Podcastfy vs Podframes
Podcastfy
github.comPodframes
github.comSide by side
| Figure | Podcastfy | Podframes |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 0 |
| Spec score · AI Podcast Generators | 8.0 (#6) | 7.0 (#23) |
| Interfaces | The project provides Python package and CLI usage, and documents a FastAPI deployment as beta for URLs. | The project includes a command-line runner and a local web studio. |
| License | The project is licensed under Apache 2.0. | The public repository is licensed under Apache-2.0. |
| Requirements | The quickstart lists Python 3.11 or higher and ffmpeg for audio processing as prerequisites. | The quickstart lists Node.js 22 or later, pnpm, ffmpeg, and API keys for the services used. |
| Ways to use it | The README documents installation as a Python package, a command-line interface, and a beta FastAPI service for URLs. | Podframes can be run through a command-line interface or a local web studio. |
Plans
In their own words
Podcastfy
Podcastfy is a free, open-source Python package that turns multimodal source material into multilingual audio conversations with generative AI. It accepts websites, PDFs, images, YouTube videos, raw text, transcript files and user-provided topics; topic generation can use grounded real-time web search. Users can set the podcast format, style, voices, language and structure, then generate short episodes of 2–5 minutes or longform episodes of 30 minutes or more. Transcript generation supports more than 100 language-model options, including OpenAI, Anthropic and Google models. Listed speech engines include OpenAI, Google, ElevenLabs and Microsoft Edge. Local language models are supported for transcript generation, offering the project’s stated privacy and control benefits. Usage is available through a Python package, command-line interface and beta FastAPI service for URLs, with MP3 audio export. API-key needs depend on selected models; a documented local-model and Edge TTS setup requires none. Python 3.11 or higher and ffmpeg are required. The project uses the Apache 2.0 license.