A production-ready RAG (Retrieval-Augmented Generation) system designed for robotics research and education, indexing 1000+ research papers and course materials from top universities.
- Semantic Search: Advanced semantic search capabilities with citation tracking across multiple knowledge domains
- High Performance: Optimized FastAPI backend with vector database achieving <200ms query response time
- Multi-Document Retrieval: Efficient retrieval and synthesis of information from multiple sources
- Authentication & Analytics: Secure access with usage analytics and user management
- Production Ready: Deployed system serving 50+ daily active users in the UCSC robotics program
- Index Size: 1000+ robotics research papers and course materials
- Query Response Time: <200ms for multi-document retrieval
- Active Users: 50+ daily active users
- Target Audience: UCSC robotics program students and researchers
- Backend: FastAPI with optimized vector database
- Search Engine: Semantic search with citation tracking
- Database: Vector database for efficient similarity search
- Authentication: Secure user authentication system
- Analytics: Usage tracking and analytics dashboard
- Research: Query complex robotics topics across multiple knowledge domains
- Education: Access to comprehensive robotics course materials
- Citation Tracking: Follow research citations and references
- Multi-Domain Search: Search across different robotics specializations
- Python 3.8+
- FastAPI
- Vector database (e.g., Chroma, Pinecone, or Weaviate)
- Authentication system
# Clone the repository
git clone <repository-url>
cd RoboRag
# Install dependencies
pip install -r requirements.txt
# Set up environment variables
cp .env.example .env
# Edit .env with your configuration
# Run the application
uvicorn main:app --reload- Robotics research papers from top universities
- Course materials and lecture notes
- Technical documentation and tutorials
- Industry reports and whitepapers
The system supports various configuration options for:
- Vector database connection
- Authentication providers
- Search parameters
- Analytics settings
Track usage patterns and system performance:
- Query frequency and types
- User engagement metrics
- System performance monitoring
- Search result effectiveness
We welcome contributions to improve the RoboRag system:
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
This project is licensed under the MIT License - see the LICENSE file for details.
- UCSC Robotics Program for providing access to research materials
- Contributors and researchers who have made this system possible
- Open source community for the tools and libraries used
For questions, suggestions, or collaboration opportunities, please reach out through the project's issue tracker or contact the development team.
Built with ❤️ for the robotics research and education community