lestan/web-vector-storage
Web Vector Storage (WVS) is a lightweight and efficient vector database that stores document vectors in the browser's IndexedDB. It supports perform semantic similarity searches on text documents using vector embeddings. Embedding is enabled through use of OpenAI, Ollama or HuggingFace Transformer embedding models.
This tool helps web application developers build semantic search capabilities directly into their browser-based applications. It takes text documents and their associated metadata, converts them into numerical 'vectors' using various AI models, and stores them in the user's browser. When a user queries, it finds the most semantically similar documents, allowing for more intuitive and context-aware search results within web apps.
No commits in the last 6 months.
Use this if you are a web developer building a client-side application that needs to perform fast, intelligent searches on text documents without relying on a backend server for vector storage.
Not ideal if your application requires server-side data processing, complex query logic beyond semantic similarity, or if you need to manage a very large dataset that exceeds typical browser storage limits.
Stars
13
Forks
2
Language
TypeScript
License
MIT
Category
Last pushed
Mar 18, 2024
Commits (30d)
0
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