🚀 NiagaBot - Smart WhatsApp Business Automation

NiagaBot adalah bot WhatsApp pintar untuk automasi perniagaan yang menggunakan AI Qwen3-Omni. Bot ini membantu anda mengautomasikan komunikasi perniagaan, broadcast, penjadualan mesej, auto-reply, dan banyak lagi!

Your Smart Business Automation Companion powered by Advanced AI

✨ Ciri-Ciri Utama

🤖 Automasi Pintar AI

• AI Multimodal: Proses teks, imej, audio, dan video dengan AI Qwen3-Omni
• Auto-Response Pintar: Balas mesej pelanggan secara automatik
• Chat Flow Builder: Bina conversation flow untuk customer service

📣 Broadcast & Marketing

• Mass Broadcast: Hantar mesej ke ramai pelanggan serentak
• Scheduled Messages: Jadualkan mesej untuk hantar kemudian
• Progress Tracking: Monitor status hantar real-time

👥 Group Management

• Welcome/Farewell Messages: Automatically greet new members
• Anti-Spam Protection: Keep your groups clean and safe
• Group Synchronization: Manage multiple groups easily

📊 Analytics & Reporting

• Dashboard Lengkap: Pantau semua aktiviti bot anda
• Statistics & Metrics: Analisis prestasi mesej dan broadcast
• Export Data: Export analytics ke CSV/JSON

🔐 Enterprise Features

• Multi-User Support: Team collaboration dengan role-based access
• REST API: Integrate dengan sistem lain
• Web Dashboard: Control panel yang cantik dan mudah
• Secure Authentication: JWT-based security

Architecture

WhatsApp Web (Browser Automation)
          ↓
   WhatsApp Bot Core
          ↓
  Qwen3-Omni Integration
    ↙              ↘
Local Model    DashScope API

Prerequisites

• Node.js (v16 or higher)
• npm or yarn
• WhatsApp account for testing
• (Optional) DashScope API key for cloud-based Qwen3-Omni access

Installation

1. Clone the repository:

git clone <repository-url>
cd whatsapp-bot-mcp

2. Install dependencies:

npm install

Configuration

The bot can be configured in two ways:

Option 1: Local Model (Resource Intensive)

To run Qwen3-Omni locally, you'll need:

• High-end GPU (32GB+ VRAM recommended)
• Significant RAM (64GB+ recommended)
• Proper Python environment with required dependencies

This option requires installing additional dependencies that are not included in this package due to their size and complexity.

Option 2: Alibaba Cloud/DashScope API (Recommended for Most Users)

This is the easiest way to use Qwen3-Omni without the need for high-end hardware:

Option A: Melalui DashScope (Versi Mudah)

1. Daftar akaun di DashScope
2. Dapatkan kunci API anda dari dashboard:
   • Lawati DashScope Console
   • Navigasi ke bahagian "API Keys"
   • Cipta kunci API baru atau gunakan yang sedia ada
3. Kemas kini config.json:

{
  "dashscope": {
    "enabled": true,
    "apiKey": "kunci-api-anda-di-sini",
    "model": "qwen3-omni"
  }
}

Option B: Melalui Alibaba Cloud (Untuk Pengguna Enterprise)

1. Daftar akaun di Alibaba Cloud
2. Aktifkan perkhidmatan DashScope atau ModelStudio
3. Dapatkan kunci akses melalui konsol Alibaba Cloud
4. Gunakan endpoint API yang sesuai:

{
  "dashscope": {
    "enabled": true,
    "apiKey": "kunci-akses-anda-di-sini",
    "model": "qwen3-omni",
    "apiEndpoint": "https://dashscope.aliyuncs.com/api/v1"
  }
}

How to Get Your API Key:

1. Sign up for an account:

   • For DashScope: dashscope.aliyuncs.com
   • For Alibaba Cloud (global): Alibaba Cloud

2. Get your API key:

   • Visit the DashScope Console
   • Navigate to "API Keys" section
   • Create a new API key or use an existing one
   • Copy the API key for use in your configuration

