A Guide for AI Chatbot Development. No Coding Required

Author: Andrei Chiril?

In 2 other articles, I’ve looked over use-cases for AI powered Chatbots and AI Chatbot development for people who know how to code. I’ve also promised that there is a way to do this for people who aren’t developers and I am here to deliver!

We will be looking over 2 examples of Chatbots, using different tools and for different use-cases, just to make things more interesting:

• a simple web AI Chatbot that knows your business and can chat with customers
• a WhatsApp chatbot that takes information from your website and answers customers 24/7.?

Please mind that these tools, although they are mostly no-code, might require some basic implementations in order for them to work 100%. They are very easy and will require mostly just connecting different tools between each other or copying some code from one place to another. So no worries, it’s nothing too complicated.

Now, let’s get started with our no-code AI Chatbot development.

Before starting

I will not be giving a step-by-step tutorial as it will make this article extremely long. I just want to show what is possible with these tools.?

If you are looking for something in-depth, check out the links I will be linking to videos regarding AI Chatbot Development that I found useful or documentation for the tools used.

Common concepts and flows for developing AI Chatbots

These AI Chatbot development tools have something in common. They transform the act of writing code into a visual, drag-and-drop interface. All you really need to know is the flow (or the steps) needed. And you need to use the right block or combination of blocks for each of them.

I will be giving you the basic steps but you should check out the links if you find that this solution might be good for your use-case.?

Customer Support AI Chatbot for the web

You have a business that sells toys. It would be cool if your customers could write in your AI Chatbot the type of toy they are looking for (puzzles for 12yo) and the chatbot could tell them if you have any products like that, or not. Then help them with information regarding the hours that you are open followed by instructions on how to get to your store.?

The problem is simple: ChatGPT won’t know the details of your business and won’t be able to answer. But if there would be some way of giving it information regarding your business, then your AI Chatbot could really be useful. Luckily, there is a way to do this and it’s called RAG.

There are a couple of different tools that can do this. But let’s pick FlowiseAI. We will need to simulate the steps for RAG chatbot development.?

• RAG (Retrieval-Augmented Generation) is a framework that lets you include your own data. This helps you create a custom knowledge base for your AI Chatbot.
• It is useful for building an AI Chatbot that knows your business, your products, your processes etc. and can answer to a customer that wants to know more details.

If at any point you don’t understand what I am talking about, then you need to take a look at my previous article. Please check it out in order to understand what “embedding”, “vector store”, and “semantic search” is. If you prefer a video, here is something that will help.?

The process goes like this:?

• You have your documents and you split them into chunks.
• You embed the chunks and you put the embeddings in a vector store.
• You take the input from the user, embed it, and do a semantic search for relevant information in the vector store.
• You give what you find + the user question to the LLM in order to formulate an answer.

How you will do it:

1. Install FlowiseAI onto your computer. Take a look here and see how you can do that.
2. After opening Flowise, just create a new chat flow for your AI Chatbot.
3. Start off with a chain node (add it from the left “+” symbol, “Chains” category), more specifically a “Conversational Retrieval QA Chain”. This chain is used to query a knowledge base and it needs an LLM and a Vector store in order to work.
4. Add a vector store (choose “In-Memory Vector Store” if you just want to do some tests). The vector store will need the documents and an embedding function.
5. Add a document loader and upload files from your computer.
6. Attach a text splitter to the documents loader so that the text can be split into smaller chunks that will be fed to the LLM.
7. Now that we have the documents, we need to embed the text so the AI can make sense of the information. Add an embedding function. Let’s say OpenAI Embeddings.
8. We’ve gone through most of the flow, now we just need to connect everything with an LLM. You can do that by going to “Chat Models” and selecting a model (let’s say ChatOpenAI).
9. Save the chatflow and press the message icon on the top left in order to test out the AI Chatbot.
10. Press on the “</>” icon in order to see embedding options. Just choose the one that you are comfortable with. The easiest way to get the AI Chatbot on your website is to use the HTML code provided in the “Embed” tab. Just copy the code and insert it at the beginning of your < body> tag of your main HTML file.
11. You can also change the appearance of the chatbot by adding different attributes to the code. Check out this video with a full explanation of both step 10 and 11.

And there you have it. You will need to go more in-depth with this tool if you want some more specific behaviour. But, you should know that more complex flows can be created with this. Just take a look at this playlist and go through the videos in order to build your AI Chatbot.

