3 Ways to Develop Your Own Chatbot — from Simple Programs to ChatGPT Alternatives

Not so long ago, ChatGPT took the world by storm. It has revolutionized how we see, build, and interact with chatbots. But not everyone realizes that ChatGPT isn't all that different from bots that you see on websites or in messaging apps.

However, those programs are designed to provide customer service for repetitive, simple queries. What makes ChatGPT stand out is its versatility because of the sheer amount of data it’s trained on.

It might seem impossible to create your own chatbot of similar intelligence. But actually, you can do just that — or build a simpler bot to accommodate your business goals. Whatever your goal, in this article, we explore three methods to build your own chatbot:

1. Using OpenAI’s language generation model
2. Via automatic chatbot builders
3. Fine-tuning your own customized model.

Option 1. OpenAI GPT — work smarter, not harder

Whether you're interested in the programming feats or the possible applications, ChatGPT’s success is certainly inspiring to all. Why not take the technology at its core and build something new on top?

GPT, or Generative Pre-trained Transformer, is a language generation model developed by OpenAI. It uses deep learning techniques to generate human-like responses and improve based on user interactions.

Essentially, it’s the “brain” that you can insert into your chatbot to make it as smart as ChatGPT.

Is it possible to develop a chatbot without GPT? Of course. But if you want it to be just as smart, you’ll have to train your chatbot a lot. In the meantime, OpenAI will release another ChatGPT version that will leave you even further behind. So, a smarter move would be to take the “brain” and fine-tune it to accommodate your own specific goal.

If you want to use GPT in your chatbot, you’ll need to integrate OpenAI’s code into it. OpenAI has instructions that explain the API implementation process step by step. Bear in mind that embedded GPT is not free. It costs nothing for only the first three months unless you run out of free credit points faster. You also need to be familiar with coding; although, the documentation makes it all pretty beginner friendly.

There are various models you can use. The most powerful one is GPT-4. To get this version, you have a few different payment and access options.

However, you might want to create a simpler chatbot — perhaps one that has a limited number of interactions. If that’s the case, check out the chatbot-building instruments below.

Option 2. Automatic chatbot builders — easy, quick, and efficient

This solution is available even to those with little programming expertise. A chatbot builder is a platform that allows developers and even non-technical users to design chatbots. Many of these platforms are zero-code, so creating a chatbot is possible without having to write a single line of code.

It’s almost like assembling Lego blocks, just with chatbots.

Chatbot builders make it simple to generate conversational agents that provide guidance in e-commerce, resolve issues in customer support, and engage users on social media platforms.

Examples of chatbot builders:

• Giosg — drag-and-drop interface with pre-defined templates 
• MobileMonkey — multi-platform bots with a free plan
• Chatfuel — free for servicing up to 50 users

But here’s the thing about all these builders: the more users the chatbot serves, the more expensive it gets. As the chatbot’s user base grows, the service provider's pricing policy demands that you give more and more. So, this solution is more suitable for a limited number of users.

Another point to consider: automatic builders streamline the process of making chatbots, so the end results are more or less the same. They are efficient, of course, but they are lacking in the unique factor. What if you wanted to have more control over how you assemble the chatbot?

The more customized yet complex option is coding your chatbot via dedicated software and a programming language.

Option 3. Programming — customize your chatbot manually

Note: This option is not ideal for beginners. If you want to code your chatbot manually, it will only be as good as your programming skills.

A chatbot is divided into two parts: the “body” and the “brain.” 

• The body is the structure that holds the brain of a chatbot.
• The brain is the neural network that generates human-like speech. 

To build the body, or structure, of a chatbot, programmers use the specialized ChatterBot Python library. The next step is to train its neural network. The three programs widely used for this task are TensorFlow, Keras, and PyTorch. Build your customized chatbot by learning any of them. If you're feeling particularly ambitious, master them all.

While it's true that you only need to learn one framework to train a chatbot, the programs aren’t necessarily interchangeable. All three have their own strengths and weaknesses, and you’ll likely find that learning one may not be enough as each is best suited for different tasks.

Here’s a short explanation of their differences:

• TensorFlow is an open-source software library for dataflow and differentiable programming. It’s highly scalable, flexible, and suitable for large tasks that require complex algorithms and training on vast amounts of data.
• Keras_{A Beginner’s Guide to Deep Learning: Why Data Scientists Use Keras} is a high-level neural networks API written in Python and capable of running on top of TensorFlow. It provides a simplified interface for building and training neural networks.
• PyTorch is an open-source machine-learning library. Compared to TensorFlow, PyTorch is easier to learn and use. Its key feature allows users to change the model structure on the fly.

The best framework to use depends on your specific goal and personal preferences, so it’s a good idea to try each one.

Note that if you want to work with any of these programs, you’ll have to learn Python_{Is Programming Hard? Make It Easy with Python}. IT newcomers often start their journey with this programming language because its syntax is fairly simple to understand. Also, Python has tools that work well for chatbot-building tasks.

If you want to create a complex chatbot

Some businesses require only primitive chatbots that automate the processing of users’ queries. But if you're serious about building an alternative to ChatGPT, you might also want to learn more about the following:

• Natural language processing is a field of artificial intelligence that helps your chatbot understand human speech and talk like a human.
• Machine learning allows you to teach your chatbot to learn and improve. Its subset, deep learning, teaches your chatbot to learn and improve on its own by implementing neural networks.
• API development and integration lets chatbots interact with other software and services, such as Facebook Messenger, Slack, and WhatsApp.
• User experience (UX) design helps with creating simple and intuitive interfaces. A good UX is exactly what makes the difference between a chatbot that people love and one that is ignored.

That’s it! Hopefully, you now have a clear vision of all the skills and tools it takes to build a chatbot. Let’s review the key points:

Your development method depends on the chatbot's complexity

There are three main ways of building chatbots.

1. Very smart & costs money: If you want to build an extremely smart chatbot, integrate OpenAI’s GPT-4 API in your program.
2. Primitive & sometimes free: For tasks that require simple bots (e.g. to process customer feedback), opt for zero-code chatbot builders.
3. Custom & time-consuming: If you need a chatbot that is fine-tuned to your unique goals, the best option might be to code it manually.

What if you hoped your chatbot would pose a full-on challenge to ChatGPT? In that case, you might want to learn more about natural language processing, artificial intelligence, API development and integration, and UX design.

Some of these skills are available in TripleTen's Data Science Bootcamp. Over a nine-month program, you’ll learn to code in Python, master Keras, and acquire machine-learning skills. 

Our students benefit from a simulated work environment within our interactive platform. This approach turns even absolute beginners into confident professionals who are prepared to work in the industry.

After completing our program, you won’t simply be able to build a chatbot — you’ll also become a welcome candidate for positions at prominent tech companies, including OpenAI itself! So, consider applying for the Data Science Bootcamp, and get ready to tap into a new and exciting career, be it a chatbot builder, an AI expert, a data scientist, or anything else that you imagine. Try it out in the Apple App Store or Google Play.