voice_audio_multi/examples/docker/server/EXAMPLE.md
Fabio c36510c21e
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Initial import: audio.cpp with Orange Pi documentation
2026-11-04 19:05:22 +01:00

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# Docker Compose Server
Run the audio.cpp TTS server as configured in the server JSON files
with Docker Compose.
## PocketTTS
### 1. Download the PocketTTS model
Get the English q8 model from
[audio-cpp/audio.cpp-gguf](https://huggingface.co/audio-cpp/audio.cpp-gguf/tree/main/PocketTTS-GGUF)
on Hugging Face.
Place the files from `english/` into `../models/PocketTTS-GGUF/english/`:
The directory should look like:
```
../models/PocketTTS-GGUF/english/
├── pocket-tts-english-q8_0.gguf
└── embeddings/
├── alba.safetensors
└── ...
```
### 2. Start the server
Start **one** of:
```bash
docker compose -f pocket-tts-cuda12.yml up
docker compose -f pocket-tts-cuda13.yml up
docker compose -f pocket-tts-cpu.yml up
```
### 3. Optionally: Wait for server to be ready
```bash
./wait-for-server.sh
```
### 4. Generate speech
```bash
./pocket-tts.sh
```
This sends a request to `http://localhost:8080/v1/audio/speech` and saves
the result to `output/speech.wav`.
## Qwen3-TTS (with voice cloning)
### 1. Download the Qwen3-TTS model
Get the q8 model from
[audio-cpp/audio.cpp-gguf](https://huggingface.co/audio-cpp/audio.cpp-gguf/tree/main/Qwen3-TTS-12Hz-1.7B-Base-GGUF)
on Hugging Face.
Place the file into `../models/Qwen3-TTS-12Hz-1.7B-Base-GGUF/`:
The directory should look like:
```
../models/Qwen3-TTS-12Hz-1.7B-Base-GGUF/
└── qwen3-tts-12hz-1.7b-base-q8_0_v2.gguf
```
### 2. Add reference audio and transcription
Put a `ref_audio.wav` and `ref_text.txt` in `../references/`.
The directory should look like:
```
../references/
├── ref_audio.wav
└── ref_text.txt
```
### 3. Start the server
Start **one** of:
```bash
docker compose -f qwen3-tts-cuda12.yml up
docker compose -f qwen3-tts-cuda13.yml up
docker compose -f qwen3-tts-cpu.yml up
```
### 4. Optionally: Wait for server to be ready
```bash
./wait-for-server.sh
```
### 5. Generate speech
```bash
./qwen3-tts.sh
```
This sends a request to `http://localhost:8080/v1/audio/speech` with voice
cloning parameters and saves the result to `output/speech.wav`.