Open-source note-taking and research platform combining AI capabilities with complete privacy control. Features podcast generation, content integration, and customizable workflows.

At a Glance:

Open Notebook is an open-source, privacy-focused alternative to Google's Notebook LM that supports 18+ AI providers, self-hosted deployment, and multi-modal content organization for research workflows.

Overview:

Open Notebook is an open-source research tool that functions as a self-hosted, multi-model alternative to Google's Notebook LM. It allows users to organize multi-modal content including PDFs, videos, audio files, and web pages, then interact with that content through AI-powered chat, intelligent search, and automated note generation. The application supports 18+ AI providers, giving users the flexibility to choose models from OpenAI, Anthropic, Ollama, Google, LM Studio, and others. It also includes professional podcast generation with multi-speaker Episode Profiles and a full REST API for programmatic access. Open Notebook targets users who need private, locally-controlled research environments without cloud dependencies or vendor lock-in.

Key Decision Points:

  • Deployment flexibility: Can be deployed via Docker, cloud, or local environments, with a quick-start option using docker-compose that takes approximately 2 minutes.

  • AI provider choice: Supports 18+ providers including OpenAI, Anthropic, Ollama, and LM Studio, allowing users to switch providers or run models locally with Ollama to avoid API costs.

  • Self-hosted architecture: Research data remains under user control with self-hosted deployment, unlike Google Notebook LM's cloud-only approach.

  • Multi-modal content ingestion: Supports PDFs, videos, audio, web pages, Office docs, and other content types within multiple organized notebooks.

  • API access: Full REST API enables programmatic access and custom integrations, which Google Notebook LM does not offer.

Core Features:

  • Multi-Notebook Organization: Manage multiple research projects in separate notebooks with fine-grained context control over what content AI models can access.

  • Universal Content Support: Ingest and process PDFs, videos, audio files, web pages, Office documents, and other content types.

  • Multi-Model AI Support: Choose from 18+ AI providers for chat, embeddings, speech-to-text, and text-to-speech capabilities, with a provider support matrix for each capability.

  • Professional Podcast Generation: Generate podcasts with 1-4 speakers using custom Episode Profiles and full script control.

  • Intelligent Search: Full-text and vector search across all research content within notebooks.

  • Content Transformations: Apply customizable actions to summarize and extract insights from research materials.

  • REST API: Full programmatic access to all functionality for custom integrations and automation.

  • MCP Integration: Connect with Claude Desktop, VS Code, and other MCP clients for extended AI workflows.

  • Reasoning Model Support: Full support for thinking models like DeepSeek-R1 and Qwen3.

Use Cases:

  • Researchers handling sensitive materials who need a private, self-hosted environment to organize multi-modal content and query it through AI without sending data to external cloud services.

  • Developers and technical users who want flexible AI provider selection, including the ability to run models locally via Ollama to eliminate API costs, or integrate through a full REST API.

  • Content creators who need professional podcast generation with multi-speaker flexibility and script control for transforming research into audio formats.

  • Multi-language users who benefit from a UI supporting English, Portuguese, Chinese, Japanese, Russian, and Bengali.

Open-Source Alternative Value:

Open Notebook provides a self-hosted, source-available option for users seeking an alternative to Google's Notebook LM. The MIT-licensed codebase allows full customization and modification, while the self-hosted architecture keeps research data under user control rather than in Google's cloud. The project's multi-provider support lets users select cost-appropriate AI models or run models locally through Ollama, avoiding dependency on a single AI vendor. A full REST API enables programmatic integration that is unavailable in Google Notebook LM, making Open Notebook extensible for custom research workflows and automation.

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Statistiques du projet

Étoiles

32,227

Forks

3,646

Licence

MIT

Métadonnées

Alternative à
NotebookLM