uh

you'll come to the document list now

what is this document list is that it

gets uh you know it goes back to the

knowledge base to the AI agent and says

hey these are the four documents which

we have all right and these are the four

documents which need to be Tagged so

once I go back to uh vicasa uh sorry my

test and uh then we will go to

Integrations and you have an API key

here which we need right now this is the

primary key this is the API keys and you

will just copy this key okay so it's

copied let's go back to our system all

right so I'm going to use the key out

here and what is this going to do is it

is going to connect this particular API

with this knowledge base right here uh

which is our knowledge base these four

documents okay and it will pull these

four documents so it knows that this is

the a agent and I'm going to pull this

information all right so when I say the

document I've connected the AP key and

I'm going to say try it and there you go

so as you can see it is right here all

it's pulled up all the information so

total is four documents data and then so

this is not the code basically okay so

this is the as you can see this is total

of four documents and this is the

document ID you can see the name 200 uh

let me just actually copy this and put

it into a

so it's easier to see all right again

don't go get bogged down by the code

this is just information nothing else

I'm just going to expand

that so you guys can easily see it show

FS all

right okay so now if you can see this is

total of four and there's a data and

then the data says this is 200h hour

foundation yoga training program so this

is the document this is the document ID

which we'll be using and

uh if you see there are no tags out here

okay so this is look at this tags column

this is empty which basically means that

there is no tag uh which is attached to

this document and that will that's

exactly what we'll be creating so that

we can reference the tags when we're

actually talking with the AI agent all

right so okay so the same thing out here

this is tags is empty tag is empty so

this is a different document ID and this

is for 300 Advanced and so on so forth

all right so now we have got the

document list out so the next step is

that so now we've got the document list

now let's create the tags okay so for

that we will close this API and let's go

to the tags API which is right here just

below that and open this so in order to

create tags what we'll do is we will

actually go to the create tag which is

right here create KB tag okay which is

knowledge based tag all right and so it

has zero tags right now if you can see

right and the best part is it

automatically copies the uh the key so

you don't you don't have to reenter it

again and again it has already there

okay so now if you go here and you say

try it it has got a 400 which means

error which which basically means that

there are no tags right now okay so

let's create some tags so in order to

create tags what I'm going to do is I

will actually go down and uh come to

data object okay this is the body

patterns which is the parameters so you

just create it out here and you can say

something like foundation so I'm going

to say U you know so what is the name uh

this is advanced yoga teacher training

let's start with the the first one

Foundation yoga teacher training so ytt

okay so I'm going to create and say

ytt Foundation this is the tag which I'm

using right now okay so I'm going to

this is a string and uh that's it so all

I have to do is now say try

it and it's a 200 perfect so it's

already created the tag so you can see

that this is the tag right now again the

tag is not L to the document we're just

creating the tags okay so there's a tag

ID and there's a tag uh name and we will

later uh join this tag ID with a

document ID so that U you know it knows

exactly what to reference so similarly

we'll do it for all four so I'm just

going to call this ytt foundation so

Advanced all

right so then say try it

again 200 and it's created this one as

well so the next one should be YTD

Yin

okay okay so this is also created and

then finally what was the last fourth

one refresh

okay so let's call this

refresh so tag is something which is

easier to remember so just use those

names and then again let's create

this perfect so it's also created okay

so now all the Four Tags have been

created now if you go back to the tags

API and I want to see the list all right

say C KB tag list let's go here and see

what all tags have been created so if I

go here and say try it now it should

show all the Four

Tags and there you go so all the Four

Tags you we just create this is all is

right here okay okay so now we already

have the tags created everything is

right here okay so let's copy this and

put it into a text document as well all

right

okay all right so now we have all the

tag IDs we have already created that

okay and then from the previous uh text

file if you remember we had the document

ID as well so let me just get that grab

that right here okay so if you remember

we have uh you know all of this uh we

have already created the data

and the tag was empty okay the tag was

empty and this is the data uh the

document ID so in the next step what

we'll do is we will attach this

particular one uh the document to their

respective tags so for this is uh 200 uh

Foundation yoga teacher program so for

this what we'll do is we will actually

attach it with the foundation tag okay

and then the next time we run this you

should see this tag filled about here

okay so let's do that

so after this what we need to do is we

