SimplerVectors is a straightforward, beginner-friendly vector database project designed for efficiently handling and querying large-scale high-dimensional data vectors. This project is especially suited for applications like language models in retrieval-augmented generation (RAG) projects. Currently in its early stages, SimplerVectors aims to achieve high performance and scalability, making it ideal for managing very large datasets.

• Efficient Storage: Leverages NumPy's memory-mapped files to manage large datasets efficiently.
• Simple Design: The system is designed to be easy to understand and use, even for developers new to vector databases.
• Vector Normalization and Search: Supports automatic vector normalization and cosine similarity searches to find the top similar vectors.
• Scalability in Development: Focuses on enhancements for handling growing data volumes and increasing query demands as development progresses.

Stay Tuned... something big is coming soon !