🤖 Gemini API Chatbot (Learned API Integration)

I did not build the entire chatbot , it is inspire by learning from YouTuber Rohit Negi for getting knowledge of "how API integration work".I focused on understanding how the Gemini API works and how to connect it to my project.

What I Learned and Integrated:

I did not build the entire chatbot from scratch but learned how to use an existing AI Chatbot codebase and integrate it into my own blog and e-commerce websites. I focused on understanding how the Gemini API works and how to connect it to my project. Below is how I applied this knowledge to enhance user interactions on my site.

This is a simple AI chatbot built using the Gemini API from Google. The chatbot takes user input and returns intelligent responses, demonstrating how to connect and use large language models in a web app.

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📘 About This Project

This project was created to learn how to integrate the Gemini API into an application. While I didn’t build the entire app from scratch, I focused on:

• Setting up the Gemini API
• Making API calls and handling responses
• Displaying chatbot messages in a UI

Some parts of the UI and structure were built using existing tools or templates, which helped me focus on learning how AI integration works in practice.

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🧠 What I Learned

• How to set up and authenticate the Gemini API
• Making asynchronous API requests
• Handling user input and rendering responses
• Basic front-end integration with AI

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🔧 Technologies Used

• Gemini API (Google AI)
• JavaScript / HTML / CSS (or React if used)
• [Add framework/tool if applicable: e.g., Vite, Bootstrap, etc.]

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🚀 Future Improvements

• Add user authentication
• Improve UI/UX
• Add context memory to chatbot
• Deploy the chatbot to a live site (e.g., Vercel, Netlify)

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📌 Disclaimer

This project was created for learning purposes. Some components were assisted by tools or templates to focus on the core goal: understanding Gemini API integration. I plan to improve and expand this project manually over time.

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🙋‍♂️ About Me

I'm actively learning web development and AI integration. Building small but meaningful projects like this helps me grow and understand how modern tools work in real-world applications.

This project demonstrates how to integrate the AI Chatbot into a web application using the Gemini API. The repository provides a basic structure for building an AI-driven chatbot, which can respond to user input in real-time.

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Features:

• AI-driven chatbot powered by Gemini API to provide intelligent responses.
• Easy-to-implement integration for web projects.
• Designed for interactive user experience in blogs or e-commerce websites.

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Technologies Used:

• Frontend: HTML, CSS, JavaScript (React.js) ,Next.JS
• Backend: Node.js (for handling server-side requests, if applicable)
• API: Gemini AI for generating dynamic responses
• Version Control: Git, GitHub

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How to Use this Repository:

1. Clone the Repository: Clone the repository to your local machine:

   git clone https://github.com/VedantPadole52/AI-Chat-Bot.git

2. Install Dependencies: Navigate to the project folder and install necessary dependencies:

   npm install

3. Set Up the Gemini API Key:

   • Sign up on the Gemini AI platform (or any platform that provides an AI API).
   • After signing up, obtain your API key from the Gemini platform.
   • Create a .env file in your project directory and add the following:

   GEMINI_API_KEY=your_api_key_here

4. Run the Project: Start the project locally using the command:

   npm start

   This will launch the project in your browser, where you can interact with the chatbot.

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What I Learned and Integrated:

Although I didn’t write the full codebase for the chatbot, I focused on understanding the integration of Gemini API into my web project. Here’s what I did:

• Learned how to connect the Gemini API key to the project.
• Understood how to send requests to the API and handle responses.
• Integrated the chatbot into my personal project (blog/e-commerce website) to provide users with an interactive AI assistant.
• Customized the integration based on my project’s requirements (e.g., adding the chatbot feature to the UI of my website).

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How This Can Be Used in Your Own Project:

You can clone this repository and integrate the chatbot into your own project by following these steps:

• Replace the default API key with your own Gemini API key.
• Customize the frontend UI to match your project’s design.
• Modify the backend (if needed) to suit the specific requirements of your app.
• Use the chatbot to provide AI-driven responses to users in your web app.

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Contributing:

Feel free to fork this project and improve upon it. Some ideas for improvement include:

• Extending the AI capabilities of the chatbot.
• Customizing the user interface to make it more engaging.
• Enhancing security and error handling in the API requests.

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Live Demo Link:

https://ai-chat-bot-three-ashy.vercel.app/

Final Thoughts:

I used this AI chatbot as a learning tool to understand how to integrate an external API into my own project, which allowed me to add intelligent features to my website. While I didn't build the entire chatbot code, I was able to modify and apply it in real-world use cases.