Notebooklm

NotebookLM CLI & Python API

Automate Google NotebookLM through the notebooklm-py package (unofficial community client; CLI + async Python API). This file is the workflow and orientation; full command syntax and recipes are in the references.

• references/cli-reference.md — complete CLI commands, flags, advanced features.
• references/python-api.md — full async Python API reference.
• references/setup-guide.md — install, auth, multiple accounts, CI/CD.
• references/troubleshooting.md — detailed troubleshooting.

Note: uses undocumented Google APIs — community project, not affiliated with Google; rate limits apply.

Quick Setup

pip install "notebooklm-py[browser]" && playwright install chromium
notebooklm login          # opens browser for Google login
notebooklm auth check --test   # verify environment

Platform-specific setup, multiple accounts, and CI/CD config: references/setup-guide.md.

Core Workflow

Five steps — one example each; full flags in references/cli-reference.md.

1. Create — notebooklm create "My Research Project".
2. Add sources — notebooklm source add "<url | ./file.pdf | youtube-url>"; source add-drive, source add-research "<query>" for AI source discovery. Accepts PDF/Word/Markdown/text/audio/video/ images/Drive/YouTube/pasted text. Per-plan source limits: Standard 50, Plus 100, Pro 300, Ultra 600. Indexing takes time — notebooklm source wait <id> before asking/generating.
3. Ask — notebooklm ask "What are the key findings?" (add --save-as-note to keep the answer).
4. Generate an artifact (add --wait to block until ready, -s <source_id> to limit to sources):
   • audio (podcast), video / cinematic-video, quiz, flashcards, slide-deck, infographic, mind-map, report, data-table.
   • e.g. notebooklm generate audio "focus on practical implications" --wait.
5. Download — notebooklm download <artifact> <path> (e.g. download audio ./podcast.mp3); options --all, --name "<fuzzy>", -a <artifact_id>, --format <fmt>, --dry-run.

Generation Timeframes

For long operations use --wait, or poll with notebooklm artifact list / artifact poll <task_id>.

Artifact Options

• Audio — --format deep-dive|brief|critique|debate, --length short|default|long, 80+ languages (notebooklm language set pl).
• Video — --format explainer|brief|cinematic (Veo 3), --style auto|classic|whiteboard|kawaii|anime| watercolor|retro-print|heritage|paper-craft.

Python API

For programmatic/CI workflows use the async client (NotebookLMClient.from_storage() → notebooks.create, sources.add_url, chat.ask, artifacts.generate_audio / wait_for_completion / download_audio). Full reference: references/python-api.md.

Troubleshooting

• Auth errors / CSRF — notebooklm auth check --test to diagnose, then notebooklm login to re-auth.
• Rate limiting — wait 5–10 min or use --retry <n> for automatic backoff.
• Generation stuck — use --wait or poll artifact list / artifact poll <task_id>.

More: references/troubleshooting.md.

Key Tips

• Use --wait when you need to download immediately after generating; --json for machine-parseable output.
• For parallel/agent workflows pass explicit notebook IDs with -n instead of relying on context.
• Use profiles (-p work) for multiple Google accounts; -s <source_id> to scope generate/ask.
• source fulltext retrieves indexed content (not in the web UI).
• Slide decks revise per-slide: notebooklm generate revise-slide "prompt" --artifact <id> --slide N.
• Export artifacts to Google Docs/Sheets: notebooklm artifact export <id> --type docs.