Welcome to the Hyper Hybrid Search Engine, a next-generation search engine project designed to leverage the power of hybrid models and advanced embedding techniques to deliver superior search capabilities.
The Hyper Hybrid Search Engine is a cutting-edge project that aims to revolutionize how we think about search technologies. By integrating a powerful embedding inference backend with a robust set of tools and interfaces, this project is designed to offer unparalleled search accuracy and efficiency.
- Embedding Inference Backend: Utilizes advanced machine learning models to understand and interpret search queries at a deeper level.
- Server Interface: Provides a seamless and scalable API interface for handling search requests and responses.
- Utility/Source Module: A dedicated module (
utilsorsrc) for common utilities and source codes that support the core functionalities of the search engine. - Benchmarking: Tools and protocols to measure the performance of the search engine under various conditions and workloads.
- Application: End-user applications showcasing the capabilities and use cases of the search engine.
- Database: A robust database system designed to store, manage, and retrieve vast amounts of data efficiently.
- Python 3.8 or higher
- Docker (for containerized deployment)
- Any modern web browser for accessing the application interface
- Clone the repository:
git clone https://github.com/yourorganization/hyper-hybrid-search-engine.git - Install the required dependencies:
pip install -r requirements.txt - Setup the database (see the database configuration section).
- Start the server:
python server/start_server.py
After installation, you can quickly test the search engine by sending a search query to the server's REST API:
curl -X POST http://localhost:8000/search -d '{"query": "your search query"}'
For more detailed information about the project, including architecture diagrams, API documentation, and developer guides, please refer to the /docs directory.
We welcome contributions to the Hyper Hybrid Search Engine project! Please read our CONTRIBUTING.md file for guidelines on how to make a contribution.
This project is licensed under the MIT License - see the LICENSE file for details.
- Thank you to all the contributors who have helped to build this project.
- Special thanks to [Name or Organization] for providing datasets/resources.
This template is designed to be both informative and easy to navigate, providing essential information to get started with the project quickly while also outlining how to contribute and acknowledging contributions. Feel free to customize the README to better fit the specific needs and branding of your project.