Essai Detect

A simple web-based application for detecting LLM-generated text. The system uses BERT model for predictions.

Table of Contents

• Features
• Usage
• Installation
• License
• Acknowledgments

Features

• Message Box - Input text for LLM-generated or Human-written text classification.
• Chat History - Displays recent text input and result.

Usage

1. Input text to be analyze in the Message Box.
2. Pressing the Send button or Enter Key in the keyboard, will trigger prediction.
3. Text must be more than 100 words to maintain a more accurate prediction.
4. Reloading the page will cause the Chat History to be reset.

Installation

Warning

Ensure that Git and Python are installed in your computer.

Warning

Ensure that you have self-trained BERT model in the model directory. If not, you can use the Logistic Regression model instead by changing the load_model(1) to load_model(0) in app.py.

1. Clone this repository using the command git clone https://github.com/Mindkerchief/Essai-Detect.git.
2. Go to directory using cd Essai-Detect.
3. Install dependencies using pip install -r requirements.txt
4. Run the Flask application using python app.py.
5. Open the web app in the browser using http://127.0.0.1:5000.

License

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

Acknowledgments

• LLM - Detect AI Generated Text Dataset: For LLM-generated and Human-written dataset.
• Phosphor Icons: For icon library.