Open Notebook: research your own documents without uploading them
The open source alternative to NotebookLM. You load your sources, ask questions about them, and the answers cite where they came from, all inside your server.
Short answer
Open Notebook is an open source alternative to NotebookLM that you install on your VPS. You load documents, transcripts or links, and the assistant answers by citing those sources instead of improvising from memory. The documents stay on your server; only the relevant fragment travels to the model you choose. It is the right option when the material is confidential.
- Last verified
- April 30, 2026
Antes de empezar necesitas
- A VPS with Docker and 4 GB of RAM
- An API key from a model provider
The problem with asking a general assistant about your own material is that it does not know it. You can paste it into every conversation, but that does not scale beyond a handful of documents.
Open Notebook solves that: you load the sources once and every question is answered from them, with a citation showing where each statement came from.
What it is actually good for
Studying from your own material. Reviewing contracts and finding the specific clause. Preparing an article from twenty sources. Searching inside meeting transcripts without listening to them again.
In all those cases, what matters is not that the model is brilliant: it is that it does not make things up. By forcing it to answer from loaded sources and cite them, the room for invention shrinks a lot.
1. Install with Docker Compose
mkdir -p /opt/open-notebook && cd /opt/open-notebook
curl -fsSL https://raw.githubusercontent.com/lfnovo/open-notebook/main/docker-compose.yml -o docker-compose.yml
Adjust the file's variables with your provider's API key and bring it up:
docker compose up -d
2. Create your first notebook
A notebook groups sources on one topic. The discipline that pays off most is not mixing them: one notebook per project, with only that project's sources. When you throw everything in, the answers get vague.
3. Load the sources and ask
Upload the documents and wait for processing to finish. Then ask in plain language. Always check the citations: if a statement does not come with one, treat it as the model's opinion, not as a fact from your material.
Common mistakes
Loading a hundred documents at once. Processing consumes memory and the server runs out of it. Upload in batches.
Trusting without checking the citations. The model can paraphrase badly. The citation exists precisely so you can verify it.
Frequently asked questions
Do my documents leave the server?
The complete files stay on your server. When you ask a question, only the relevant fragments are sent to the model. If you need nothing to leave at all, you can connect it to a local model, at the cost of quality and speed.
How does it compare to NotebookLM?
NotebookLM is more polished and has features like audio summaries. Open Notebook wins on control: you choose the model, you decide where the data lives and you do not depend on Google keeping the product alive.
What formats does it accept?
PDF, text, Markdown and web links, plus transcripts. Scanned PDFs with no text layer need OCR first.
Is it usable by a team?
Yes, but put authentication in front of it and control what the API key spends, same as with any tool connected to a paid model.
