Turn sources into your podcast
Vozonda reads them, voices make waves, you listen.
What is Vozonda?
Give Vozonda articles, papers, PDFs, audio files, podcast episodes, screenshots, YouTube videos, RSS feeds or your own notes, and it turns them into the show you want. Audio sources are transcribed locally.
- Fourteen show formats: deep dive, quick brief, debate, critique, morning dispatch of your feeds, feature story, explainer, three-voice roundtable, and more.
- One to three voices, or a single narrator: in ten languages; translates sources into the language you want to hear.
- Watchlists: turn RSS feeds into a daily or weekly digest that fills your feed automatically.
- Every episode comes with: chapters, transcripts, takeaways, highlights, and shareable clips; read and fix the script before it is voiced.
- Self-hosted & private: runs on your hardware with Docker. Voice generation runs on CPU by default with Kokoro (no GPU required). No cloud logins, no telemetry, and no subscriptions.
- Personal RSS feed: publishes episodes to your private podcast feed with chapters and transcripts, compatible with any podcast player, and optionally to Nostr.
Which install do you want?
| You want | Use |
|---|---|
| The app (web UI, feeds, voices, everything) | Docker |
| The orchestrator API and pipeline without the web UI, e.g. to drive it from scripts or an agent | this package |
This package is the Python orchestrator only. It does not contain the web UI. You talk to it
over its HTTP API (/docs lists the routes) or through the MCP server.
Installation
Needs Python 3.11+, ffmpeg on the PATH, and an LLM endpoint (a local Ollama or vLLM, or any
OpenAI-compatible API).
pip install "vozonda[tts-kokoro]" # orchestrator + Kokoro voices on CPU
# or: uv tool install "vozonda[tts-kokoro]"
Optional extras
| Extra | Adds |
|---|---|
tts-kokoro |
Kokoro voices, CPU-friendly |
tts-piper |
Piper voices |
stt |
Local transcription of audio sources (faster-whisper) |
tts |
All of the above plus Qwen3-TTS (needs torch) |
mcp |
MCP server for agents |
Without a TTS extra the server starts, but it cannot voice an episode.
Usage
export VOZONDA_LLM_BASE=http://127.0.0.1:11434/v1 # your LLM endpoint
export VOZONDA_LLM_MODEL=qwen2.5:latest
vozonda # or: vozonda-api
The API listens on http://127.0.0.1:8787 (VOZONDA_HOST, VOZONDA_PORT change it); open
http://127.0.0.1:8787/docs for the routes. Every setting is in
.env.example. Before you expose
it beyond this computer, read the
deployment guide: remote
requests need the VOZONDA_TOKEN.
Docker Quickstart
The full app, with the web UI and all dependencies:
git clone https://github.com/Vozonda/vozonda.git
cd vozonda
docker compose up -d
Prebuilt multi-architecture containers are available from GitHub Container Registry:
docker pull ghcr.io/vozonda/vozonda:latest
Links & Community
- Website & Audio Samples: https://vozonda.com
- GitHub Repository: https://github.com/Vozonda/vozonda
- Bug Tracker: https://github.com/Vozonda/vozonda/issues
- License: MIT
Metadata
Release files for vozonda 0.7.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| vozonda-0.7.5.tar.gz | 790.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vozonda-0.7.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.1 MB
Release files / vozonda-0.7.5.tar.gz
| Download URL | vozonda-0.7.5.tar.gz |
|---|---|
| Size | 790.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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Signed by GitHub Actions, verified by PyPI on Oct 15, 2026.
Transparency logRelease files / vozonda-0.7.5-py3-none-any.whl
| Download URL | vozonda-0.7.5-py3-none-any.whl |
|---|---|
| Size | 327.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 15, 2026.
Transparency log