kagisearch/vectordb
A lightweight Python library for local embeddings-based text chunking, storage, and vector search retrieval.
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VectorDB provides a minimal, fully local end-to-end solution for text embedding and retrieval. It chunks long text automatically, stores content with associated metadata, and enables semantic search using vector distances. The library is used in production to power AI features in Kagi Search, and supports configurable chunking strategies and embedding modes.
Frequently asked
- What is kagisearch/vectordb?
- A lightweight Python library for local embeddings-based text chunking, storage, and vector search retrieval.
- Is vectordb open source?
- Yes — kagisearch/vectordb is open source, released under the MIT license.
- What language is vectordb written in?
- kagisearch/vectordb is primarily written in Python.
- How popular is vectordb?
- kagisearch/vectordb has 796 stars on GitHub.
- Where can I find vectordb?
- kagisearch/vectordb is on GitHub at https://github.com/kagisearch/vectordb.