nitaiaharoni1/vector-storage

Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.

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Established

Vector Storage allows web developers to build search features that understand the meaning and context of text, rather than just keywords. You provide text documents and a search query, and it returns documents semantically similar to your query. This is ideal for developers creating web applications that need smart, contextual search capabilities directly in the user's browser.

244 stars. No commits in the last 6 months. Available on npm.

Use this if you are a web developer building an application that needs to perform intelligent, meaning-based searches on text documents stored directly within the browser.

Not ideal if you need to perform semantic searches across a large, centralized database or if your application isn't primarily browser-based.

web-development semantic-search browser-storage text-analysis client-side-applications
Stale 6m
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 19 / 25

How are scores calculated?

Stars

244

Forks

39

Language

TypeScript

License

MIT

Last pushed

Dec 11, 2024

Commits (30d)

0

Dependencies

2

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/vector-db/nitaiaharoni1/vector-storage"

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