WhatsApp AI Bot using Twilio, Flask, and GPT-4Free

This project implements a WhatsApp chatbot that uses Twilio for message handling, Flask for the server, and GPT-4Free to generate AI responses. The bot listens for messages sent to a WhatsApp sandbox and responds with intelligent replies based on the input message.

Features

Receive WhatsApp messages using Twilio’s API.
Respond to messages using AI-based responses from GPT-4Free.
Deployable using ngrok for local testing or any other hosting service.

Prerequisites

Before running this project, ensure you have the following:

Python 3.9 installed (minimum, might have to update to 3.12)
A Twilio account with a configured WhatsApp sandbox
Flask for handling the web server
Ngrok for local testing or any other service to expose your local server
GPT-4Free installed for AI responses

Project Setup

Clone the Repository:

git clone https://github.com/MariaSan-tos/Whatsapp-BOT---GPT.git
cd Whatsapp-BOT---GPT

Create a Virtual Environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install Dependencies: Ensure that pip is up to date:
```
pip install --upgrade pip
```
Then install the dependencies:
```
pip install -r requirements.txt
```

Configure Twilio: You will need your Twilio account SID, Auth Token, and the WhatsApp sandbox number. Replace these values in bot.py:

account_sid = 'YOUR_TWILIO_ACCOUNT_SID'
auth_token = 'YOUR_TWILIO_AUTH_TOKEN'
from_='whatsapp:+YOUR_TWILIO_WHATSAPP_SANDBOX_NUMBER'

Run Flask App: Start your Flask server:
```
python bot.py
```
Expose Localhost to Public (ngrok): Run ngrok to expose the Flask server:
```
ngrok http 5000
```
Copy the forwarding URL provided by ngrok (e.g., https://xxxxxxxx.ngrok-free.app).
Configure Twilio Webhook: In your Twilio console, set the "When a message comes in" webhook URL to:
```
https://xxxxxxxx.ngrok-free.app/whatsapp
```
Make sure the HTTP method is POST.
Test the Bot: Now, send a message to your Twilio WhatsApp sandbox number. The bot will respond with AI-generated replies based on your input.

File Structure

.
├── bot.py                 # Main Flask application and Twilio logic
├── requirements.txt       # Dependencies for the project
└── README.md              # Project documentation

Dependencies

The required dependencies are listed in the requirements.txt file. Key libraries include:

Flask: For handling the web server.
Twilio: For interacting with the WhatsApp API.
requests: For making HTTP requests (used for interacting with GPT-4Free).
g4f: Client for GPT-4Free (if implemented).

To install all dependencies, use:

pip install -r requirements.txt

Environment Variables (Optional)

You can use environment variables to store sensitive data such as Twilio credentials. Create a .env file in the root of the project and add the following:

TWILIO_ACCOUNT_SID=your_account_sid
TWILIO_AUTH_TOKEN=your_auth_token

Load these variables in your Python script using python-dotenv:

from dotenv import load_dotenv
load_dotenv()

account_sid = os.getenv('TWILIO_ACCOUNT_SID')
auth_token = os.getenv('TWILIO_AUTH_TOKEN')

Troubleshooting

502 Bad Gateway on ngrok: Ensure your Flask server is running on port 5000 and the webhook URL in Twilio matches the ngrok forwarding address.
No Response from Bot: Check the Twilio logs in the console for errors and ensure the Flask server logs show incoming messages.
Missing curl_cffi error: Install the missing module with:
```
pip install curl_cffi
```

License

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