Audify vs Mozilla Document-to-Podcast
Audify
github.comMozilla Document-to-Podcast
github.comSide by side
| Figure | Audify | Mozilla Document-to-Podcast |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 0 |
| Spec score · AI Podcast Generators | 7.7 (#8) | 7.4 (#15) |
| License | The repository is licensed under the MIT License. | The project is licensed under Apache 2.0. |
| Purpose | Audify converts PDF, DOC, and DOCX documents into editable two-speaker podcast scripts and downloadable MP3 audio. | Document-to-Podcast is a Mozilla.ai Blueprint for turning input documents into podcasts featuring two speakers. |
| Workflow | Users upload a document, review and edit the generated dialogue, choose voices, then play or download the finished episode. | The pipeline extracts and cleans document text, generates a conversational script with a language model, then creates audio with text-to-speech. |
In their own words
Audify
Audify is a free, open-source application that turns PDF, DOC and DOCX files into editable two-speaker podcast scripts and downloadable MP3 episodes. It extracts document text and can use OCR when a scanned PDF yields little text. Users review and revise speaker turns, wording and flow, choose host and guest voices, and select conversational, educational or professional tones before generating audio. Ollama is the primary script-generation route, with OpenAI as a fallback; an OpenAI API key is required for text-to-speech, while Ollama is optional. The TTS service creates speech for dialogue turns, combines it into MP3, and supports playback and download. Audify uses FastAPI microservices with a React and Vite frontend and is orchestrated for local Docker Compose deployment. Its API handles uploads, generation, job status and downloads. Docker Engine 24.x or later and Docker Compose Plugin v2 or later are required. Uploads are limited to 10 MB, and jobs reset after container restarts unless storage is added.
Mozilla Document-to-Podcast
Mozilla Document-to-Podcast is an open-source Mozilla.ai blueprint that turns documents into two-speaker podcasts. Its workflow extracts and cleans text, uses a language model to create a conversational script, then generates speech audio. The CLI accepts PDF, HTML, TXT, DOCX and Markdown files, and saves podcast.txt and podcast.wav in the selected output folder. Users can customize prompts, speakers, voice profiles and model settings, and select text models that load with llama.cpp; Kokoro-82M is supported out of the box for text-to-speech. The project offers a command-line interface and a Streamlit demo app, with installation through PyPI or an editable clone. It is designed for local processing without external API calls or GPU access. The stated requirements include 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. When cleaned text exceeds the model's context-based character limit, the CLI may use only part of the input.