Affordable WhatsApp AI Chatbot Built in Python: Just $6/month

Create a powerful WhatsApp chatbot powered by Google's Gemini AI for just $6/month (WaSenderAPI subscription) plus Google's free Gemini API tier (1500 requests/month). This Python-based solution uses Flask to handle incoming messages via WaSenderAPI webhooks and leverages Gemini's advanced AI capabilities to generate intelligent, conversational responses.

💰 Cost-Effective Solution

• WaSenderAPI: Only $6/month for WhatsApp integration
• Gemini AI: Free tier with 1500 requests/month
• Hosting: Run locally or on low-cost cloud options
• No WhatsApp Business API fees: Uses WaSenderAPI as an affordable alternative

🔥 Key Features

• WhatsApp Integration: Receives and sends messages through WaSenderAPI
• AI-Powered Responses: Generates intelligent replies using Google's Gemini AI
• Media Support: Handles text, images, audio, video, and document messages
• Smart Message Splitting: Automatically breaks long responses into multiple messages for better readability
• Customizable AI Persona: Tailor the bot's personality and behavior via simple JSON configuration
• Conversation History: Maintains context between messages for natural conversations
• Error Handling: Robust logging and error management for reliable operation
• Easy Configuration: Simple setup with environment variables

📁 Project Structure

/whatsapp-python-chatbot/
├── script.py         # Main Flask application and bot logic
├── requirements.txt  # Python dependencies
├── .env              # Environment variables (API keys, etc.)
├── persona.json      # Customizable AI personality settings
└── README.md         # This file

🚀 Setup and Installation

1. Clone the repository (if applicable) or create the files as described.

2. Create a virtual environment (recommended):

   python3 -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip3 install -r requirements.txt

4. Configure Environment Variables: Create a .env file in the project root directory by copying the example below. Do not commit your .env file to version control if it contains sensitive keys.

   GEMINI_API_KEY="YOUR_GEMINI_API_KEY_HERE"  # Free tier: 1500 requests/month
   WASENDER_API_TOKEN="YOUR_WASENDER_API_TOKEN_HERE"  # $6/month subscription
   # Optional: If you change the port in script.py, update it here too for ngrok or other services
   # FLASK_RUN_PORT=5000

   Replace the placeholder values with your actual API keys:

   • GEMINI_API_KEY: Your API key for the Gemini API (free tier available)
   • WASENDER_API_TOKEN: Your API token from WaSenderAPI ($6/month subscription)

🏃‍♂️ Running the Application

1. Development Mode (using Flask's built-in server)

This is suitable for local development and testing.

python3 script.py

The application will typically run on http://0.0.0.0:5001/ by default.

2. Using ngrok for Webhook Testing

WaSenderAPI needs to send webhook events (incoming messages) to a publicly accessible URL. If you're running the Flask app locally, ngrok can expose your local server to the internet.

a. Install ngrok (if you haven't already) from https://ngrok.com/.

b. Start ngrok to forward to your Flask app's port (e.g., 5001):

ngrok http 5001

c. ngrok will provide you with a public URL (e.g., https://xxxx-xx-xxx-xxx-xx.ngrok-free.app).

d. Configure this ngrok URL as your webhook URL in the WaSenderAPI dashboard for your connected device/session. Make sure to append the /webhook path (e.g., https://xxxx-xx-xxx-xxx-xx.ngrok-free.app/webhook).

3. Production Deployment (using Gunicorn)

For production, it's recommended to use a proper WSGI server like Gunicorn instead of Flask's built-in development server.

a. Install Gunicorn:

pip3 install gunicorn

b. Run the application with Gunicorn: Replace script:app with your_filename:your_flask_app_instance_name if you change them.

gunicorn --workers 4 --bind 0.0.0.0:5001 script:app

• --workers 4: Adjust the number of worker processes based on your server's CPU cores (a common starting point is 2 * num_cores + 1).
• --bind 0.0.0.0:5001: Specifies the address and port Gunicorn should listen on.

c. Reverse Proxy (Recommended): In a typical production setup, you would run Gunicorn behind a reverse proxy like Nginx or Apache. The reverse proxy would handle incoming HTTPS requests, SSL termination, static file serving (if any), and forward requests to Gunicorn.

🔄 WaSenderAPI Webhook Configuration

• Log in to your WaSenderAPI dashboard.
• Navigate to the session management section.
• connect you phone number to the session.
• Find the option to set or update the webhook URL.
• Enter the publicly accessible URL where your Flask application's /webhook endpoint is running (e.g., your ngrok URL during development, or your production server's URL).
• make sure you only select only message_upsert.
• seve the changes.

📝 Customizing Your Bot's Personality

The chatbot includes a customizable base prompt that defines the AI's persona and behavior. Edit the persona.json file to change how Gemini responds to messages, making the bot more formal, casual, informative, or conversational as needed for your use case.

{
  "name": "WhatsApp Assistant",
  "base_prompt": "You are a helpful and concise AI assistant replying in a WhatsApp chat...",
  "description": "You are a helpful WhatsApp assistant. Keep your responses concise..."
}

📊 Logging and Error Handling

• The application uses Python's built-in logging module.
• Logs are printed to the console by default.
• Log format: %(asctime)s - %(levelname)s - %(message)s.
• Unhandled exceptions are also logged.
• Important for Production: Consider configuring logging to write to files, use a centralized logging service (e.g., ELK stack, Sentry, Datadog), and implement log rotation.

📚 WaSenderAPI Documentation

Refer to the official WaSenderAPI documentation for the most up-to-date information on API endpoints, request/response formats, and webhook details: https://wasenderapi.com/api-docs

💡 Why This Solution?

This chatbot offers an incredibly cost-effective way to deploy an AI-powered WhatsApp bot without the high costs typically associated with WhatsApp Business API. By combining WaSenderAPI's affordable $6/month subscription with Google's free Gemini API tier, you get a powerful, customizable chatbot solution at a fraction of the cost of enterprise alternatives.