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https://github.com/alitindrawan24/gemini-chatbot

A simple chatbot using Node.js, Express, and the Gemini AI API.
https://github.com/alitindrawan24/gemini-chatbot

chatbot express-js gemini-ai

Last synced: 11 months ago
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A simple chatbot using Node.js, Express, and the Gemini AI API.

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README

          

# Gemini Chatbot

A simple chatbot using Node.js, Express, and the Gemini AI API.

## Setup

1. **Clone the repository:**

```bash
git clone https://github.com/Alitindrawan24/Gemini-Chatbot.git
cd gemini-chatbot
```

2. **Install dependencies:**

```bash
npm install
```

3. **Set up environment variables:**

Create a `.env` file in the project root and add your Gemini API key:

```
GEMINI_API_KEY=YOUR_ACTUAL_API_KEY_HERE
```

4. **Run the server:**

```bash
npm start
```

The server will start on port 3000 (or the port specified in your environment variable).

5. **Open in browser:**

Navigate to `http://localhost:3000` in your web browser to interact with the chatbot.

## Project Structure

- `index.js`: The main server file, handling API requests and communication with the Gemini AI.
- `public/`: Contains the frontend files (HTML, CSS, and JavaScript).
- `index.html`: The main HTML file for the chatbot interface.
- `style.css`: Styles the chatbot interface.
- `script.js`: Handles user interaction and communication with the server.
- `README.md`: This file, providing information about the project.

## How it works

1. The user types a message in the input field and submits the form.
2. `script.js` sends the message to the server (`/api/chat`) using a POST request.
3. The server (`index.js`) receives the message, sends it to the Gemini AI model, and gets a response.
4. The server sends the Gemini's reply back to the frontend.
5. `script.js` displays the reply in the chatbox.

## Improvements

- Add error handling for API requests.
- Implement a loading indicator while waiting for the Gemini response.
- Add user authentication and chat history management.
- Improve the user interface with more styling and features.
- Deploy the chatbot to a platform like Netlify or Vercel.