Notebooklm Py.Bak

Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成（播客、视频、幻灯片、测验、思维导图等）、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。

Security Scan

The skill's files and runtime instructions are consistent with an unofficial NotebookLM Python CLI wrapper: it installs/uses notebooklm-py, requires a browser login, and runs the CLI to upload/download artifacts — nothing in the bundle indicates hidden exfiltration or unrelated privilege requests, but the source is unknown and the library uses browser-based auth and local storage so exercise caution with sensitive data.

Purpose & Capability

Name/description advertise an unofficial NotebookLM Python API and the files/instructions consistently install and call the notebooklm-py CLI and Python client. The included helper scripts simply orchestrate notebooklm CLI commands (create, source add, generate, download), which is coherent with the stated capabilities.

Instruction Scope

SKILL.md instructs installing notebooklm-py, running notebooklm login (browser-based) and adding local files or URLs as sources. That is expected for a notebook/content ingestion tool, but it does explicitly direct uploading of local files (PDFs, audio, video, etc.) to the service — users should be aware this will transmit file contents to NotebookLM/Google endpoints and may store credentials locally.

Install Mechanism

There is no registry install spec; SKILL.md advises pip installing notebooklm-py and playwright and running 'playwright install chromium'. Installing from PyPI and downloading browser binaries is typical but carries the usual risks of third-party Python packages and browser downloads (supply-chain risk, arbitrary code execution during install).

Credentials

The skill declares no required environment variables or external credentials. Authentication is via browser login (not via declared env vars). The code does not request unrelated credentials or config paths. The only notable point is that credentials/session state will be stored locally by the library after login (as the README notes).

Persistence & Privilege

The skill does not request always: true, does not modify other skills, and does not declare elevated system privileges. The scripts call the notebooklm CLI and create local output directories only within user-specified locations.

Assessment

This skill appears coherent for automating NotebookLM via the unofficial notebooklm-py package, but the package source is unknown: 1) Review the notebooklm-py project's code/repo before installing (unofficial libraries can change or call internal APIs). 2) Avoid uploading highly sensitive documents — the tool intentionally uploads local files/URLs to NotebookLM/Google. 3) Be aware browser-based login stores tokens/cookies locally; consider isolating the login (VM/container) if you’re concerned. 4) Installing via pip and Playwright will download and run third-party code and a Chromium binary; only proceed if you trust the package. If you want lower risk, prefer an officially supported SDK or manually inspect the notebooklm-py package on PyPI/GitHub before use.

NotebookLM Skill

通过非官方 Python API 访问 Google NotebookLM 的全部功能。

前置要求

pip install notebooklm-py
pip install "notebooklm-py[browser]"  # 首次登录需要
playwright install chromium

