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Open Text Shield (OTS)

Open Text Shield (OTS) is an open-source, real-time filtering and classification tool for SMS and messaging traffic. It helps detect and block spam, phishing, and malicious content, providing a powerful solution for telecom operators, messaging providers, and any application that processes message traffic, such as those using SMPP, SIP, RCS, or SMTP.

Features

  • Real-Time Detection: Instantly classify and block spam, phishing, and other unwanted messages.
  • Machine Learning Models: Leverages advanced models like BERT to ensure high accuracy.
  • Flexible Integration: Compatible with any application capable of making HTTP requests, including those using SMPP, SIP, RCS, and SMTP.
  • Web API: Simple and efficient API for message analysis and predictions.
  • Open Source: Free to use and modify, with commercial support available for advanced use cases.

Quick Start with Docker

Setting up Open Text Shield is quick and easy with Docker. Follow these steps to get started:

1. Build Docker Image (Recommended)

# Clone the repository first
git clone https://github.com/TelecomsXChangeAPi/OpenTextShield.git
cd OpenTextShield

# Build with mBERT model included (679MB)
docker build -t opentextshield .

2. Run the Docker Container

# Run with both API and frontend
docker run -d -p 8002:8002 -p 8080:8080 opentextshield

# Alternative if port 8080 is busy
docker run -d -p 8002:8002 -p 8081:8080 opentextshield

Alternative: Use Pre-built Image

docker pull telecomsxchange/opentextshield:latest
docker run -d -p 8002:8002 -p 8080:8080 telecomsxchange/opentextshield:latest

Access Points:

3. Send a Message for Prediction

Once the container is running, you can send HTTP requests to the API to classify messages.

Example curl request:

curl -X POST "http://localhost:8002/predict/" \
-H "accept: application/json" \
-H "Content-Type: application/json" \
-d "{\"text\":\"Your SMS content here\",\"model\":\"bert\"}"

Example Response:

{
  "label": "ham",
  "probability": 0.9971883893013,
  "processing_time": 0.6801116466522217,
  "Model_Name": "OTS_mBERT",
  "Model_Version": "bert-base-uncased",
  "Model_Author": "TelecomsXChange (TCXC)",
  "Last_Training": "2024-03-20"
}

API Documentation

The API accepts the following parameters:

  • text: The message content to be analyzed.
  • model: The machine learning model to use (e.g., bert).

For more information on API endpoints and parameters, please refer to the full documentation in the OpenTextShield GitHub Repository.

Contributing

We welcome contributions to Open Text Shield! Please check the contributing guide for guidelines on how to get involved.

License

Open Text Shield is open-source and licensed under the MIT License.