README.md

metadata

title: Corpus Collection Engine
emoji: 👀
colorFrom: purple
colorTo: indigo
sdk: gradio
sdk_version: 5.42.0
app_file: app.py
pinned: false
license: mit
short_description: AI-powered platform for preserving Indian cultural heritage

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

🇮🇳 Corpus Collection Engine

Team Information

• Team Name: Heritage Collectors
• Team Members:
  • Member 1: Singaraju Saiteja (Role: Streamlit app development)
  • Member 2: Muthyapu Sudeepthi (Role: AI Integration)
  • Member 3: Rithika Sadhu (Role: Documentation)
  • Member 4: Golla Bharath Kumar (Role: developement stratergy)
  • Member 5: k. Vamshi Kumar (Role: App design and user experience)

AI-powered platform for preserving Indian cultural heritage through interactive data collection

📋 Setup & Installation

Prerequisites

• Python 3.8 or higher
• pip package manager
• Git (for cloning the repository)

Quick Start

1. Clone the Repository

   git clone [repository-url]
   cd corpus-collection-engine
   

2. Create Virtual Environment

   python -m venv venv
   
   # On Windows
   venv\Scripts\activate
   
   # On macOS/Linux
   source venv/bin/activate
   

3. Install Dependencies

   pip install -r requirements.txt
   

4. Run the Application

   streamlit run corpus_collection_engine/main.py
   

5. Access the App Open your browser and navigate to localhost:8501

Alternative Installation Methods

Using Docker

docker build -t corpus-collection-engine .
docker run -p 8501:8501 corpus-collection-engine

Using the Smart Installer

python install_dependencies.py
python start_app.py

🌟 What is this?

The Corpus Collection Engine is an innovative Streamlit application designed to collect and preserve diverse data about Indian languages, history, and culture. Through engaging activities, users contribute to building culturally-aware AI systems while helping preserve India's rich heritage.

🎯 Features

🎭 Interactive Cultural Activities

• Meme Creator: Generate culturally relevant memes in Indian languages
• Recipe Collector: Share traditional recipes with cultural context
• Folklore Archive: Preserve stories, legends, and oral traditions
• Landmark Identifier: Document historical and cultural landmarks

🌍 Multi-language Support

• Hindi, Bengali, Tamil, Telugu, Marathi, Gujarati, Kannada, Malayalam, Punjabi, Odia, Assamese
• Native script support and cultural context preservation

📊 Real-time Analytics

• Contribution tracking and cultural impact metrics
• Language diversity and regional distribution analysis
• User engagement and platform growth insights

🔒 Privacy-First Design

• No authentication required - start contributing immediately
• Minimal data collection with full transparency
• User-controlled privacy settings

🚀 How to Use

1. Choose an Activity: Select from meme creation, recipe sharing, folklore collection, or landmark documentation
2. Select Your Language: Pick from 11 supported Indian languages
3. Contribute Content: Share your cultural knowledge and creativity
4. Add Context: Provide cultural significance and regional information
5. Submit: Your contribution helps build culturally-aware AI!

🎨 Activities Overview

🎭 Meme Creator

Create humorous content that reflects Indian culture, festivals, traditions, and daily life. Perfect for capturing contemporary cultural expressions.

🍛 Recipe Collector

Share traditional family recipes, regional specialties, and festival foods. Include cultural significance, occasions, and regional variations.

📚 Folklore Archive

Preserve oral traditions, folk tales, legends, and cultural stories. Help maintain the rich narrative heritage of India.

🏛️ Landmark Identifier

Document historical sites, cultural landmarks, and places of significance. Share stories and cultural importance of locations.

🛠️ Technical Architecture

Built With

• Frontend: Streamlit with custom components
• Backend: Python with modular service architecture
• AI Integration: Fallback text generation for public deployment
• Storage: SQLite for local development, extensible for production
• Analytics: Real-time metrics and reporting
• PWA: Progressive Web App features for offline access

Project Structure

corpus_collection_engine/
├── main.py                 # Application entry point
├── config.py              # Configuration settings
├── activities/            # Activity implementations
│   ├── meme_creator.py
│   ├── recipe_collector.py
│   ├── folklore_collector.py
│   └── landmark_identifier.py
├── services/              # Core services
│   ├── ai_service.py
│   ├── analytics_service.py
│   ├── engagement_service.py
│   └── privacy_service.py
├── models/                # Data models
├── utils/                 # Utility functions
└── pwa/                   # Progressive Web App files

🧪 Testing

Run the test suite:

python -m pytest tests/

Run specific tests:

python test_app_startup.py

🚀 Deployment

Hugging Face Spaces

1. Upload files to your Hugging Face Space
2. Use app.py as the entry point
3. Ensure requirements.txt and .streamlit/config.toml are included

Local Production

streamlit run corpus_collection_engine/main.py --server.port 8501

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

📝 License

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

🌟 Why Contribute?

• Preserve Culture: Help maintain India's diverse cultural heritage for future generations
• Build Better AI: Contribute to creating more culturally-aware and inclusive AI systems
• Share Knowledge: Connect with others who value cultural preservation
• Make Impact: See real-time analytics of your cultural preservation impact

📈 Platform Impact

Track the collective impact of cultural preservation efforts:

• Total contributions across all languages
• Geographic distribution of cultural content
• Language diversity metrics
• Cultural significance scoring

🔧 Development

Environment Setup

# Install development dependencies
pip install -r requirements-dev.txt

# Run linting
flake8 corpus_collection_engine/

# Run type checking
mypy corpus_collection_engine/

Configuration

• Copy .env.example to .env and configure your settings
• Modify corpus_collection_engine/config.py for application settings

📞 Support

• Issues: Report bugs and request features via GitHub Issues
• Documentation: Check our comprehensive guides in the docs folder
• Community: Join our discussions via GitHub Discussions

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Start preserving Indian culture today! 🇮🇳✨

Every contribution matters in building a more culturally-aware digital future.