need to attach so there is in the tags

API you have something called attach KB

tags to the document okay so let's go

here and we are here right now okay so

there's nothing right now here all right

uh in this what it says is that it needs

a document ID okay so let's get the

document ID so we will copy the first

one which is this copy this put it here

okay and the data object which is body

PM let's open that add

string okay so once we come here uh you

can see an array what it requires is

existing KB tag label so you need the

label okay uh which is this so we'll say

YT

foundation and then we attach it right

here okay and that's it so now if you

can see it is different uh let me just

say try it

and we have a status of okay which is

that it was a success okay let me do it

for all four of them and then we'll see

exactly uh whether it's attached or not

and how it looks okay okay perfect so uh

I've finished for YT refresh that was

the last one so I've done it for all

four of them okay so after this what

we'll do is we let's go back to the

document API all right and in the

document list so if you now see this is

the first document Okay so then when we

actually generated this particular one

there's nothing in tags this is the

document ID but the tag is empty all

right and now we have attached the tag

to the document so now let's run this

again and actually what I'm going to do

is I'm going to create another document

so you can see all right and let's see

this one and uh let's go to the document

list which is this

one you already have the API and let's

say try

it okay perfect okay so let's copy this

and then put it

here perfect so if you see the

difference between both the documents

okay this is the first one this is the

second one in this there is no tags and

in this you can see the tag ID now right

it's right here ytt Foundation is the

first one and if you go down this is ytt

Advanced and Yin and refresh okay

perfect so now it has attached the

document to the particular tag okay so

now our API business is finished out

here and this is uh so it's all

connected now okay great so now uh we

have the document list we've already

done the tag attachment everything is

ready okay so the final thing is that we

out here we need to test this as well

okay so let's go to the query API now

the query API is used to actually query

the knowledge base okay and that's what

we'll do out here okay so in the query

database if you see we have a sample

request and we need to use that that in

wherever you call the API but let's for

now let's test this out here okay so we

have a testing interface let's go down

and you can ask a question here and put

everything out here okay so let me just

check real quick okay so we already have

our API which basically means that it's

all knowledge bases all

connected okay so what we can do is

Let's test this and uh for the question

I'm going to ask uh what is the program

pricing okay what is the program pricing

chunk limit is equal to two so

essentially what is the program pricing

we have four documents there and uh this

is a very generic question so program

pricing can mean whether you are talking

about the Foundation program pricing or

the advanced program pricing what are

you talking about and that is where the

tag is going to help the tag which we

just created when we say okay the tag is

ytt foundation so it will get the

pricing for the YTD Foundation which is

this okay and uh otherwise if in case we

say what is the program pricing for YT

Advanced it should actually go to let me

just see that real quick okay so it

should go to Advanced and then get the

pricing for this which

is right

here let me just see that wow okay which

is right here okay so the one is 3600

and the other one is 4500 okay so let's

test this so I'm going to say what is

the program pricing I'm not saying uh

anything else and then since says yes

true basically means that okay you want

the AI to generate the

answer settings F tags in tags yes this

is include tag add string and then this

is where we Define the tag and sorry

input the tag which is ytt

foundation so now when we try when we

actually execute this um query what the

system should do is it should go to this

particular document uh which is tagged

with this tag and then get the price ing

for this which is supposed to be 3600

okay I think we don't need to include

anything else and let's say try

it and perfect we got 200 which is okay

let's see the output so the output is

the tution for a 200 hour

foundation yoga training is teacher

training is is 3500 perfect this is

great okay so it's working fine and

let's test this again now with the other

tag so I'm not going to change the

question I'm just going to change the

tag now and I'll say

ytt Advanced okay and let's test this

and now this should become what is the

pricing okay so Advanced is 4500 okay so

now this should become 4500 okay and

let's see

this oh perfect see so now it is giving

the response as 4500 so because the tag

is different it is YTD Advanced perfect

so I this is this is working great now

okay so now what we next thing is the

next step is to actually Implement all

of this functionality into voice flows

chatbot and use the API to get uh to

kind of query the knowledge base and get

the same results okay but this is

working fine this is the we are testing

the API and the API works right now so

it is actually getting all the values

from the knowledge base all right so

let's head over to voice flow just a

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joining the AI community okay let's get

