I built Stash, a self-hosted bookmark manager that uses AI to automatically process your links.
Paste a URL and it fetches the content, parses it, summarizes it, auto-assigns categories and tags, and generates a vector embedding for search.
Search is hybrid — it combines pgvector cosine similarity (semantic) with PostgreSQL tsvector (keyword) and merges both with Reciprocal Rank Fusion. You can search in natural language ("articles about distributed systems tradeoffs") or with simple keywords.
It's single-tenant by design: one password, no user accounts, no tracking. Your data stays on your machine.
The project is MIT licensed don't hesitate to contribute. Some areas where help would be great: browser extension, bookmark import/export
Paste a URL and it fetches the content, parses it, summarizes it, auto-assigns categories and tags, and generates a vector embedding for search.
Search is hybrid — it combines pgvector cosine similarity (semantic) with PostgreSQL tsvector (keyword) and merges both with Reciprocal Rank Fusion. You can search in natural language ("articles about distributed systems tradeoffs") or with simple keywords.
It's single-tenant by design: one password, no user accounts, no tracking. Your data stays on your machine.
The project is MIT licensed don't hesitate to contribute. Some areas where help would be great: browser extension, bookmark import/export
GitHub: https://github.com/ayoub9360/stash
Happy to answer questions about the architecture or the hybrid search approach.