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
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.