client-vector-search
The client-vector-search library delivers an efficient solution for embedding and vector searching with caching options, designed for both browser and server-side use. Notably faster than alternatives such as OpenAI's text-embedding-ada-002 and Pinecone, it utilizes transformer models to embed documents and compute cosine similarity between embeddings. Users can manage and cache indexes directly on the client side. Upcoming enhancements include integrating an HNSW index and a comprehensive testing framework, accommodating thousands of vectors for versatile application performance.