3. Secure Storage of API Key (Recommended): Instead of hardcoding your API key in configuration files, use environment variables:

   # Set environment variable (Linux/Mac)
   export DASHSCOPE_API_KEY="your-api-key-here"
   
   # Set environment variable (Windows)
   set DASHSCOPE_API_KEY="your-api-key-here"
   
   # Or create a .env file in your project directory
   echo "DASHSCOPE_API_KEY=your-api-key-here" > .env
   

   Then reference it in your config.json:

   {
     "dashscope": {
       "enabled": true,
       "apiKey": null,
       "model": "qwen3-omni"
     }
   }
   

Secara alternatif, anda boleh menyalin fail konfigurasi contoh dan mengemaskininya:

cp config.example.json config.json
# Kemudian edit config.json dengan kunci API anda

Free Tier & Pricing:

• DashScope menawarkan kuota percuma untuk permulaan
• Pengebilan bayar-mengikut-penggunaan untuk keperluan yang lebih tinggi
• Semak halaman harga DashScope untuk kadar semasa

Free Tier & Pricing:

• DashScope offers a free tier with limited usage for getting started
• Pay-as-you-go pricing for higher usage requirements
• Check the DashScope pricing page for current rates

Security Best Practices

When using DashScope API, follow these security best practices:

1. Never commit API keys to version control

   • Add .env and config.json to your .gitignore file
   • Use environment variables instead of hardcoded keys

2. Use environment variables for API keys

   # Create .env file
   echo "DASHSCOPE_API_KEY=your-api-key-here" > .env
   
   # Add to .gitignore
   echo ".env" >> .gitignore
   

3. Limit API key permissions

   • Create keys with minimal required permissions
   • Use different keys for different environments (development, staging, production)

4. Monitor API usage

   • Regularly check your usage in the DashScope console
   • Set up alerts for unusual activity or usage spikes

5. Rotate keys regularly

   • Change your API keys periodically
   • Immediately rotate any compromised keys

Usage

1. Start the bot:

npm start

2. Scan the QR code with your WhatsApp mobile app to log in

3. The bot will start monitoring for messages and responding using Qwen3-Omni

How It Works

1. Message Monitoring: The bot continuously checks for new messages in WhatsApp Web
2. Message Processing: Incoming messages (text or media) are processed by Qwen3-Omni
3. Response Generation: Qwen3-Omni generates appropriate responses based on the input
4. Response Sending: Responses are sent back through WhatsApp Web

Qwen3-Omni Capabilities

Qwen3-Omni provides advanced multimodal processing including:

• Text Understanding: Process and respond to text messages in multiple languages
• Image Analysis: Analyze images and respond to visual content
• Audio Processing: Transcribe and understand audio messages
• Video Understanding: Process video content with both visual and audio analysis
• Multimodal Reasoning: Combine information from multiple modalities for comprehensive understanding
• Real-time Interaction: Stream responses in both text and natural speech
• Multilingual Support: Supports 119 text languages, 19 speech input languages, and 10 speech output languages

Supported Modalities

1. Text: Process natural language queries, conversations, and document analysis
2. Images: Recognize objects, scenes, text (OCR), and visual elements
3. Audio: Speech recognition, music analysis, sound classification, and audio captioning
4. Video: Video description, scene analysis, and audio-visual understanding

Voice Options

When using audio generation capabilities, Qwen3-Omni supports multiple voice options:

• Ethan: A bright, upbeat male voice with infectious energy
• Chelsie: A honeyed, velvety female voice with gentle warmth
• Aiden: A warm, laid-back male voice with boyish charm

Contributing

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

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Qwen3-Omni by Tongyi Lab
• DashScope API for cloud-based AI access
• Playwright/Puppeteer for browser automation
• Model Context Protocol for tool integration

Kelebihan Menggunakan Alibaba Cloud/DashScope

Lihat faedah terperinci menggunakan Alibaba Cloud atau DashScope untuk akses Qwen3-Omni.