Get Started#
This page guides you through the fastest path to a running Text To Speech microservice. The recommended deployment uses Docker Compose. Alternative deployment options are available in the How-to Guides section.
Before You Begin#
Confirm that your machine meets the System Requirements.
Review the Configuration Guide if you plan to change models, runtimes, devices, or precision.
Deploy with Docker#
The container image exposes the API on host port 8011 and mounts shared
folders for models, storage, and the Hugging Face cache.
docker compose up -d --build
If you hit permission errors on models/, storage/, or
.cache/huggingface/, see
Troubleshooting.
For the full step-by-step guide, see Run with Docker Compose.
Verify#
Once the service is running:
curl --noproxy '*' http://127.0.0.1:8011/health
Expected response:
{"status": "ok"}
Try It Out#
Once the service responds to the health check, send a speech synthesis request:
curl --noproxy '*' -sS \
-o speech.wav \
-w '%{http_code}\n' \
-X POST http://127.0.0.1:8011/v1/audio/speech \
-H 'Content-Type: application/json' \
-d '{
"model": "default",
"input": "The kiosk is ready for your next request.",
"response_format": "wav"
}'
Expected output:
200
The synthesized audio is saved to speech.wav in the current directory. Play
it with any WAV-capable player (aplay speech.wav on Linux, or open it in a
media player).
To list available voices and confirm the active model:
curl --noproxy '*' http://127.0.0.1:8011/v1/audio/voices
Expected output (example with the default SpeechT5 model):
{
"model": "microsoft/speecht5_tts",
"runtime": "openvino",
"speakers": ["default"],
"languages": ["English"]
}
Note: First startup may take longer than usual because the model is downloaded and converted during initialization. Subsequent starts are faster.
Next Steps#
API Reference for full endpoint details, Qwen TTS examples, and session persistence
Configuration Guide to customize the model, runtime, and device
Troubleshooting for common startup issues
Other Deployment Options#
Run on the Host — run directly with Python, without Docker
Build from Source — build the Docker image from source code