telecomsxchange/OTS

What is Open Source Text Shield (OTS)?

OTS (Open Source Text Shield) is an AI-driven solution designed to enhance the security of telecom networks by detecting and filtering spam and phishing messages in real time. This application leverages both BERT and FastText models for efficient text classification.

Getting Started

Prerequisites

• Python 3.8 or later
• FastAPI
• pydantic
• torch
• transformers
• fasttext
• BERT

You can install the necessary libraries using pip:

pip install fastapi pydantic torch transformers fasttext

Installation

Clone the repository to your local machine:

git clone https://github.com/TelecomsXChangeAPi/OpenTextShield/

Navigate to the cloned directory:

cd OpenTextShield

Running the Application

Start the server by running:

uvicorn main:app --host 0.0.0.0 --port 8001

The application will be available at http://localhost:8001.

Usage

Predicting SMS

To predict if an SMS is spam, phishing, or ham (regular message), send a POST request to /predict/ with a JSON body containing the SMS text and the model to use (bert or fasttext).

Example using curl:

curl -X POST "http://localhost:8001/predict/" -H "accept: application/json" -H "Content-Type: application/json" -d "{\"text\":\"Your SMS content here\",\"model\":\"bert\"}"

Feedback Loop

To provide feedback on predictions, send a POST request to /feedback-loop/ with relevant feedback data.

Example using curl:

curl -X POST "http://localhost:8001/feedback-loop/" -H "accept: application/json" -H "Content-Type: application/json" -d "{\"content\":\"SMS content\",\"feedback\":\"Your feedback here\",\"thumbs_up\":true,\"thumbs_down\":false,\"user_id\":\"user123\",\"model\":\"bert\"}"

Download Feedback

To download the feedback data for a specific model, send a GET request to /download-feedback/{model_name}.

Example using curl:

curl -X GET "http://localhost:8001/download-feedback/bert"

Acknowledgements

Special thanks to the team at TelecomsXChange (TCXC) for their invaluable contributions to this project.