back to our video okay so now we are

back in the assistant uh this is the

knowledge base so let's go to the

workflow this is where we will Design

our AI agent okay and then you can start

addit workflow and we are here I don't

know how this got there so it's a blank

canvas right now so let's start putting

some stuff out here uh the first thing

I'm going to do is I will actually put

in a text just say connect this

thing welcome to Vasa

how can I help you

today okay so let's put this and this is

there after that what we can do is we

can actually add some

buttons so the buttons are for the 10 so

we can actually say hey uh this is for

YTD

foundation so and then add a button we

can put

in

ytt add r

and so on so forth so we'll create those

four buttons so we have these four

buttons right here and then they connect

to something like so the moment the uh

the user comes in he says welcome to

vikasa how can I help you today and then

of course he sees these four options now

when we are quitting the knowledge base

okay it can be only one uh at a time so

one document at a time in the sense that

when you're asking questions you will

know want to know about the ydt

foundation or the ydt advanced or Yin or

refresh whatever the case is okay so we

will use and so we will send this

information to the API which we just

created the knowledge base so that it

Returns the uh the correct answer all

right but so we have four different

options here depending on what the user

chooses okay and then we need to store

that so that we can send that to the

knowledge base so for that basically we

will create a variable a variable is

nothing but it's just a holding Place uh

which tells once the user selects this

uh White Foundation that is what it

holds and then it is passed on to the

knowledge base saying that hey the user

wants the information for ytt foundation

uh using this question or okay or about

this question

sorry okay so uh what I'll do is I will

just quickly create a variable uh let's

see when you actually connect this it is

in the actions we'll go to something

called set variable and we won't have it

out here so let's create one when you

click on this this thing there's an

option to create a

variable and I'm going to call it

something like U test here and I'm going

to say program you can name it anything

you want it doesn't matter okay you can

call it strr program you can just call

it program you can call it underscore

program whatever you prefer okay and the

description of this is that it uh tells

us what exactly

is uh What uh

program tells us what

program has the user selected okay it'll

all start making sense just give me some

time okay and say just create variable

so now it's created the variable okay so

what we'll do is enter value applies to

this thing so once this is so let's say

for example when I run this bot so

welcome to vikasa how can I help you

today and then you have YTD Foundation

Advanced YTD Yen and refresh okay so

when he selects this we want this

program this s Str program which is the

variable we just created to have the

value ytt Foundation when he selects

this that particular uh variable will

have the uh the value Yen and so on so

forth okay and so that is the reason we

have this and so once you go here it'll

go here and it'll of course there's

nothing connected so it'll finish off

but this is how it is done so again

it'll all start making sense in some

time okay so all four of them are done

now so basically when he selects this

thing this is going to get U active uh

this the value of the St program the

variable which we have is going to be

this okay and I'm going to show you how

it'll all tie up so now the next step is

that uh we will ask the question okay so

let's ask the question to the user for

that we will use a

text so we can say something

like what is your question and this is I

mean of course you know don't we can

always change the text but this is just

to for example so what is your question

for uh

program and then we will open the

bracket and you can see SDR program

right here and we will use this

okay all right so basically what's going

to happen is it's going to say what is

your question for the program ydd

Foundation or ydd Advanced or whatever

the user selects based on that it will

actually uh assign that okay and let's

connect this to all one

two three and four okay

so this is done after this then what uh

is your question for the program and

then you need to use a capture step so

where is the capture this is basically a

capture step which will actually capture

the user's input because you're asking

them a question right so then now they

need to input and uh this goes into last

utterance which is whatever the user

inputed so now what we have is we have a

capture step and in this the user is

going to whatever the user enters uh

this this is going to be captured in the

last atance I like using variables so

similar to what we did out here like you

know we used the SDR program uh to

capture what user was inputting as a

program Choice what we'll do is we'll

create two more variables so let's go

and create two more variables one is

question asked so uh we call the

variable question asked which means that

whatever the user inputs in the capture

step it is in last utterance but uh I

prefer using uh questions asked

basically as an creating own variable

