Update README.md

# 🌿 Psychological Health Risk Assessment (DASS-12)

This is an automated psychological health evaluation tool based on the simplified **DASS (Depression, Anxiety and Stress Scale)**. It leverages a Machine Learning model to predict potential mental health risk levels based on 12 psychological state questions.

## 🚀 Key Features
- **Instant Assessment**: Interactive interface that provides evaluation results within 5 minutes.
- **Three-Dimensional Analysis**: Calculates and visualizes specific scores for Anxiety, Depression, and Stress.
- **Cloud-Based Storage**: Test results are anonymized and securely stored in a cloud database (Google Sheets) for academic research and trend analysis.
- **Session History**: Supports viewing history logs within the current browser session.

## 🛠 Technical Stack
- **Frontend Interface**: [Gradio](https://gradio.app/)
- **Data Processing**: Pandas, Numpy
- **Machine Learning**: LightGBM (LGBMClassifier)
- **Backend Storage**: Google Sheets API (via gspread)
- **Deployment**: Hugging Face Spaces

## 📁 File Structure
- `app.py`: The main Gradio application logic.
- `DASS_model.bin`: The pre-trained machine learning model.
- `AutoPreprocess.py`: Custom data preprocessing class.
- `requirements.txt`: List of Python dependencies required for execution.

## 🔐 Privacy & Ethics
Privacy is our top priority:
1. **Anonymity**: The "Nickname" input is used solely for the user interface and is **NEVER** transmitted to the database or used in model calculations.
2. **Data Collection**: Collected data includes: timestamp, basic demographics (Gender/Age/Family Size), dimensional scores, and the 12 raw responses.
3. **Disclaimer**: This tool is not a medical device. Results are for reference only and do not constitute a formal diagnosis.

## 👥 Development Team
- Group 4: Mental Health Risk Prediction Team 🌿

README.md

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 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference