These days, it feels like there’s an AI chatbot for everything. Need help with homework? Stuck on a coding problem? Want to research a random topic? These virtual assistants can answer just about any general question you throw at them. They’re becoming our go-to partners for learning, creating, and problem-solving. But have you ever wanted a chatbot that doesn’t just give generic answers but understands and responds with information specific to your needs?

What if you could build your own AI chatbot, even as a beginner? Thanks to modern tools like the Google Gemini API and Next.js, you don’t need to be an expert or have a powerful computer to get started. Building your assistant is more achievable than you might think.

In this guide, you’ll learn how to create a simple chatbot from scratch. We will cover everything from setting up your project and integrating the Google Gemini API to building a basic, user-friendly chat interface with Next.js. You’ll also learn how to shape your AI’s responses to your needs. By the end, you’ll have a working chatbot and the foundational skills to continue your journey into AI-powered applications.

Getting Started Before You Build: Key Concepts & Tools

Before building your chatbot, we’ll cover the essential concepts and tools you’ll soon use. Understanding these basics will make the rest of the tutorial much easier to follow, even if you’re new to development or AI.

What is a Chatbot?

A chatbot is a computer program that renders conversations with users. Chatbots can answer queries, provide necessary information, or help users complete tasks.

What is an API?

An Application Programming Interface (API) is a machine that allows software programs to communicate with each other. APIs make it possible for apps to share data or functions without having to know exactly how each other works internally. In this project, you’ll use an API to connect your chatbot to Google’s powerful AI models.

Why Google Gemini API?

Google Gemini API is a cloud-based service that lets you send prompts (questions or instructions) and receive intelligent, AI-generated responses. It’s easy to use, reliable, and integrates well with modern web apps, making it an excellent choice for beginners who want to add AI features to their projects.

Why Next.js?

Next.js is a React framework that simplifies building fast, scalable web applications. It supports frontend and backend logic, making it ideal for projects that need server-side API routes and modern user interfaces.

What You’ll Need

• Basic JavaScript and React knowledge: Don’t worry if you’re not an expert, as this guide is beginner-friendly!
• Node.js and npm: These are tools for running JavaScript on your computer and managing project dependencies.
• A Google account: Needed to access the Gemini API.

Now that you’re equipped with knowledge of the basics let’s take a look at a real-world example of what you can achieve by the end of following this guide:

Project Wingman

Wingman is a university assistant I developed for my senior high school alma mater, the University of Makati. Through a simple chat interface, it aims to help students, faculty, alums, and guests answer general questions about the university, such as enrollment procedures, office contacts, department organizations, and more.

Key Features:

• Answers university-related questions in real time
• Friendly and helpful responses tailored to the university’s community
• Simple, intuitive chat interface built with Next.js
• Secure handling of user data and API keys
• Uses Google Gemini API for intelligent, conversational replies

Wingman was built using the same steps and tools you’ll learn in this article. By the end of this guide, you’ll have the foundation to create your own AI chatbot for your school, organization, or any project you have in mind.

If you’re eager to try Wingman out for yourself, you can test it out here!

Setting Up Your AI Project & Securing Your API Key

Now, we can start building a new project for our AI chatbot. This section will walk you through the first step in building your own AI chatbot: setting up your development environment and getting access to the API.

Step 1: Create a New Next.js App

Open your terminal and run:

npx create-next-app chatbot
cd chatbot

This will scaffold a new Next.js project for you.

Step 2: Install Required Packages

Install the Google Gemini SDK:

npm install @google/genai

You can also install any other packages you’ll need as you go if you expand your project in the future.

Step 3: Get your Google Gemini API Key

1. Go to Google Gemini API documentation
2. Follow the instructions to create a project and generate your API key.
3. Never share your API key publicly.

Step 4: Store your API Key Securely

Create a .env.local file in the root of your project and add your API key:

GEMINI_API_KEY= -insert-your-gemini-api-key-here-

This keeps your key safe and out of your codebase.

