NotebookMLX

NotebookLM's podcast generation feature for macOS, running locally powered by MLX. Transform any PDF document into an engaging podcast conversation between two AI hosts.

Installation

Prerequisites

• uv
• Python
• macOS with Apple Silicon

Setup

1. Clone the repository:

   git clone https://github.com/BhaskarSteve/NotebookMLX.git
   cd NotebookMLX

2. Install dependencies:

   uv sync

3. Activate the virtual environment:

   source .venv/bin/activate

Run

python main.py --context file_name.pdf --speed 0.95

This will:

1. Extract and clean text from the PDF
2. Generate an engaging podcast script
3. Convert the script to natural-sounding audio
4. Save the final audio file to Output/file_name

The speed of output is usually fast, set your manual speed accordingly.

Customization

Custom Voice Samples

Create your own custom voice for podcast generation by running:

python sample.py

This will generate a sample.mp3 file that can be used for voice cloning in your podcast generation. Edit the text in sample.py to match the voice characteristics you want to clone.

Modify Podcast Host Characters

The personalities and characteristics of the podcast hosts (Chris and Sam) can be customized by editing the system prompt in script.py. Modify their roles, speaking styles, and interaction patterns to create your desired podcast format.

Models

• Script generation: mlx-community/Qwen3-8B-8bit
• Text cleaning: mlx-community/Qwen3-1.7B-4bit
• Text-to-speech: nari-labs/Dia-1.6B

Acknowledgments

• Qwen Team: For providing the light weight and excellent open-source Qwen language models.
• Nari Labs: For the outstanding Dia text-to-speech model. Consider contributing to nari-labs/dia.
• Cursor: For providing the student offer that made this development possible
• MLX Community: For porting these models to Apple Silicon and making local AI accessible