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Mozilla Document-to-Podcast

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What Mozilla Document-to-Podcast is

Mozilla Document-to-Podcast is a free, open-source Mozilla.ai blueprint for turning documents into two-speaker audio programs. Its workflow extracts and cleans text, uses a language model to create dialogue, then converts the script to speech. The command-line interface accepts PDF, HTML, TXT, DOCX, and Markdown files, and saves the script as podcast.txt and audio as podcast.wav in a chosen output folder.

The project supports text models that can be loaded by llama.cpp and compatible text-to-speech loaders; Kokoro-82M is supported out of the box. You can adjust the prompt, speaker names and roles, descriptions, voice profiles, and model settings. Use the CLI or the Streamlit graphical demo. The project is designed for local processing without external API calls or GPU access, an approach it describes as more privacy-friendly. It runs on Windows, macOS, and Linux. Stated requirements include Python 3.10 or later, at least 8 GB of RAM, and 20 GB of disk space; Apple M chips require Python 3.12 or later. Setup options include local installation, Google Colab, and GitHub Codespaces. The project is licensed under Apache 2.0.

Who it suits

It suits developers who want to add document-to-audio capabilities using open-source models and tools. It is also relevant to people who want to turn supported document formats into dialogue with customizable speakers and voices, while keeping processing local.

What it does well

  • Accepts PDF, HTML, TXT, DOCX, and Markdown files.
  • Creates both a script file and a WAV audio file.
  • Offers a CLI and a Streamlit graphical demo.
  • Supports customizable prompts, speakers, voice profiles, and model settings.
  • Designed to process locally without external API calls or GPU access.
  • Licensed under Apache 2.0.

What to know first

  • Requires at least 8 GB RAM and 20 GB disk space.
  • Needs Python 3.12 or later on Apple M chips.
  • May use only part of input that exceeds the model context limit.

Limits

When cleaned text exceeds the text model's context-based character limit, the CLI may use only a subset of the input.

Getting started

  1. Choose local installation, Google Colab, or GitHub Codespaces.
  2. For local use, install from PyPI with pip or clone the project and install it in editable mode.
  3. Use Windows, macOS, or Linux with the stated Python version, RAM, and disk requirements.
  4. Select a supported input document and text-to-text and text-to-speech models.
  5. Run the CLI or use the Streamlit demo app.

Verdict

Choose Mozilla Document-to-Podcast if you want a free, open-source way to generate two-speaker audio from documents, with configurable voices and local processing. Look elsewhere if your workflow needs the full text of documents that exceed the selected model's context-based character limit.

Questions

Is Mozilla Document-to-Podcast free?

Yes. It is free and open source.

Which document formats can it use?

The CLI accepts PDF, HTML, TXT, DOCX, and Markdown files.

What does it save?

It saves podcast.txt and podcast.wav in the selected output folder.

Which systems does it support?

The stated operating systems are Windows, macOS, and Linux. Requirements include Python 3.10 or later, except Apple M chips require Python 3.12 or later.

Can I customize the speakers and voices?

Yes. Speaker names, roles, descriptions, and voice profiles can be customized, along with the script prompt and model settings.

What license does it use?

It is licensed under Apache 2.0.

Facts from Mozilla Document-to-Podcast's own pages

Cloud setup options
The getting-started guide lists Google Colab, GitHub Codespaces, and local installation as setup options. · mozilla-ai.github.io, 7 Oct 2026
Customization
Users can customize the script prompt, speakers, voice profiles, and model settings. · mozilla-ai.github.io, 4 Oct 2026
Document formats
The documented pipeline accepts PDF, HTML, TXT, DOCX, and Markdown files. · mozilla-ai.github.io, 7 Oct 2026
Input formats
The CLI accepts PDF, HTML, TXT, DOCX, and Markdown files. · mozilla-ai.github.io, 4 Oct 2026
Installation
The project can be installed from PyPI with pip or cloned and installed in editable mode. · mozilla-ai.github.io, 4 Oct 2026
Interfaces
The project offers a command-line interface and a Streamlit graphical demo app. · github.com, 7 Oct 2026
License
The project is licensed under Apache 2.0. · github.com, 7 Oct 2026
Local processing
The project is designed to run on local setups without external API calls or GPU access, keeping processing local. · github.com, 7 Oct 2026
Model choice
Users can select a text-to-text model loadable by llama.cpp and can use the supported Kokoro-82M text-to-speech model out of the box. · mozilla-ai.github.io, 7 Oct 2026
Model support
Users can select text-to-text models loadable by llama.cpp and supported text-to-speech loaders; Kokoro-82M is listed as currently supported out of the box. · mozilla-ai.github.io, 4 Oct 2026
Output files
The CLI writes a podcast script as podcast.txt and audio as podcast.wav in the specified output folder. · mozilla-ai.github.io, 7 Oct 2026
Pipeline
The documented workflow extracts and cleans document text, generates a conversational script with a language model, then creates audio with text-to-speech. · mozilla-ai.github.io, 4 Oct 2026
Privacy
The project describes local processing without external API calls as a way to keep processing local and make it more privacy-friendly. · github.com, 4 Oct 2026
Purpose
Document-to-Podcast is a Mozilla.ai Blueprint for turning input documents into podcasts featuring two speakers. · github.com, 7 Oct 2026
Speaker voices
Each speaker can have a distinct voice profile, and speaker names, roles, descriptions, and voice profiles are customizable. · mozilla-ai.github.io, 7 Oct 2026
Support
The README directs users with issues to the troubleshooting documentation before opening a new issue, and the docs invite questions on Discord. · github.com, 7 Oct 2026
Supported operating systems
The stated system requirements list Windows, macOS, and Linux, Python 3.10 or later (3.12 or later for Apple M chips), at least 8 GB RAM, and at least 20 GB disk space. · github.com, 4 Oct 2026
System requirements
The README lists Windows, macOS, or Linux, Python 3.10 or later (3.12 or later for Apple M chips), at least 8 GB RAM, and 20 GB disk space. · github.com, 7 Oct 2026
Target audience
The project describes Blueprints as tools for developers to integrate AI capabilities into their projects using open-source models and tools. · mozilla-ai.github.io, 7 Oct 2026
Usage limit
The CLI may use only a subset of the input when cleaned text exceeds the text model's context-based character limit. · mozilla-ai.github.io, 4 Oct 2026
Workflow
The pipeline extracts and cleans document text, generates a conversational script with a language model, then creates audio with text-to-speech. · mozilla-ai.github.io, 7 Oct 2026

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