okay so we'll do that and the next is

answer okay and what basically means

that when we connect it to the step and

the API returns an output that will be

captured in the variable again it's

going to make sense once I do it so let

me just create those variables right now

just going to go back where you have

variables right now you can see all the

variables are right here and I can

create a new variable okay so I'm going

to create something called question

a

okay let's create this you can put a

description or you can let it be it

doesn't matter and uh then is the next

one is

answer oh

sorry okay now let's done let's create

this as

well okay so we have two more variables

two new variables and uh you can always

add a description if you want uh so I'm

going to add that later on okay now

let's go back to our

agent okay so we are right here okay so

once the user enters captur in the

capture step what I'll do is I will

after this action I'll say set variable

and applies to we just created question

asked okay and then the value of this

should be last utterance so this is what

last utterance a system variable so this

is what it actually captures from the

user when he enters that and I'll show

it to you okay and it those goes into

this thing uh into questions asked so

let me just show you exactly what I

captured uh let's put a text step

here and I'm going to say just to be

more clearer let's say stdr

program is equal to and then I'm going

to put an stf

program value and this is just going to

Output it so that you know exactly what

the variables values are and what is

coming in and the next is what we just

created question asked question

is asked okay and which is equal to and

then question asked all right so the

purpose of this particular block is that

it will just input what the user has

selected okay so let's run this and I'm

going to show this to you so that it

makes sense why we creating or using

variables okay welcome to vikasa how can

I help you so let me this time I'm going

to use YTD

Advanced

okay so what is your question for

program YTD Advanced and I can say what

are the start

dates for the program okay or something

like

that

and if you if you see out here the value

St Str program is equal to Y Advanced

and the question asked the the Val the

variable value is what are the start

dates for the program I'm sorry for the

mistake out here uh the start mistake

okay

uh so this is exactly what it is sending

to the API okay these are the two values

basically so it'll send this question

and it the S Str program is uh YTD

Advanced so now what is going to happen

is that the API is going to look at this

document the advanced document and it is

going to see how can I answer this

question what are the start dates for

this program and then it is going to get

a response back okay and that response

we will capture in the variable which is

created which is called the answer okay

and I'm going to show that to you but

first what we'll do is we will actually

U configure the API and uh that we'll do

right now all right so for configuring

that API what we'll do is we will go to

the API step let's put it out here we

connect this so that it goes inside here

and okay so this is where we will need

to actually get a lot of information I'm

going to use information from here uh

from this particular thing okay so the

first thing is it's asking where whether

it's a get or a post response so a PO

get is generally to get information out

a post is that you are actually giving

some input to the API all right so right

here we are sending in uh we are sending

in the two uh two variables right here

question asked and SDF program so we'll

use a post which basically means that we

are sending these two variables and

based on this please give us the answer

okay and uh after this is your header

and uh so we need a URL so for this we

will go here and copy this

URL

okay the next is the header so header is

where you need to put in your API key

okay because it needs to be

authenticated it needs to know that okay

it this is coming from this particular

agent which has got this API key so API

key is sort of an identification all

right so we will use this this is the

API key which we were using and so we

will copy this and of course it has to

have a key value pair

so we will use authorization here

okay I'm just going to type it in small

cases

authorization

okay so this is done okay and uh so now

it is basically when it sends the

request it will send the API key along

with this so that the system knows that

oh it's coming from this particular AI

agent and this is what I need to know

what I need to do

sorry the params so params is the

parameters the parameters are these two

values okay so now here we'll go into

query

API okay so basically this is so when

you query uh the query API is that

you've already created the documents

you've created the tags now whatever

query comes from the user I'm going to

use that and I will actually generate a

response in the AI and then send it back

to you okay so that is what exactly this

quy API does okay and it needs a format

in the body should be in this format

okay so this is of course a sample

request so we will modify this according

to us and so let's go back and we'll

paste it out here uh from our system

what we actually had generated initially

so I think now everything is all set uh

