tts-dgx-spark-faster-qwen3-tts/DOCKERHUB_STREAMING.md
mARTin-B78 9708eede71 refactor: consolidate Docker files into docker/ and merge streaming repo
- Move full 4-service compose config/docker-compose.yml → docker/docker-compose.yml
- Move single-service quickstart docker-compose.yml → docker/docker-compose.simple.yml
- Replace private /home/sparky paths with /path/to/ placeholders in docker/docker-compose.yml
- Merge martinb78/qwen3-tts-streaming-dgx-spark into martinb78/faster-qwen3-tts-dgx-spark:streaming tag
- Update all image references: v4 → latest, streaming image → :streaming tag
- Update README and DOCKERHUB_STREAMING.md to reflect new structure

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-30 14:31:25 +02:00

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# Qwen3-TTS Streaming — DGX Spark (GB10)
Low-latency, OpenAI-compatible streaming TTS server for the **NVIDIA DGX Spark GB10**
(ARM64 / SM 121 / CUDA 13), powered by [faster-qwen3-tts](https://github.com/andimarafioti/faster-qwen3-tts)
with CUDA graph acceleration.
Streams WAV audio chunks to the client while generation is still running —
first audio arrives in under a second for typical sentences.
Part of a four-backend TTS stack documented on the NVIDIA Developer Forum:
[Three times (VoiceClone | VoiceDesign | CustomVoice) — Faster-Qwen3-TTS for NVIDIA DGX Spark (GB10)](https://forums.developer.nvidia.com/t/three-times-voiceclone-voicedesign-customvoice-faster-qwen3-tts-for-nvidia-dgx-spark-gb10/370530)
---
## Quick start
```bash
docker run -d \
--runtime nvidia \
--name qwen3-tts-streaming \
-p 8023:8000 \
-e NVIDIA_VISIBLE_DEVICES=all \
-v /path/to/Qwen3-TTS-12Hz-1.7B-Base:/models/Qwen3-TTS:ro \
-v /path/to/faster-qwen3-tts/config:/config:rw \
-v /path/to/active_voices:/voices:ro \
martinb78/faster-qwen3-tts-dgx-spark:streaming \
/bin/bash -c "
python3 /config/generate_voices.py &&
python3 /config/run_server.py
--model /models/Qwen3-TTS
--voices /config/voices.json
--port 8000
--max-seq-len 4096
"
```
Check it's running:
```bash
curl http://localhost:8023/health
```
---
## Voice configuration
Create a `voices.json` in your config directory. Each entry maps a voice ID to a
reference audio file and transcript:
```json
{
"william": {
"ref_audio": "/voices/william.wav",
"ref_text": "The quick brown fox jumps over the lazy dog.",
"language": "English",
"temperature": 0.75,
"top_k": 40,
"top_p": 0.85
},
"natasha": {
"ref_audio": "/voices/natasha.wav",
"ref_text": "She sells seashells by the seashore.",
"language": "English"
}
}
```
`temperature`, `top_k`, and `top_p` are optional — defaults are `0.8 / 50 / 0.9`.
---
## API
OpenAI-compatible `/v1/audio/speech`:
```bash
curl http://localhost:8023/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{"model": "tts-1", "input": "Hello world!", "voice": "william", "response_format": "wav"}' \
--output speech.wav
```
| Endpoint | Method | Description |
|---|---|---|
| `/v1/audio/speech` | POST | Generate speech (WAV / PCM / MP3) |
| `/v1/models` | GET | List available voice IDs |
| `/v1/audio/voices` | GET | Voice list (OpenWebUI fallback) |
| `/speakers` | GET | Voice list (SillyTavern) |
| `/health` | GET | Liveness check |
Works with **OpenWebUI**, **SillyTavern**, **llama-swap**, and any OpenAI-compatible client.
---
## Requirements
- NVIDIA DGX Spark GB10 or another ARM64 system with CUDA 13
- CUDA driver 580+
- Docker + NVIDIA Container Toolkit
- [Qwen3-TTS-12Hz-1.7B-Base](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-Base) weights downloaded locally
---
## Related images
| Image | Description |
|---|---|
| `martinb78/faster-qwen3-tts-dgx-spark:latest` / `:v5` | VoiceClone, VoiceDesign, and CustomVoice backends |
| `martinb78/faster-qwen3-tts-dgx-spark:streaming` | This tag — streaming VoiceClone |
Full four-backend `docker-compose` setup in `docker/docker-compose.yml` and detailed documentation on GitHub and the
[NVIDIA Developer Forum](https://forums.developer.nvidia.com/t/three-times-voiceclone-voicedesign-customvoice-faster-qwen3-tts-for-nvidia-dgx-spark-gb10/370530).