🚀 RADD - Real-time AI-Driven Document Detector

RADD is an intelligent document analysis tool that leverages advanced NLP models to extract, classify, and visualize insights from text files. Built with Streamlit, Transformers, Torch, and Pandas.

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📌 Features

• 📤 Upload and process various text-based documents
• 🤖 Apply pre-trained or custom NLP models (e.g., BERT, RoBERTa)
• 📊 Visualize predictions and document insights
• ⚡ Real-time interactive UI using Streamlit
• 🧹 Efficient text handling with Pandas

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🛠️ Tech Stack

Technology	Purpose
Streamlit	Interactive web UI
Transformers	NLP model inference
PyTorch	Deep learning model backend
Pandas	Data preprocessing and analysis

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🚀 Getting Started

✅ 1. Clone the Repository

git clone https://github.com/Pranaykamble000/radd.git
cd radd

## 🛠 Create a virtual environment
python -m venv env
env\Scripts\activate

## 📦 Install Independencies
pip install -r requirements.txt

## Run the Streamlit app
streamlit run app.py

## 📂 Project Structure
radd/
├── app.py                  # Streamlit main app
├── model/                  # Pre-trained models or checkpoints
├── utils/                  # Helper scripts (e.g., preprocessing)
├── data/                   # Sample input/output files
├── requirements.txt        # Dependencies list
└── README.md               # Project documentation

### 📄 License
This project is licensed under the **MIT License**.  
See the [LICENSE](./LICENSE) file for more details.


### 🙌 Acknowledgments
Streamlit – For building elegant, interactive web apps effortlessly.
HuggingFace Transformers – For access to state-of-the-art NLP models.
PyTorch – For providing the deep learning engine.
Pandas – For powerful data manipulation tools.

###✨ Author
Pranay Kamble
📫 GitHub: @Pranaykamble000

Let me know if you want to:
- Add deployment steps (e.g., on Streamlit Cloud or Heroku)
- Include a demo video/GIF
- Automatically download models when the app runs

Happy building!