Tip: Never commit your .env.local file to public repositories

Now, you can connect your project to the Google Gemini API!

Connecting to Google Gemini API

Now, you can connect your project to the Google Gemini API! This lets your chatbot send user questions and receive natural, intelligent responses.

Step 1: Initialize the Gemini Client

Import the Gemini SDK and initialize it using your API key from the environment variable:

Step 2: Create a Function to Send Prompts

Write an async function that sends the user’s prompt to Gemini and returns the AI’s response.

Add a basic error handling and retry logic for reliability:

Step 3: Use the Function in Your API Route

• When a user sends a message, call your function with the user’s prompt (and any system instructions or chat history you want to include).
• Return the AI’s response to the front end.

With this setup, your chatbot can now communicate with Google Gemini and provide intelligent, context-aware answers!

Building a Simple Chat Interface

Now that your backend can communicate with the Google Gemini API, you can proceed to work on creating a basic chat interface so users can interact with the AI chatbot. A user-friendly chat interface is essential for any chatbot project. A chat interface must contain an input box, a message display area, and basic state management.

Simple Chat UI Parts:

• Message List: Displays the conversation history, showing user and AI messages.
• Input Box: This is where users can type and send their questions.
• Send Button: To trigger the message to your backend/API.
• Loading Indicator: Show feedback while waiting for the AI’s response.
• Message Formatting: Use libraries like react-markdown for rich text or add a typing animation for a more interactive feel.

You can use React’s useState to manage messages and input and useEffect for stylish animations like typing effects.

Things you can try:

• Add avatars or icons for user and AI messages.
• Use a library like react-markdown to support formatted responses.
• Implement a typing animation for the AI to make the chat feel more dynamic.
• Add buttons for copying, liking, or regenerating responses.

Remember, your chatbot’s features and design could constantly be improved as you go.

Customizing Your AI’s Behavior & Responses

Creating your chatbot also means you can shape its personality, tone, and knowledge to fit your needs and audience. Chatbots have system prompts or system instructions that determine their purpose.

Tips for Customizing your AI:

• Build well-structured system instructions for your chatbot that guide the AI’s behavior.
• Prompt Engineering. Experiment with different instructions to capture the tone, style, and level of detail you want. For example, you can ask the AI to be formal, friendly, or brief.
• Implement Contextual Responses. Include previous messages or users’ chat history in your prompt to help the AI remember conversations and provide more relevant answers.
• Apply Handling Limitations to encourage users to provide clear questions and feedback to help the AI improve its responses.
• Be clear with your chatbot’s purpose. You can update your system instructions to enhance your chatbot.

Testing and Improving Your AI

Now that your chatbot is running see how it performs and identify gaps and areas for improvement. Pay attention to how accurate and relevant the responses are. Take notes on what works and what doesn’t. Continue to refine your system instructions or adjust your prompts for better results.

Allow your friends to test your chatbot and share their experiences. Real user feedback is invaluable for identifying issues you may have overlooked, such as functions you never considered for your chatbot’s uses, and determining improvements that could enhance your chatbot.

Make sure to update your chatbot as you develop it. Revise your prompts, refine its interface, and add new features as needed. Monitor your backend for errors or failed API calls, and address these issues promptly to ensure a smooth user experience.

Improving your chatbot is an ongoing journey. Each round of testing and feedback will help you create a more reliable and user-friendly AI assistant.

Conclusion

Congratulations! You’ve just learned the essentials of building your AI-powered chatbot using Google Gemini API and Next.js. Along the way, you explored key concepts, set up a secure project, connected to a powerful AI service, and created a simple yet functional chat interface.

Remember, your chatbot does not have to be perfect. Continue exploring, building, and testing new ideas and features. The world of AI development is full of possibilities, and now, you have the foundation to make your mark.

References

• What Is a Chatbot? | IBM
• What Is an API? |  AWS
• Gemini API  |  Google AI for Developers
• Next.js Docs | Next.js