Add online serving to Stable Audio Diffusion and introduce v1/audio/generate endpoint (#1255)
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# Text-To-Audio
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Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/online_serving/stable_audio>.
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This example demonstrates how to deploy Stable Audio models for online text-to-audio generation using vLLM-Omni.
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## Supported Models
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| Model | Description |
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|-------|-------------|
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| `stabilityai/stable-audio-open-1.0` | Open-source audio generation, up to ~47 seconds, 44.1 kHz stereo |
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## Start Server
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### Basic Start
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```bash
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vllm-omni serve stabilityai/stable-audio-open-1.0 \
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--host 0.0.0.0 \
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--port 8000 \
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--gpu-memory-utilization 0.9 \
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--trust-remote-code \
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--enforce-eager \
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--omni
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```
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## API Calls
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### Method 1: Using curl
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```bash
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# Run all curl examples
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bash curl_examples.sh
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# Or execute directly
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curl -X POST http://localhost:8000/v1/audio/generate \
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-H "Content-Type: application/json" \
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-d '{
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"input": "The sound of a cat purring",
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"audio_length": 10.0
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}' --output cat.wav
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```
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### Method 2: Using Python Client
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```bash
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cd examples/online_serving/stable_audio
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# Simple generation
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python stable_audio_client.py \
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--text "The sound of a cat purring"
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# With custom duration
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python stable_audio_client.py \
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--text "A dog barking" \
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--audio_length 5.0
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# With all parameters
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python stable_audio_client.py \
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--text "Thunder and rain" \
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--audio_length 15.0 \
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--negative_prompt "Low quality" \
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--guidance_scale 7.0 \
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--num_inference_steps 100 \
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--seed 42 \
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--output thunder.wav
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```
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The Python client supports the following command-line arguments:
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- `--api_url`: API endpoint URL (default: `http://localhost:8000/v1/audio/generate`)
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- `--text`: Text prompt for audio generation (default: `"The sound of a cat purring"`)
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- `--audio_length`: Audio length in seconds (default: `10.0`, max ~47s for `stable-audio-open-1.0`)
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- `--audio_start`: Audio start time in seconds (default: `0.0`)
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- `--negative_prompt`: Negative prompt for classifier-free guidance (default: `"Low quality"`)
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- `--guidance_scale`: Guidance scale for diffusion (default: `7.0`)
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- `--num_inference_steps`: Number of inference steps (default: `100`)
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- `--seed`: Random seed for reproducibility (default: `None`)
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- `--response_format`: Audio output format (default: `wav`). Options: `wav`, `mp3`, `flac`, `pcm`
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- `--output`: Output file path (default: `stable_audio_output.wav`)
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### Method 3: Using Python httpx
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```python
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import httpx
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response = httpx.post(
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"http://localhost:8000/v1/audio/generate",
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json={
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"input": "The sound of ocean waves crashing on a beach",
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"audio_length": 10.0,
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"negative_prompt": "Low quality, distorted",
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"guidance_scale": 7.0,
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"num_inference_steps": 100,
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},
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timeout=300.0,
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)
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with open("ocean.wav", "wb") as f:
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f.write(response.content)
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```
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## Request Format
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### Simple Generation
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```json
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{
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"input": "The sound of ocean waves"
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}
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```
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### Generation with Parameters
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```json
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{
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"input": "A piano playing a gentle melody",
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"audio_length": 10.0,
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"negative_prompt": "Low quality, distorted, noisy",
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"guidance_scale": 8.0,
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"num_inference_steps": 150,
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"seed": 42,
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"response_format": "wav"
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}
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```
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## API Reference
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### Endpoint
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```
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POST /v1/audio/generate
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Content-Type: application/json
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```
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### Generation Parameters
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| Parameter | Type | Default | Description |
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|-----------|------|---------|-------------|
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| `input` | string | **required** | Text prompt describing the audio to generate |
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| `model` | string | server's model | Model to use (optional, should match server if specified) |
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| `response_format` | string | "wav" | Audio format: wav, mp3, flac, pcm, aac, opus |
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| `speed` | float | 1.0 | Playback speed (0.25 - 4.0) |
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| `audio_length` | float | null | Audio duration in seconds (max ~47s for `stable-audio-open-1.0`) |
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| `audio_start` | float | 0.0 | Audio start time in seconds |
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| `negative_prompt` | string | null | Text describing what to avoid in generation |
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| `guidance_scale` | float | model default | Classifier-free guidance scale (higher = more adherence to prompt) |
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| `num_inference_steps` | int | model default | Number of denoising steps (higher = better quality, slower) |
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| `seed` | int | null | Random seed for reproducible generation |
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### Response Format
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Returns binary audio data with appropriate `Content-Type` header (e.g., `audio/wav`).
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## Tuning Tips
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1. **Audio Length**: Keep under 47 seconds for `stable-audio-open-1.0`.
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2. **Quality vs Speed**:
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- 50 steps: Fast, decent quality (quick previews)
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- 100 steps: Good balance (general purpose)
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- 150+ steps: High quality, slower (final / critical audio)
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3. **Guidance Scale**:
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- Lower (3 - 5): More creative / varied output
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- Default (7): Good balance
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- Higher (10+): Strict adherence to the prompt
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4. **Negative Prompts**: Use to avoid unwanted characteristics such as `"Low quality"`, `"distorted"`, `"noisy"`.
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5. **Seeds**: Set a fixed seed to get deterministic, reproducible results.
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## File Description
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| File | Description |
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|------|-------------|
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| `curl_examples.sh` | Curl examples covering common use cases |
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| `stable_audio_client.py` | Python client with full CLI argument support |
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## Troubleshooting
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1. **Audio generation model did not produce audio output**: Verify the server started successfully and the model loaded without errors.
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2. **Connection refused**: Make sure the server is running on the correct port.
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3. **Generation timeout**: Reduce `num_inference_steps` or `audio_length`, and check GPU memory with `nvidia-smi`.
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4. **Out of memory**: Lower `--gpu-memory-utilization` or reduce `audio_length`.
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5. **Audio quality issues**: Increase `num_inference_steps`, add a negative prompt, or raise `guidance_scale`.
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## Example materials
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??? abstract "stable_audio_client.py"
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``````py
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--8<-- "examples/online_serving/stable_audio/stable_audio_client.py"
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``````
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??? abstract "curl_examples.sh"
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``````sh
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--8<-- "examples/online_serving/stable_audio/curl_examples.sh"
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``````
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