reor

Some here comment on notes they've taken for their entire life, often using powerful note-taking systems. Of course, there's a ton of note-taking systems out there. Org-Mode [1], Obsidian [2], plain .txt, ... And it's become quite simple to integrate such systems with LLMs. Whether to add that data to the LLM [3], using LLM formatting, or to visualize and use it as a personal partner. For the latter - there's also a ton of open-source UIs such as Chatbot-ui[4] and Reor[5]. And that's just the tip of the iceberg. Personally, I haven't been consistent enough through the years in note-taking. So, I'm really curious to learn more about those of you who were and implemented such pipelines. I'm sure there's a ton of cool interaction experiences. [1] https://orgmode.org/ [2] https://obsidian.md/ [3] https://ollama.com/ [4] https://github.com/mck

Seems promising, but I couldn't get it to work at all. Seems like I'm not the only one having issues: https://github.com/reorproject/reor/issues

Thanks for your feedback! - Multiple vaults is in fact in a PR right now: https://github.com/reorproject/reor/pull/28 - Manual linking is coming. - Minimizing the UI to chat is interesting. Right now I guess you can drag chat to cover anything - but yes perhaps a toggle between two modes could be interesting. - Read other formats also something in the pipeline. Just need to sort out the editor itself to support something like this. Perhaps pdfs would just be embedded into the vector db but not accessible to the editor. - Integrating with browser history and bookmarks is a big feature. Things like web clipping and bringing in context from different places are interesting...

Reor is an open-source AI note-taking app that runs models locally. The four main things to know are: 1. Notes are connected automatically with vector search. You can do semantic search + related notes are automatically connected. 2. You can do RAG Q&A on your notes using the local LLM of your choice. 3. Embedding model, LLM, vector db and files are all run or stored locally. 4. Point it to a directory of markdown files (like an Obsidian vault) and it works seamlessly alongside Obsidian. Under the hood, Reor uses Llama.cpp (node-llama-cpp integration), Transformers.js and Lancedb to power the local AI features. Reor was built right from the start to support local models. The future of knowledge management involves using lots of AI to organize pieces of knowledge - but crucially, that AI should run as much as possible privately & locally.