🚀 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

Clone the repository:

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

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)

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

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

Option B: Melalui Alibaba Cloud (Untuk Pengguna Enterprise)

Daftar akaun di Alibaba Cloud
Aktifkan perkhidmatan DashScope atau ModelStudio
Dapatkan kunci akses melalui konsol Alibaba Cloud
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:

Sign up for an account:
- For DashScope: dashscope.aliyuncs.com
- For Alibaba Cloud (global): Alibaba Cloud
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

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:

Never commit API keys to version control
- Add .env and config.json to your .gitignore file
- Use environment variables instead of hardcoded keys

Use environment variables for API keys

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

# Add to .gitignore
echo ".env" >> .gitignore

Limit API key permissions
- Create keys with minimal required permissions
- Use different keys for different environments (development, staging, production)
Monitor API usage
- Regularly check your usage in the DashScope console
- Set up alerts for unusual activity or usage spikes
Rotate keys regularly
- Change your API keys periodically
- Immediately rotate any compromised keys

Usage

Start the bot:

npm start

Scan the QR code with your WhatsApp mobile app to log in
The bot will start monitoring for messages and responding using Qwen3-Omni

How It Works

Message Monitoring: The bot continuously checks for new messages in WhatsApp Web
Message Processing: Incoming messages (text or media) are processed by Qwen3-Omni
Response Generation: Qwen3-Omni generates appropriate responses based on the input
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

Text: Process natural language queries, conversations, and document analysis
Images: Recognize objects, scenes, text (OCR), and visual elements
Audio: Speech recognition, music analysis, sound classification, and audio captioning
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.

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