teng-lin/notebooklm-py

Source: https://github.com/teng-lin/notebooklm-py

notebooklm-py

A Comprehensive NotebookLM Skill & Unofficial Python API. Full programmatic access to NotebookLM’s features—including capabilities the web UI doesn’t expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.

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, Codex, and other LLM agents. Ships with a root NotebookLM skill for GitHub and npx skills add discovery, local notebooklm skill install support for Claude Code and .agents skill directories, and repo-level Codex guidance in AGENTS.md.

📚 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

Features

Complete NotebookLM Coverage

Content Generation (All Artifact Types)

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
• Slide deck as PPTX - Download editable PowerPoint files (web UI only offers PDF)
• Slide revision - Modify individual slides with natural-language prompts
• Report template customization - Append extra instructions to built-in format templates
• Save chat to notes - Save Q&A answers or conversation history as notebook notes
• Source fulltext access - Retrieve the indexed text content of any source
• Programmatic sharing - Manage permissions without the UI
• Multi-account profiles - Switch between Google accounts without re-authenticating
• Browser cookie import - Reuse cookies from your existing browser session instead of driving Playwright

Installation

The full install guide — six personas (agent, end-user, library, headless, contributor, power-user), optional extras matrix, platform notes — lives in docs/installation.md.

Quickest start (CLI users and AI agents):

pip install "notebooklm-py[browser]"   # core + Playwright
playwright install chromium             # ~170 MB; no progress bar — be patient (30–90 s)
notebooklm login                        # opens browser for Google sign-in
notebooklm auth check --test --json     # verify: expect "status": "ok"

As a library (embedded in your app — no Playwright, no Chromium):

pip install notebooklm-py               # ~10 MB; ship a pre-acquired storage_state.json

If playwright install chromium fails on Linux with TypeError: onExit is not a function, see the Linux workaround. Contributors: see CONTRIBUTING.md.

Quick Start

16-minute session compressed to 30 seconds

CLI

# 1. Authenticate (opens browser)
notebooklm login
# Or use Microsoft Edge (for orgs that require Edge for SSO)
# notebooklm login --browser msedge
# Or reuse cookies from an already-logged-in browser session
# notebooklm login --browser-cookies chrome
# notebooklm login --browser-cookies 'chrome::Profile 1'  # one Chromium profile
# (combine with --profile to populate a specific profile;
#  use --account / --all-accounts after auth inspect when several
#  Google accounts are signed in)

# 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?"
notebooklm ask --prompt-file ./long_question.txt  # Read question from file

# 4. Generate content (use --prompt-file for long prompts)
notebooklm generate audio "make it engaging" --wait
notebooklm generate video --style whiteboard --wait
notebooklm generate cinematic-video "documentary-style summary" --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 cinematic-video ./documentary.mp4
notebooklm download quiz --format markdown ./quiz.md
notebooklm download flashcards --format json ./cards.json
notebooklm download slide-deck ./slides.pdf
notebooklm download infographic ./infographic.png
notebooklm download mind-map ./mindmap.json
notebooklm download data-table ./data.csv

Other useful CLI commands:

notebooklm auth check --test         # Diagnose auth/cookie issues
notebooklm auth refresh --quiet      # One-shot cookie keepalive (for cron / launchd / systemd)
notebooklm auth refresh --browser-cookies chrome  # Re-extract and repair account routing
notebooklm auth inspect --browser 'chrome::Profile 1'  # Preview one Chromium profile
notebooklm agent show codex          # Print bundled Codex instructions
notebooklm agent show claude         # Print bundled Claude Code skill template
notebooklm language list             # List supported output languages
notebooklm metadata --json           # Export notebook metadata and sources
notebooklm share status              # Inspect sharing state
notebooklm source add-research "AI"  # Start web research and import sources
notebooklm skill status              # Check local agent skill installation
notebooklm profile list              # List all Google account profiles
notebooklm profile switch work       # Switch active account profile

Use --prompt-file PATH with ask, prompt-based generate commands, and source add-research when the text is too long for the shell command line. This reads prompt/query text from a file and is separate from source add ./file.pdf, which still uploads that file as a NotebookLM source.

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 Setup

Option 1 — CLI install:

notebooklm skill install

Installs the skill into ~/.claude/skills/notebooklm and ~/.agents/skills/notebooklm.

Option 2 — npx install (via the open skills ecosystem):

npx skills add teng-lin/notebooklm-py

Fetches the canonical SKILL.md directly from GitHub.

Documentation

• CLI Reference - Complete command documentation
• Python API - Full API reference
• Configuration - Storage and settings
• Release Guide - Release checklist and packaging verification
• 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

Star History

License

MIT License. See LICENSE for details.