WhatsApp AI Chatbot for small businesses

You are a medical clinic with a small website full of information regarding your services, your doctors, prices, and many more. You receive a lot of questions on your WhatsApp number from your customers. They could easily be answered if they just looked closer on the website. If that’s the case, why not use the information on the website in combination with an LLM in order to build an AI Chatbot that can answer your customers?

The problem is similar to the one in the previous example. But let’s use a different tool. We’ll go with Voiceflow because you will be able to find a lot of tutorials for this.

Here is how you do it:

1. Register to Voiceflow and create a free account.
2. Start by creating an assistant using the “New Assistant” button on the top right corner of the page.
3. Choose “Build AI Assistant” and then pick WhatsApp when you are asked about channels and the English language.
4. Remove the predefined blocks but leave the starting node.
5. Go to “Knowledge Base” on the left menu and add the different pages of your website to the knowledge base by pressing “Add Data Source” —> “URLs”. Then paste in all of the different URLs that you want, one by one.
6. Go back to the “Designer” space using the left menu and let’s start. First, connect a “Text” block (under the “Talk” category) to the “Start” block. Add whatever you want as a first message from the AI Chatbot to the user. You can also use a built-in feature to generate similar messages automatically and let the chatbot use a different one each time.?
7. Add a capture card to the block from the tools menu, listed under “Listen” → “Capture”. Then add a variable called {userQuestion} in the right menu of the capture card. This will record the user’s question in a variable that we can use in other blocks.
8. From here, pass the user question into a new block. You want to send the question to the LLM so you need to choose the “Response AI” card from the “AI” category and create a new block with that card.?
9. In this card you should select “Knowledge Base” as a Data Source and pass it the variable {userQuestion}.
10. Now you have the answer to the user’s question so let’s keep it going and ask the user if there are any other questions. Do this by adding a “Text” cell in the block followed by a “Choice” cell from the “Listen” category. Create 2 paths: yes and no.
11. If the user says no just add another “Text” card with a goodbye text like: “Have a great day!”. We want to be polite. You can also generate more ways of saying this so we get different messages.
12. Grab an “End” card from the “Logic” category and add it to the block. This will end the conversation.
13. If the user still has questions, just add another block with a “Text” cell asking “What can I do for you?”. Then “Capture” the answer and use the same variable as before, {userQuestion}. You just create the same block as in steps 6 and 7.
14. Now loop back to the “Response AI” card from step nr. 8 and that’s about it. Now the user can ask as many questions as needed and always get the answer from the AI Chatbot.
15. You can now test it by pressing the “Run” button on the top right of the page, selecting “Test on WhatsApp” and entering your phone number so you can chat with it in the WhatsApp app.
16. You can also publish it by following the steps of the “Publish” option.

So, that’s about it. It’s not that hard to build such an AI Chatbot. It can be really useful if you are wasting a lot of time answering simple questions from your users.?

Other things you can do

I’ve only shown you some very basic use-cases but these AI Chatbots can get really complex, really fast. For example, you can:

• Promote your YouTube channel. If the user has more than 5 questions regarding what you are selling or your services, just send a second message after the answer telling him “I see you are interested in the subject. Why not take a look at my YouTube channel where I share different aspects of what I do.”
• Use tools like Zapier and connect them to a Google Spreadsheet. When the user gives his email to the chatbot (for example in order to receive a free ebook) you can take that answer and put it in a leads spreadsheet that you created.?
• Understand the intent of the user and react accordingly. If, for example, the user is asking how to return a product, you can create the flow of the conversation so that the AI Chatbot asks what is wrong, if the user is not satisfied, etc. It will gather specific information that it can send through a Zapier connection to another tool where you collect feedback.
• Track orders by giving it access to your orders so that, when the user asks the status of order #1234, the AI Chatbot can answer with: “It left our storage today and is on its way to arriving at your address.” It can then handle follow up questions like “What address did I choose for delivery” or anything else the user might need to know.

Tools for AI Chatbot Development

I’ve only talked about FlowiseAI and Voiceflow but there are many more tools that you can use. They all follow the same principles even though they have different flows and ways of helping you build chatbots.?

Here is a list of some other tools you might want to check out: LangFlow (similar to FlowiseAI), botpress (similar to Voiceflow), WotNot or n8n (more of an automation tool).

At the moment these tools offer similar things so choose one that you like best. Start understanding how to map conversations and you will be able to switch between tools with no problem if needed.

I hope this helped you on your AI Chatbot development journey. Have a nice day and see you around!