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Contributing to IndicRAG

Thank you for your interest in contributing to IndicRAG! This project aims to make scientific research accessible across Indian languages through advanced multilingual RAG capabilities.

🚀 Getting Started

Prerequisites

  • Python 3.8+
  • Git
  • Basic understanding of RAG systems and NLP

Setup Instructions

  1. Fork the repository

  2. Clone your fork

    git clone https://github.com/your-username/IndicRAG.git
cd IndicRAG

  3. Set up development environment

    python -m venv venv
source venv/bin/activate  # Linux/Mac
# or
venv\Scripts\activate  # Windows

pip install -r requirements.txt

  4. Configure environment variables

    cp .env.example .env
# Edit .env with your API keys (Groq, etc.)

  5. Verify installation

    python test_pipeline.py
python example_query.py

🛠️ Development Workflow

1. Create a Feature Branch

git checkout -b feature/your-feature-name
# Examples:
# - feature/add-tamil-support
# - fix/embedding-dimension-mismatch
# - docs/update-api-examples

2. Make Your Changes

  • Write clean, well-documented code
  • Follow the existing code style and structure
  • Add inline comments for complex logic
  • Update relevant documentation

3. Test Thoroughly

# Run test pipeline
python test_pipeline.py

# Test with different languages
python example_query.py --lang hi  # Hindi
python example_query.py --lang bn  # Bengali
python example_query.py --lang ta  # Tamil

# Test API endpoints (if running locally)
curl -X POST http://localhost:8000/api/query \
  -H "Content-Type: application/json" \
  -d '{"query": "आर्टिफिशियल इंटेलिजेंस क्या है?", "language": "hi"}'

4. Commit Your Changes

git add .
git commit -m "feat: add Tamil language support with Indic tokenizer"
# Use conventional commits: feat, fix, docs, style, refactor, test, chore

5. Submit a Pull Request

  • Push to your fork: git push origin feature/your-feature-name
  • Open a PR on GitHub
  • Provide a clear description of changes
  • Reference related issues (e.g., "Closes #42")
  • Wait for review and address feedback

🎯 Priority Areas for Contribution

🔥 High Priority

  • Indian Language Support: Add support for additional Indic languages (Tamil, Telugu, Kannada, Malayalam, Punjabi, Odia, etc.)
  • Translation Quality: Improve translation accuracy for technical/scientific terms
  • Embedding Models: Test and compare performance of different multilingual embedding models (Indic-BERT variants, MuRIL, etc.)
  • Performance Optimization: Reduce query latency, implement caching strategies
  • Bug Fixes: Fix any reported issues, especially language-specific edge cases

🚀 Medium Priority

  • Advanced Reranking: Implement cross-encoder models for better result ranking
  • Citation Extraction: Automatically extract and format citations from research papers
  • Query Expansion: Add query reformulation for better retrieval
  • Code-Switching Support: Handle mixed language queries (e.g., Hinglish)
  • Document Preprocessing: Better handling of scientific notation, equations, tables

💡 Nice to Have

  • Additional Formats: Support for HTML, EPUB, XML documents
  • Kubernetes Deployment: Production-ready K8s templates
  • Monitoring: Dashboards for query performance and system health
  • Load Testing: Scripts to test system under load
  • Voice Integration: Support for voice queries in Indian languages
  • Mobile App: Native mobile application

📝 Code Guidelines

Python Style

  • Follow PEP 8 style guide
  • Use type hints for function signatures
  • Write docstrings (Google style preferred)
  • Keep functions focused (single responsibility)
  • Maximum line length: 100 characters

Example:

def translate_query(query: str, target_lang: str) -> str:
    """
    Translate user query to target language.
    
    Args:
        query: Input query string
        target_lang: ISO 639-1 language code (e.g., 'hi', 'bn')
    
    Returns:
        Translated query string
    
    Raises:
        ValueError: If target_lang is not supported
    """
    # Implementation here
    pass

Documentation

  • Update README.md when adding user-facing features
  • Update ARCHITECTURE.md for system design changes
  • Add examples in examples/ directory
  • Document API changes in docstrings
  • Include language-specific considerations

Testing

  • Test with at least 3 different Indian languages
  • Verify both English and Indic script queries
  • Check edge cases (empty queries, special characters, code-switching)
  • Test with different document types (PDF, TXT, scientific papers)
  • Verify Docker/API deployments work

Language Support Checklist

When adding a new language:

  • Add language code to supported languages list
  • Test translation quality with technical terms
  • Verify embedding model handles the script
  • Test with real scientific documents
  • Add examples in examples/ directory
  • Update documentation

🐛 Reporting Issues

When reporting issues, please include:

For Bugs

  • Description: Clear explanation of the problem
  • Steps to Reproduce: Detailed steps to recreate the issue
  • Expected Behavior: What should happen
  • Actual Behavior: What actually happens
  • Environment: OS, Python version, relevant dependencies
  • Language: Which language(s) are affected
  • Logs/Screenshots: Any error messages or visual evidence

For Feature Requests

  • Use Case: Why this feature is needed
  • Proposed Solution: How you envision it working
  • Alternatives: Other approaches you've considered
  • Impact: Who benefits and how

For Questions

  • Check Documentation: Review README.md and ARCHITECTURE.md first
  • Search Issues: See if already asked/answered
  • Be Specific: Include context and what you've tried

🤝 Community

  • Be respectful and inclusive
  • Help others in discussions
  • Share your use cases and feedback
  • Star the repo if you find it useful! ⭐

📄 License

By contributing, you agree that your contributions will be licensed under the MIT License.

Thank you for helping make scientific research accessible across Indian languages! 🇮🇳

Questions? Open an issue or reach out to the maintainers.