notebooklm-py AI工具

Or use Microsoft Edge (for orgs that require Edge for SSO)

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.

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.

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.

Quick Start

<p align="center"> <a href="https://asciinema.org/a/767284" target="_blank"><img src="https://asciinema.org/a/767284.svg" width="600" /></a> <br> <em>16-minute session compressed to 30 seconds</em> </p>

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())