Back to directory

vlite

A simple vector database implemented in plain numpy, with no server or configuration to set up, that stores embeddings in a single portable context file.

vlite

vlite is a vector database that needs no separate server or setup: installing the package and importing it is enough to start indexing and searching text. It bakes in a small embedding model, embed-xsmall, and runs entirely in numpy, its only dependency, chunking long text into the model's token window automatically and supporting metadata filtering on stored entries.

Data is stored in a CTX file, a portable format meant to be carried between machines similarly to a browser cookie; saving writes the whole index to one file, and reopening the same name loads it back. It was built to support embeddings used by ChatGPT plugins running for a large number of users.

It is written in Python and released under the MIT license.

More in Databases

See all 294
  • SQLBraid

    clickin.github.io

    A SQL-first data-access toolkit for TypeScript that keeps ordinary SQL visible in tagged template literals, binds interpolated values safely by default, supports readable conditional SQL directives, and lets a schema validate the returned rows.

  • A SQL-style query language and toolchain for the Qdrant vector database, covering dense, sparse and hybrid search, filtering and multitenancy, with the same grammar running from a CLI, Python, Node.js, Rust, WebAssembly and an in-process edge engine.

  • Fast Knowledge

    github.com

    A self-hosted, Java-based knowledge base for small and mid-sized organizations, turning internal documents into a searchable, question-answerable and audit-exportable knowledge asset with hybrid retrieval and Docker deployment.