open-notebook

Open Notebook - An Open-Source, Self-Hosted AI Research Notes Platform

Overview of Capabilities

Open Notebook is an open-source, self-hostable AI-driven research and document analysis platform. It can serve as an alternative to Google NotebookLM, supports multimodal content ingestion, intelligent AI Q&A, multi-speaker podcast generation, and more. It also provides a complete REST API and support for 16+ AI providers.

Use Cases

1. Academic Research Organizations & Literature Management

Researchers can use Open Notebook to create digital research workbooks, organizing various formats of content—such as PDF papers, web resources, video lectures, and more—under one unified system. The platform automatically processes the content and performs full-text indexing and vectorization, enabling you to quickly find relevant materials through semantic search. It also uses AI to generate literature summaries and extract methodologies.

2. Automated Research Podcast Generation

Open Notebook can convert your research materials into professional multi-speaker podcasts (supporting 1–4 custom speakers). This is ideal for turning complex research into an audio format that is easy to listen to. Compared with NotebookLM, which supports only 2 speakers, Open Notebook offers more flexible podcast generation options, making knowledge sharing more engaging.

3. Building a Private Enterprise Knowledge Base

For enterprises and teams that require data privacy protection, Open Notebook offers a fully self-hosted deployment solution, with all data stored on your own infrastructure. It supports ingesting content in many formats, including PDF, video, audio, web pages, and Office documents. It also provides AI Q&A with source citations, allowing teams to safely use AI to process sensitive documents.

Core Features

1. Multimodal Content Ingestion & Intelligent Processing

Supports automatic ingestion and processing of 16+ content formats, including PDF documents, video files, audio recordings, web content, Office documents, and more. The system automatically performs text extraction, segmentation, and vectorization to build a searchable knowledge base. The processed content supports full-text search and vector-based semantic search, helping you quickly find relevant information.

2. Context-Aware AI Q&A & Chat

Open Notebook provides intelligent document chat capabilities. The AI will reference specific source materials to answer your questions, ensuring answer traceability. You can create multiple independent notebooks, each containing its own sources, notes, and chat sessions—supporting the management of multiple research projects at the same time.

3. Support for Multiple AI Providers & REST API

Unlike NotebookLM, which supports only Google models, Open Notebook uses the Esperanto library to support 16+ AI providers, including OpenAI, Anthropic, Google, Ollama, Groq, Mistral, and more. It provides a complete REST API, enabling programmatic access and integration into automated workflows—so developers can build custom research tools and content processing pipelines.

FAQ

What is Open Notebook?

Open Notebook is an open-source, self-hostable AI research notes platform that can serve as an alternative to Google NotebookLM. It supports document ingestion, AI Q&A, podcast generation, and more, offering a complete REST API and support for multiple AI providers. All data can be stored on your own infrastructure to ensure data privacy and security.

How do I deploy Open Notebook?

Open Notebook uses Docker Compose for deployment. Download the docker-compose.yml file, set the required OPEN_NOTEBOOK_ENCRYPTION_KEY environment variable, and then run docker-compose up -d to start the service. After startup, you need to configure at least one AI provider’s API key to use the AI features. For free local inference, you can use Ollama.

What are the differences between Open Notebook and NotebookLM?

Key differences include: (1) Open Notebook is open-source and self-hostable to ensure data privacy; (2) it provides a complete REST API for automation-friendly integrations; (3) it supports 16+ AI providers, so you’re not locked into a single model; (4) podcast generation supports 1–4 speakers, which is more flexible than NotebookLM’s 2 speakers; (5) it is based on the MIT license, making it fully extensible and customizable.