This repository contains a book recommendation system built using modern technologies, integrating natural language processing and vector search for an enhanced user experience.
- Personalized Book Recommendations using JINA AI.
- Voice Interaction with speech-to-text and text-to-speech capabilities.
- Fast and Scalable Search powered by MilvusDB.
- Modern Frontend using React for a seamless user experience.
- Efficient API with FastAPI for high-performance backend operations.
- React - Frontend framework for a dynamic UI.
- MilvusDB - Vector database for efficient book search and recommendations.
- FastAPI - High-performance backend framework in Python.
- Speech-to-Text - Convert voice commands into text.
- Text-to-Speech - Generate audio responses for recommendations.
- User Interaction - Users can input text or use voice commands.
- Processing - The system converts voice to text and retrieves relevant book recommendations.
- Recommendation Engine - MilvusDB stores and searches for book vectors.
- Response - The system provides results as text and optionally reads them aloud.
We welcome contributions! You can report bugs, suggest new features, or submit improvements.
This project is available under the MIT License.
This book recommendation system leverages state-of-the-art technologies to deliver personalized suggestions and an interactive user experience.