Gemini CLI Chat Bot

A powerful command-line interface and programmatic API for chatting with AI using Google's Gemini model. Have interactive conversations or get quick answers right from your terminal!

Features

• 🤖 Interactive chat sessions with memory
• 💡 Quick single-question mode
• 🎨 Beautiful CLI interface with loading spinners
• 📦 Easy-to-use programmatic API
• 🔧 TypeScript support
• 🚀 Built on Google's Gemini AI model

Installation

Global Installation (for CLI usage)

npm install -g @dj-bot07/ai-chat-cli

Local Installation (for programmatic usage)

npm install @dj-bot07/ai-chat-cli

Setup

Before using the package, you'll need a Gemini API key from Google. You can get one from the Google AI Studio.

There are two ways to set up your API key:

1. Create a .env file in your project root:

GEMINI_API_KEY=your_api_key_here

2. Set it as an environment variable:

# Windows (PowerShell)
$env:GEMINI_API_KEY="your_api_key_here"

# Linux/MacOS
export GEMINI_API_KEY="your_api_key_here"

CLI Usage

Interactive Chat Session

Start an interactive chat session where you can have a conversation with the AI:

gchat chat

In chat mode:

• Type your messages and press Enter to send
• Type 'exit' to end the session
• The chat maintains context of your conversation

Quick Questions

Ask a single question and get an immediate response:

gchat ask "What is the capital of France?"

Programmatic Usage

Basic Usage

import { AIService } from 'gemini-cli-chat-bot-dj';

// Initialize with your API key
const aiService = new AIService('your_api_key_here');

// Ask a single question
try {
  const response = await aiService.chat('What is the capital of France?');
  console.log(response);
} catch (error) {
  console.error('Error:', error.message);
}

Chat Session

import { AIService } from 'gemini-cli-chat-bot-dj';

async function chatExample() {
  const aiService = new AIService('your_api_key_here');
  
  // Start a chat session
  const chatSession = await aiService.startChat();
  
  try {
    // Send multiple messages in the same context
    const response1 = await chatSession.sendMessage('Tell me about Paris.');
    console.log('AI:', response1);
    
    const response2 = await chatSession.sendMessage('What about its famous landmarks?');
    console.log('AI:', response2);
  } catch (error) {
    console.error('Error:', error.message);
  }
}

chatExample();

With Environment Variables

import dotenv from 'dotenv';
import { AIService } from 'gemini-cli-chat-bot-dj';

// Load environment variables from .env file
dotenv.config();

const aiService = new AIService(process.env.GEMINI_API_KEY);

Error Handling

The package includes built-in error handling for common issues:

try {
  const response = await aiService.chat('Your question here');
  console.log(response);
} catch (error) {
  if (error.message.includes('API key')) {
    console.error('Invalid or missing API key');
  } else {
    console.error('An error occurred:', error.message);
  }
}

TypeScript Support

The package is written in TypeScript and includes type definitions. You get full type support out of the box:

import { AIService } from 'gemini-cli-chat-bot-dj';

const aiService = new AIService(process.env.GEMINI_API_KEY!);

interface ChatResponse {
  text: string;
  timestamp: Date;
}

async function getResponse(): Promise<ChatResponse> {
  const response = await aiService.chat('Hello!');
  return {
    text: response,
    timestamp: new Date()
  };
}

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

ISC

Support

If you encounter any issues or have questions, please file an issue on the GitHub repository.