you know it's everything connected let's

take a quick check on everything so the

API the URL should be a post Tye because

we are sending in the variables uh we

are sending in those two variables you

know the question asked as well as uh

what is this St strr program and then we

getting a output back so the the API

type should be post and then after that

you are doing the URL so the URL should

be from here and you'll pick this up in

the query this is the URL okay and uh

yeah and then the authorization in the

headers make sure that you need you need

to put in the API key and the second

header make sure that you put in

content-type is application uh / Json

this is important uh because without

this I've seen that the system uh you

know it has unexpected Behavior so it's

always better to put this okay then we

have the parameters which are the

variables and then of course um this is

our ra Json and we are ready to test one

important thing I wanted to cover I just

wanted to let you guys know is I just

copy this and I'm going to show it to

you if you see the code and this is

important because the thing is that and

I spent a lot of time on this actually

because I was not able to figure this

out the quotation marks is double quote

should be like this because when you are

actually writing it and typing it and

you do a quote from the keyboard it

comes like this you see the difference

let me just actually yeah see this is

the double quotes from the keyboard and

this is the quote it is expecting and it

just uh you know behaves weirdly and the

answer output is not exact and so I was

testing it and I was not able to figure

out exactly what's going on wrong and

then when I actually uh copied this that

is when I came to know okay so just copy

this and put it out here and should be

all good to go okay it's the same thing

out here so this is fine okay

and now let's test it so uh we'll do a

first uh regular test through this thing

uh let's test it from here itself and

then we'll run the whole program so the

question asked is what is the program

pricing and right now I'm using a tag

YTD Foundation okay so if you notice

what is the program pricing now what is

a program pricing is a generic question

because if you go to vikasa it can be so

what is the program pricing can be for

the advanced yoga or it can be for

uh Foundation yoga or it can be for Yin

or refresh anything all four any any of

the four of them okay so it is a generic

thing and based on the tag the system

will respond you know when I say YTD

Foundation now the system knows that

okay we need to say Pro program pricing

for we need to see the program pricing

for YTD Foundation now if I do the tag

as YTD Advanced it should give the price

for uh the advanced uh right here the

300H hour Advanced uh pricing okay so

now let's test this for ydd foundation

right here and let's say

generate and now it's going to the API

and it's going it's got the result back

we have a 200 okay and now if we go to

the output let's see the output the

output of the tution is okay it's right

here okay

3,500 and I'm going to test it again

with Advanced I'm not going to change

the question and that's where the

tagging actually helps let's say send

request again but in this case I'm going

to make this as YT advanced

all right and let's see generate now it

should give you the pricing for YTD

Advance which is

4,500 yeah so this is Advanced which is

4,500 and that should be your answer so

if you go down and we see the output the

output is the pricing for 300 Advance

perfect is

4,500 okay so that is the beauty of

tagging so when you actually tell the

system that okay just use this

particular document or this particular

page to answer the question

uh it actually just uses that page

information okay uh so all right so now

this is we have done this raw let's use

the system to actually generate the

response so what we'll do is let's run

this from here and run

test okay so welcome to Vasa how can I

help you today and I'm going to say ytt

Foundation what is the question for

pricing so I'll say pricing that's it

nothing else and let's see what it comes

up

with excellent so the tuition for 200 R

Foundation yog Got Run is 3,500 okay so

again let's run this one more

[Music]

time and now I'm going to say

Advanced what is the question again I'll

say pricing that's it

the pricing for 300H hour advanced yoga

is 4,500 perfect okay so as you saw this

is working perfectly now and we got the

tags working and this is how you

actually connect I use the tags uh with

the documents uh so that you can

actually uh you know your knowledge base

is highly accurate and uh yeah so

hopefully you found this video helpful

and that's it now we have created a

highly accurate knowledge base in voice

flow using TX API I I hope you like this

video and found it helpful also we are a

full service AI agency so if you need

help with building an AI agent or some

other AI project for your business do

check out my AI automation agency flip

bites you can also schedule a free 30-

minute Discovery call with me I'll drop

all the links in the description finally

here's another awesome step-by-step

video on how to create a lead generation

air chatbot from scratch or you can

watch another video that I'm sure you'll

find very use useful I can't wait to see

you in future videos thanks for watching

and I'll see you next time