💡 Summary
A Python API for Google NotebookLM that enables advanced research automation and content generation.
🎯 Target Audience
🤖 AI Roast: “Powerful, but the setup might scare off the impatient.”
Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); dependency pinning and supply-chain risk. Run with least privilege and audit before enabling in production.
notebooklm-py
Comprehensive Python API for Google NotebookLM. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—from Python or the command line.
Source & Development: https://github.com/teng-lin/notebooklm-py
⚠️ Unofficial Library - Use at Your Own Risk
This library uses undocumented Google APIs that can change without notice.
- Not affiliated with Google - This is a community project
- APIs may break - Google can change internal endpoints anytime
- Rate limits apply - Heavy usage may be throttled
Best for prototypes, research, and personal projects. See Troubleshooting for debugging tips.
What You Can Build
🤖 AI Agent Tools - Integrate NotebookLM into Claude Code or other LLM agents. Ships with Claude Code skills for natural language automation (notebooklm skill install), or build your own integrations with the async Python API.
📚 Research Automation - Bulk-import sources (URLs, PDFs, YouTube, Google Drive), run web/Drive research queries with auto-import, and extract insights programmatically. Build repeatable research pipelines.
🎙️ Content Generation - Generate Audio Overviews (podcasts), videos, slide decks, quizzes, flashcards, infographics, data tables, mind maps, and study guides. Full control over formats, styles, and output.
📥 Downloads & Export - Download all generated artifacts locally (MP3, MP4, PDF, PNG, CSV, JSON, Markdown). Export to Google Docs/Sheets. Features the web UI doesn't offer: batch downloads, quiz/flashcard export in multiple formats, mind map JSON extraction.
Three Ways to Use
| Method | Best For | |--------|----------| | Python API | Application integration, async workflows, custom pipelines | | CLI | Shell scripts, quick tasks, CI/CD automation | | Agent Skills | Claude Code, LLM agents, natural language automation |
Features
Complete NotebookLM Coverage
| Category | Capabilities | |----------|--------------| | Notebooks | Create, list, rename, delete | | Sources | URLs, YouTube, files (PDF, text, Markdown, Word, audio, video, images), Google Drive, pasted text; refresh, get guide/fulltext | | Chat | Questions, conversation history, custom personas | | Research | Web and Drive research agents (fast/deep modes) with auto-import | | Sharing | Public/private links, user permissions (viewer/editor), view level control |
Content Generation (All NotebookLM Studio Types)
| Type | Options | Download Format | |------|---------|-----------------| | Audio Overview | 4 formats (deep-dive, brief, critique, debate), 3 lengths, 50+ languages | MP3/MP4 | | Video Overview | 2 formats, 9 visual styles (classic, whiteboard, kawaii, anime, etc.) | MP4 | | Slide Deck | Detailed or presenter format, adjustable length | PDF | | Infographic | 3 orientations, 3 detail levels | PNG | | Quiz | Configurable quantity and difficulty | JSON, Markdown, HTML | | Flashcards | Configurable quantity and difficulty | JSON, Markdown, HTML | | Report | Briefing doc, study guide, blog post, or custom prompt | Markdown | | Data Table | Custom structure via natural language | CSV | | Mind Map | Interactive hierarchical visualization | JSON |
Beyond the Web UI
These features are available via API/CLI but not exposed in NotebookLM's web interface:
- Batch downloads - Download all artifacts of a type at once
- Quiz/Flashcard export - Get structured JSON, Markdown, or HTML (web UI only shows interactive view)
- Mind map data extraction - Export hierarchical JSON for visualization tools
- Data table CSV export - Download structured tables as spreadsheets
- Source fulltext access - Retrieve the indexed text content of any source
- Programmatic sharing - Manage permissions without the UI
Installation
# Basic installation pip install notebooklm-py # With browser login support (required for first-time setup) pip install "notebooklm-py[browser]" playwright install chromium
Development Installation
For contributors or testing unreleased features:
pip install git+https://github.com/teng-lin/notebooklm-py@main
⚠️ The main branch may contain unstable changes. Use PyPI releases for production.
Quick Start
CLI
# 1. Authenticate (opens browser) notebooklm login # 2. Create a notebook and add sources notebooklm create "My Research" notebooklm use <notebook_id> notebooklm source add "https://en.wikipedia.org/wiki/Artificial_intelligence" notebooklm source add "./paper.pdf" # 3. Chat with your sources notebooklm ask "What are the key themes?" # 4. Generate content notebooklm generate audio "make it engaging" --wait notebooklm generate video --style whiteboard --wait notebooklm generate quiz --difficulty hard notebooklm generate flashcards --quantity more notebooklm generate slide-deck notebooklm generate infographic --orientation portrait notebooklm generate mind-map notebooklm generate data-table "compare key concepts" # 5. Download artifacts notebooklm download audio ./podcast.mp3 notebooklm download video ./overview.mp4 notebooklm download quiz --format markdown ./quiz.md notebooklm download flashcards --format json ./cards.json notebooklm download slide-deck ./slides.pdf notebooklm download mind-map ./mindmap.json notebooklm download data-table ./data.csv
Python API
import asyncio from notebooklm import NotebookLMClient async def main(): async with await NotebookLMClient.from_storage() as client: # Create notebook and add sources nb = await client.notebooks.create("Research") await client.sources.add_url(nb.id, "https://example.com", wait=True) # Chat with your sources result = await client.chat.ask(nb.id, "Summarize this") print(result.answer) # Generate content (podcast, video, quiz, etc.) status = await client.artifacts.generate_audio(nb.id, instructions="make it fun") await client.artifacts.wait_for_completion(nb.id, status.task_id) await client.artifacts.download_audio(nb.id, "podcast.mp3") # Generate quiz and download as JSON status = await client.artifacts.generate_quiz(nb.id) await client.artifacts.wait_for_completion(nb.id, status.task_id) await client.artifacts.download_quiz(nb.id, "quiz.json", output_format="json") # Generate mind map and export result = await client.artifacts.generate_mind_map(nb.id) await client.artifacts.download_mind_map(nb.id, "mindmap.json") asyncio.run(main())
Agent Skills (Claude Code)
# Install via CLI or ask Claude Code to do it notebooklm skill install # Then use natural language: # "Create a podcast about quantum computing" # "Download the quiz as markdown" # "/notebooklm generate video"
Documentation
- CLI Reference - Complete command documentation
- Python API - Full API reference
- Configuration - Storage and settings
- Troubleshooting - Common issues and solutions
- API Stability - Versioning policy and stability guarantees
For Contributors
- Development Guide - Architecture, testing, and releasing
- RPC Development - Protocol capture and debugging
- RPC Reference - Payload structures
- Changelog - Version history and release notes
- Security - Security policy and credential handling
Platform Support
| Platform | Status | Notes | |----------|--------|-------| | macOS | ✅ Tested | Primary development platform | | Linux | ✅ Tested | Fully supported | | Windows | ✅ Tested | Tested in CI |
License
MIT License. See LICENSE for details.
Pros
- Comprehensive access to NotebookLM features
- Supports various content generation formats
- Flexible usage via API, CLI, and agent skills
Cons
- Unofficial library with potential API instability
- Rate limits may affect heavy usage
- Requires browser login for initial setup
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Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author teng-lin.