认证

首次使用需要登录：

notebooklm login

或使用 Edge（某些企业环境需要）：

notebooklm login --browser msedge

核心功能

1. 笔记本管理

# 创建笔记本
notebooklm create "我的研究"

# 列出所有笔记本
notebooklm list

# 切换当前笔记本
notebooklm use <notebook_id>

# 删除笔记本
notebooklm delete <notebook_id>

2. 添加来源

# 添加网页
notebooklm source add "https://example.com/article"

# 添加本地文件（PDF、Word、Markdown、音频、视频、图片）
notebooklm source add "./paper.pdf"
notebooklm source add "./lecture.mp3"

# 添加 YouTube 视频
notebooklm source add "https://youtube.com/watch?v=xxx"

# 执行网络研究并自动导入
notebooklm source add-research "人工智能发展趋势" --mode deep

3. 内容生成

# 生成音频概述（播客）
notebooklm generate audio "让内容更生动有趣" --wait

# 生成视频概述
notebooklm generate video --style whiteboard --wait

# 生成电影风格视频
notebooklm generate cinematic-video "纪录片风格总结" --wait

# 生成幻灯片
notebooklm generate slide-deck

# 生成信息图
notebooklm generate infographic --orientation landscape

# 生成测验
notebooklm generate quiz --difficulty hard --quantity 10

# 生成记忆卡片
notebooklm generate flashcards --quantity 20

# 生成思维导图
notebooklm generate mind-map

# 生成数据表格
notebooklm generate data-table "对比主要观点"

# 生成报告
notebooklm generate report "研究简报"

音频格式选项：

• deep-dive - 深入探讨
• brief - 简要概述
• critique - 批判性分析
• debate - 辩论形式

视频风格选项：

• whiteboard - 白板风格
• news - 新闻风格
• cinematic - 电影风格

4. 下载生成的内容

# 下载音频（播客）
notebooklm download audio ./podcast.mp3

# 下载视频
notebooklm download video ./overview.mp4

# 下载幻灯片（支持 PDF 和 PPTX）
notebooklm download slide-deck ./slides.pdf
notebooklm download slide-deck --format pptx ./slides.pptx

# 下载测验（支持 JSON、Markdown、HTML）
notebooklm download quiz --format json ./quiz.json
notebooklm download quiz --format markdown ./quiz.md

# 下载记忆卡片
notebooklm download flashcards --format json ./flashcards.json

# 下载思维导图
notebooklm download mind-map ./mindmap.json

# 下载信息图
notebooklm download infographic ./infographic.png

# 下载数据表格
notebooklm download data-table ./data.csv

5. 聊天问答

# 向笔记本提问
notebooklm ask "总结核心观点"
notebooklm ask "解释这个概念"

# 使用自定义人格
notebooklm ask "用简单的语言解释" --persona "友好导师"

完整工作流示例

学术研究转播客

# 1. 创建笔记本
notebooklm create "论文解读"

# 2. 上传论文 PDF
notebooklm source add "./research-paper.pdf"

# 3. 生成播客（深入探讨风格）
notebooklm generate audio "深入分析研究方法" --format deep-dive --wait

# 4. 下载 MP3
notebooklm download audio ./paper-podcast.mp3

批量视频生成

# 1. 创建笔记本并添加多个来源
notebooklm create "课程笔记"
notebooklm source add "./lecture1.pdf"
notebooklm source add "./lecture2.pdf"
notebooklm source add "https://reference-site.com"

# 2. 生成白板风格教学视频
notebooklm generate video --style whiteboard --wait

# 3. 同时生成测验检验学习效果
notebooklm generate quiz --difficulty medium

# 4. 下载所有材料
notebooklm download video ./lesson.mp4
notebooklm download quiz --format markdown ./quiz.md

研究项目自动化

# 1. 执行深度网络研究
notebooklm create "市场调研"
notebooklm source add-research "2024年电动汽车市场趋势" --mode deep

# 2. 生成综合分析报告
notebooklm generate report "市场分析报告"

# 3. 生成数据对比表格
notebooklm generate data-table "对比主要厂商的市场份额"

# 4. 生成演示幻灯片
notebooklm generate slide-deck

# 5. 批量下载所有材料
notebooklm download report ./report.md
notebooklm download data-table ./data.csv
notebooklm download slide-deck ./presentation.pdf

Python API 使用

当需要更复杂的逻辑时，使用 Python API：

import asyncio
from notebooklm import NotebookLMClient

async def research_workflow():
    async with await NotebookLMClient.from_storage() as client:
        # 创建笔记本
        nb = await client.notebooks.create("自动化研究")
        
        # 批量添加来源
        await client.sources.add_url(nb.id, "https://example.com/1", wait=True)
        await client.sources.add_file(nb.id, "./doc.pdf", wait=True)
        
        # 生成内容
        status = await client.artifacts.generate_audio(
            nb.id, 
            instructions="制作引人入胜的播客",
            format="deep-dive"
        )
        await client.artifacts.wait_for_completion(nb.id, status.task_id)
        
        # 下载
        await client.artifacts.download_audio(nb.id, "output.mp3")
        
        return nb.id

# 运行
nb_id = asyncio.run(research_workflow())
print(f"完成！笔记本ID: {nb_id}")

故障排查

# 检查认证状态
notebooklm auth check --test

# 查看元数据
notebooklm metadata --json

# 查看分享状态
notebooklm share status

# 列出支持的语言
notebooklm language list

注意事项

• 这是非官方库，使用 Google 内部 API，可能随时变动
• 大量使用时可能触发 rate limit
• 适合原型、研究和个人项目
• 首次登录后，凭据会保存在本地，后续无需重复登录