Summary
A local memory you can inspect.
It is CRUD and similarity search over a store on your own disk: documents keep the metadata you gave them, results come back with distances rather than as an opaque ranking, and the whole thing is a directory you can copy or delete.
What it is
A document store backed by Chroma's vector database. Documents go in with an id, content and optional metadata; retrieval is semantic similarity with metadata and content filters on top; and the data persists in a local directory between restarts.
What you get
- Documents created with an id, content and key-value metadata
- A document read, updated or deleted by id
- The whole set listed, with limit and offset
- Semantic search returning a ranked list with distance scores
- Search narrowed by metadata fields and by document content
- Storage that persists in a local directory across restarts
Requirements
Python 3.8 or newer and a recent Chroma, installed with uv. Data is written to a directory inside the project, so the store is local and the backups are yours. No account and no key.