Local-NotebookLM: An Open-Source Local Version of NotebookLM That Turns PDFs into Podcasts 222

What is Local-NotebookLM?

Local-NotebookLM is a localized AItool that can convert PDF documents into podcasts. It supports local language models (LLM) and text-to-speech (TTS) models, allowing users to generate podcasts in different styles and lengths based on their needs.

Local-NotebookLM Features

Intelligent Document Processing

• Automatic Text Extraction: Extracts text from PDFs, automatically cleaning up formatting errors and redundant content.

• Academic Paper Support: Supports processing academic papers that contain mathematical formulas.

• Intelligent Chunk Processing: Supports large file processing, with a maximum of 100,000 characters, automatically chunked to optimize processing efficiency.

Multi-Mode Content Generation

• Rich Output Formats: Supports 15 output formats, including podcasts, interviews, debates, lectures, and more.

• Diverse Content Styles: Offers 8 content styles, covering professional, academic, casual, humorous, and more.

• Flexible Content Length: Supports 4 content lengths, ranging from short (10 minutes) to long (100+ minutes).

Flexible Model Support

• Multi-LLM Service Compatibility: Supports 6 LLM services, including OpenAI, Groq, and local models.

• Configurable TTS Voice Roles: Supports host and guest dual-role dialogue, with customizable voice roles.

• Local-First Design: Prioritizes the use of local resources to protect privacy while reducing usage costs.

All-Channel Usage

• One-Click CLI Generation: Quickly generate content with simple commands.

• Python API Integration: Supports Python API integration for developer convenience.

• Web-Based Service: FastAPI-based web service for easy online operation.

Installation and Configuration

• Installation Requirements: Requires Docker Desktop and Kokoro-FastAPI to be installed.

• Installation Steps: Clone the project via Git, create and activate a virtual environment, then install the required Python packages.

• Configuration File: A config.yaml file needs to be created for configuring the output directory, LLM provider, model name, voice cloning parameters, etc.

How to Use Local-NotebookLM

• Environment Preparation: Depending on the LLM provider used, start the corresponding service or ensure the API key is available.

• Run the Script: Convert a PDF file into a podcast by running the command python main.py input.pdf [options].

• Optional Parameters: Users can specify the podcast's style, length, chunk size for text processing, and more.

Local-NotebookLM Processing Workflow

1. PDF Processing: Extract PDF text, clean it, and split it into processable chunks.

2. Script Generation: Generate a podcast script based on the specified style and length.

3. TTS Optimization: Optimize the script to improve the naturalness of speech synthesis.

4. Audio Generation: Convert text to speech and generate the final audio file.

FAQ

1. How does Local-NotebookLM generate podcasts?

• Upload the PDF file to the tool.

• Use the command line to run the script, specifying the podcast's style and length.

• The tool will automatically process the text and generate the audio file

2. What is the difference between Local-NotebookLM and NotebookLM?

• Local-NotebookLM is a localized tool that runs on a local machine, supporting local LLM and TTS models.

• NotebookLM is a cloud-based tool primarily used for note management and document analysis, supporting AI-driven summaries, collaboration, and audio generation.

GitHub Repository:https://github.com/Goekdeniz-Guelmez/Local-NotebookLM