Corporate researchers and students are hitting hard data ceilings inside Google’s AI ecosystem. NotebookLM currently restricts users to its proprietary Gemini models and enforces daily usage limits on document analysis. A new open-source alternative called Open Notebook removes these restrictions entirely by giving users a fully local knowledge base.
Developed under an MIT license by GitHub user lfnovo, the software functions completely offline. Users upload PDFs, raw text files, web articles, and YouTube URLs into the application. The system extracts the transcripts and lets the user query their own private database without sending information back to Big Tech servers.
Version 1.9.0 launched last week in early June 2026. The update adds new audio generation capabilities, including support for the Esperanto 2.22 provider. The software breaks its core functionality into two specific modes. The “Chat” interface handles ongoing conversational research, while the “Ask” mode answers rapid, single-question data lookups.
Getting the system running requires a bit of technical setup. The installation relies on specific Docker deployment prerequisites. Users spin up local containers for the main Open Notebook application, a SurrealDB database instance, and Ollama to run the models locally.
The chat interface is highly responsive, but the initial setup demands decent computer hardware. The most hardware-intensive phase of the workflow is processing the initial document uploads. Open Notebook runs the text through the `nomic-embed-text` model to generate searchable vector embeddings. This background process requires a minimum of 4GB of RAM to function correctly.
Many developers are switching to this open-source software specifically for the privacy benefits. Keeping document analysis entirely offline via local APIs ensures that sensitive corporate or academic data remains strictly under user control. The GitHub repository currently tracks 112 open issues and 22 pull requests as the developer community tests the platform.
How Open Notebook Breaks Vendor Lock-In
Google keeps NotebookLM tied to the Gemini infrastructure and hides the underlying AI instructions from the user. Open Notebook explicitly targets this lack of control. The self-hosted platform includes fully editable “Transformations,” allowing users to rewrite the exact prompts the AI uses to summarize and analyze their uploaded data.
The software also opens up the model selection. Users can connect to 16 different AI providers. They can route their queries through OpenAI, Anthropic, Mistral, xAI, OpenRouter, or completely local models via Ollama. It competes directly alongside other local retrieval-augmented generation tools like AnythingLLM and StackAI.
Open Notebook also builds its own version of Google’s most popular consumer feature. The tool includes an advanced podcast generator that creates multi-speaker audio summaries of the uploaded documents. Users can customize the voice profiles directly, building a fully private alternative to NotebookLM’s viral Audio Overviews.