clientvectorsearch.com
🚀 Discover 'clientvectorsearch.com'! 🔍 Embed, store, and search vectors effortlessly with just 5 lines of code. 🌟 Outperforming OpenAI's text-embedding-ada-002, it offers lightning-fast searches through up to 100K vectors in under 100ms! 💡 #AITool #VectorSearch #SemanticSearch
- Install `client-vector-search` on npm to embed, store, and search vectors on the client side effortlessly.
- Achieve semantic search functionality with just 5 lines of code.
- Benefit from computation that outperforms OpenAI's text-embedding-ada-002 on the client side.
- Search through up to 100K vectors in under 100ms for minimal latency.
- Scale efficiently using the embedding API with a cost of only $20 per month to handle 10M vectors.
- Get early access to the API for updates and enhanced features.
- Utilize `getEmbedding` and `EmbeddingIndex` after installing `client-vector-search`.
- Create an index with `new EmbeddingIndex(initialObjects)` to manage up to 100k embeddings.
- Compute the embedding for a query using `getEmbedding` for effective searching.
- Efficiently search the index with specified parameters using `index.search`.
- Test the computation speed by inputting lengthy text or using a Wikipedia dataset for search evaluation.
- Access the dataset used for search and generate embeddings from the provided resources.