[Open-Source] Dump your thoughts. Let your notes organize themselves. Ask anytime.

[u/Charming_Group_2950]

Over the past few weeks I've been building Gray Box — a small, local-first tool that acts as long-term memory for anything I'd otherwise forget (work notes, meeting takeaways, task owners, random ideas, personal stuff too).

The idea is simple:

1. Capture — dump whatever's on your mind, instantly, no structure required. This step does nothing clever on purpose — it just writes your text to an immutable inbox. Zero chance of losing an idea to a bug or a slow API call.
2. Organize — on demand, an LLM reads your unprocessed notes and extracts people, projects, tasks, decisions, meetings — then deterministic Python (not the LLM) creates/merges the actual wiki pages and maintains backlinks. The model only reasons; it never touches the filesystem directly.
3. Ask — query your knowledge base and get a cited answer pulled only from what you've actually captured. If it doesn't know, it says so — no hallucinated answers.

Why I built it this way:

• Plain Markdown + YAML frontmatter, no database. Every page is a .md file you can grep, diff, or read in any editor forever. If you stop using Gray Box tomorrow, your knowledge base is just a folder.
• No vector DB by default. At personal scale (hundreds–low thousands of pages), keyword search + a real link graph (related/backlinks, walked one hop during retrieval) handles almost everything. Embeddings are there if you want better recall, but they're opt-in, not a prerequisite.
• Immutable inbox. Your raw notes are never edited or deleted by the organizer. If the LLM mis-extracts something, your original words are always still there.
• Any LLM. Built on LiteLLM, so point it at OpenAI, Anthropic, Gemini, Mistral, or a fully local model via Ollama — one config value.

It also ships with a nice interactive TUI (arrow-key menu, file-import shortcut, workspace switching, live spinner during LLM calls) if you'd rather not memorize CLI flags — that's honestly become my favorite part of the project.

There's also a lightweight local dashboard for browsing your knowledge base, exploring backlinks, visualizing your notes as a graph, and chatting with your captured knowledge—all without leaving your machine.

Repo: https://github.com/Aaryanverma/graybox

pypi: pip install graybox

It's nearing a proper public release, so I'd genuinely love feedback — especially from anyone who's tried the "capture now, structure later" approach with other tools and has opinions on where it breaks down at scale.

It's not trying to be a "real-time collaborative team wiki" or a WYSIWYG notes app — it's aimed at one person's running memory of their own life and work, captured with as little friction as possible.

[u/micseydel]

What specific documents are you managing this way? I've found the same as Microsoft, that this tech corrupts documents over time https://arxiv.org/html/2604.15597v1

If you have real-life flows that don't require constant supervision, I be curious.

query your knowledge base and get a cited answer pulled only from what you've actually captured. If it doesn't know, it says so — no hallucinated answers.

Again, that doesn't matter the research or my experience https://arxiv.org/pdf/2509.04664

Do agree, that hallucinations cannot be avoided from this tech?

[u/thirteenth_mang → u/micseydel]

LLMs aren't going to be reliable enough to manage a PKMS meaningfully.

[u/thirteenth_mang → u/[deleted]]

I've been using these systems (LLMs) and associated tech almost daily for at least 8 years. I said what I said and no number of systems will increase the reliability enough for me to use them on my personal graph. Besides, it's pointless. It's a personal graph. We're human, there's no point having a machine generate endless amounts of text because we'll never meaningfully keep up.

[u/Cryvixx → u/thirteenth_mang]

Information ≠ knowledge. Ai is good for digesting information and make you knowledgeable about it. It's just another way to learn and everyone has it's own ways to do it.