Cyberbullying Detection AI

This project provides an AI-powered system for detecting cyberbullying and toxic content in text. Built with Streamlit and Hugging Face transformers, it offers an intuitive web interface for analyzing user-entered text.

Features

• Real-time Text Analysis: Instantly analyze input text for harmful content.
• Hate Speech Detection: Identifies and flags hate speech.
• Offensive Language Detection: Detects offensive and inappropriate language.
• Confidence Scores: Provides scores for different categories (Hate, Offensive, Normal) to indicate the likelihood of harmful content.
• Visual Feedback: Uses progress bars and color-coded alerts to highlight analysis results.
• Model Flexibility: Attempts to load PyTorch model with a fallback to Flax if PyTorch fails.

Setup

To set up and run this project locally, follow these steps:

1. Clone the repository (if you haven't already):

   git clone <repository_url>
   cd "Cyber bulling AI"
   

2. Create a virtual environment (recommended):

   python -m venv venv
   

3. Activate the virtual environment:

   • Windows:

     .\venv\Scripts\activate
     

   • macOS/Linux:

     source venv/bin/activate
     

4. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

1. Run the Streamlit application:

   streamlit run app.py
   

2. Open your web browser and navigate to the local URL provided by Streamlit (usually http://localhost:8501).

3. Enter the text you want to analyze in the text area and click the "Analyze Text" button to see the results

4. Enter the text you want to analyze in the text area and click the "Analyze Text" button to see the results.