🤖 Gemini API Chatbot.

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.