Open Notebook: A Privacy‑First, Fully Local AI Note‑Taking Tool vs Google Notebook LM

01 Pain Points of Google Notebook LM

In the AI‑driven knowledge‑management era, users expect more than simple content organization. Google Notebook LM’s cloud‑hosted, closed ecosystem creates three major issues:

🚨 Data exposure: all research materials and private notes are uploaded to Google Cloud, risking leakage of academic results and commercial research.

📛 Model lock‑in: only Google’s proprietary models can be used, preventing low‑cost alternatives or local models.

⛓️ Feature restrictions: supports only two‑person podcasts, limited content conversion, and offers no API, which hampers professional scenarios.

02 Core Comparison

Data Privacy – Open Notebook uses self‑hosted, local deployment for 100% data ownership, while Google Notebook LM stores data only on Google Cloud.

AI Model Choice – Open Notebook integrates 18+ providers (OpenAI, Anthropic, Ollama, LM Studio, etc.), whereas Google Notebook LM is limited to Google’s own models.

Podcast Function – Open Notebook allows 1‑4 custom speakers with configurable personas; Google Notebook LM is fixed to 2 speakers with a rigid format.

Content Processing – Open Notebook offers custom and built‑in conversion for multimodal inputs (PDF, audio, video, web pages); Google Notebook LM provides limited conversion options.

Deployment – Open Notebook runs on Docker, cloud, or locally without platform lock‑in; Google Notebook LM is only Google‑hosted.

Extensibility – Open Notebook is open‑source with a full REST API for secondary development; Google Notebook LM is closed‑source with no API.

Cost Model – Open Notebook charges only for AI usage and can run local models for free; Google Notebook LM offers a free tier plus a monthly subscription.

Citation Feature – Open Notebook provides basic citation support (still improving); Notebook LM currently has more mature source attribution.

03 Core Highlights

Privacy First – All data stays on the user’s device or server; no upload to third‑party servers, eliminating leakage risk.

18+ AI Service Providers – Powered by the Esperanto library, it supports major LLMs, embeddings, speech‑to‑text, and text‑to‑speech from providers such as OpenAI/Azure, Anthropic, Ollama (local), Google GenAI, ElevenLabs, and compatible solutions like LM Studio/OpenRouter.

All‑Scenario Content Management – Handles PDF, video, audio, web links, and Office documents; combines full‑text and vector search for instant retrieval; enables real‑time AI‑driven dialogue over notes.

Professional Podcast Generation – Supports 1‑4 custom speakers with personalized voice and persona settings; generates complete podcast scripts and exports audio, surpassing Notebook LM’s 2‑person fixed format.

Open‑Source Customizability – Built with Python, Next.js, React, and SurrealDB; source code allows UI tweaks, adding new AI providers, or integrating with internal systems; a complete REST API enables automation and enterprise integration.

04 Practical Deployment

Prerequisite – Install Docker Desktop (Windows/Mac/Linux); no complex environment setup required.

Step 1: Obtain docker‑compose.yml

Recommended method (one‑click):

curl -o docker-compose.yml https://raw.githubusercontent.com/lfnovo/open-notebook/main/docker-compose.yml

Alternative method (manual): create a file named docker-compose.yml and paste the following content:

services:
  surrealdb:
    image: surrealdb/surrealdb:v2
    command: start --log info --user root --pass root rocksdb:/mydata/mydatabase.db
    user: root
    ports:
      - "8000:8000"
    volumes:
      - ./surreal_data:/mydata
    restart: always
  open_notebook:
    image: lfnovo/open_notebook:v1-latest
    ports:
      - "8502:8502"
      - "5055:5055"
    environment:
      - OPEN_NOTEBOOK_ENCRYPTION_KEY=change-me-to-a-secret-string # must modify
      - SURREAL_URL=ws://surrealdb:8000/rpc
      - SURREAL_USER=root
      - SURREAL_PASSWORD=root
      - SURREAL_NAMESPACE=open_notebook
      - SURREAL_DATABASE=open_notebook
    volumes:
      - ./notebook_data:/app/data
    depends_on:
      - surrealdb
    restart: always

Step 2: Change the encryption key – Replace OPEN_NOTEBOOK_ENCRYPTION_KEY=change-me-to-a-secret-string with a custom secret (e.g., my-notebook-secret-8888) to avoid default‑key security risks.

Step 3: Start the services docker compose up -d Wait 15‑20 seconds, then open http://localhost:8502 in a browser.

Step 4: Configure AI service providers

Go to Settings → API Keys.

Click “Add Credential”, select a provider (OpenAI, Groq, Google, etc.).

Paste the API key, save, then “Test Connection” → “Discover Models” → “Register Models”.

(Optional) For free local models, follow the official examples/docker-compose-ollama.yml to set up Ollama and use it without API costs.

Free API key sources: OpenAI, Anthropic, Groq (free tier).

Common Pitfalls and Fixes

Port 8502 unresponsive – Ensure Docker is running and the surrealdb container starts first (depends_on handles ordering).

API key validation fails – Verify the key is not expired and that “Discover Models” completed successfully.

Data persistence failure – Check volume mount permissions; on Linux/Mac ensure the current user has read/write access.

05 Core Feature Demonstrations

Multimodal Content Management – Upload PDFs, audio, video, or web links; the system parses and indexes content, supporting both full‑text and vector search for rapid information location.

Contextual Dialogue – Chat with the AI using uploaded content as context; supports multi‑turn conversations suitable for research or commercial analysis.

Podcast Generation – In the Podcast module, configure 1‑4 speakers, script style, and topic; the system generates a complete script and exports audio, meeting commercial‑grade podcast needs.

Content Conversion – Define custom conversion rules to summarize notes, extract keywords, or generate abstracts for various downstream scenarios.

06 Summary and Selection Guidance

Key Takeaways

Privacy: 100% data control, no cloud leakage.

Cost: Pay‑as‑you‑go AI usage; local models are free.

Features: Multimodal management, professional podcasting, API integration for personal or enterprise use.

Freedom: Open‑source, fully customizable, no platform lock‑in.

Recommendation Matrix

Ordinary personal users (no privacy needs) – Google Notebook LM free tier (zero‑config, ready‑to‑use).

Researchers / students (privacy + low cost) – Open Notebook with Ollama local models (free, data stays private).

Entrepreneurs / enterprise users (professional scenarios) – Open Notebook with multiple AI providers (full feature set, customizable, API‑ready).

Developers (secondary development) – Deploy Open Notebook from source (open‑source, extensible, integrates with own systems).

07 Further Reading

Additional articles on AI tooling, open‑source projects, and advanced AI workflows are linked in the original source.