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.
Not yet testedsource: GitHubhomepageTypeScriptMITcommit 0484d9c25765
TypeScript, MIT licensed. The project labels itself: cosine similarity, embedding vectors, javascript, local storage, localstorage, lru cache, npm and open source.
vector-storage has not been verified yet.
Measured by Argusic on a fresh machine every time. Every number links to its evidence.
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
No recorded runs.
Topics (from GitHub)
cosine-similarityembedding-vectorsjavascriptlocal-storagelocalstoragelru-cachenpmopen-sourceopenaisemantic-searchsemantic-similaritytypescriptvector-databasevector-dbvector-searchvector-similarityvector-similarity-databasevector-similarity-search
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/vector-storage)Questions
- Does vector-storage run?
- vector-storage has not been fully verified yet. No recorded run has produced a verdict yet.
- How did Argusic test vector-storage?
- On a fresh, disposable machine, with every command recorded. 0 attempts are recorded, and the full method is on the methodology page.
- Where is the evidence for vector-storage?
- All 0 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.