Add online serving to Stable Audio Diffusion TTS

examples/online_serving/stable_audio/README.md

@@ -0,0 +1,234 @@
+# Stable Audio Online Serving
+
+Generate audio from text prompts using Stable Audio models via an OpenAI-compatible API endpoint.
+
+## Features
+
+- **OpenAI-compatible API**: Use `/v1/audio/speech` endpoint
+- **Flexible control**: Adjust audio length, guidance scale, inference steps
+- **Quality control**: Use negative prompts to avoid unwanted characteristics
+- **Reproducible**: Set random seed for deterministic generation
+
+## Quick Start
+
+### 1. Start the Server
+
+```bash
+vllm-omni serve stabilityai/stable-audio-open-1.0 \
+    --host 0.0.0.0 \
+    --port 8000 \
+    --gpu-memory-utilization 0.9 \
+    --trust-remote-code \
+    --enforce-eager \
+    --omni
+```
+
+### 2. Generate Audio
+
+#### Using curl
+
+```bash
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "The sound of a cat purring",
+        "audio_length": 10.0
+    }' --output cat.wav
+```
+
+#### Using Python Client
+
+```bash
+python stable_audio_client.py \
+    --text "The sound of a cat purring" \
+    --audio_length 10.0 \
+    --output cat.wav
+```
+
+#### Using Bash Script
+
+```bash
+bash curl_examples.sh
+```
+
+## API Reference
+
+### Endpoint
+
+```
+POST /v1/audio/speech
+```
+
+### Request Body
+
+```json
+{
+    "input": "Text description of the audio",
+    "audio_length": 10.0,
+    "audio_start": 0.0,
+    "negative_prompt": "Low quality",
+    "guidance_scale": 7.0,
+    "num_inference_steps": 100,
+    "seed": 42,
+    "response_format": "wav"
+}
+```
+
+### Parameters
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `input` | string | **required** | Text prompt describing the audio to generate |
+| `audio_length` | float | 10.0 | Audio duration in seconds (max ~47s for stable-audio-open-1.0) |
+| `audio_start` | float | 0.0 | Audio start time in seconds |
+| `negative_prompt` | string | null | Text describing what to avoid in generation |
+| `guidance_scale` | float | 7.0 | Classifier-free guidance scale (higher = more adherence to prompt) |
+| `num_inference_steps` | int | 100 | Number of denoising steps (higher = better quality, slower) |
+| `seed` | int | null | Random seed for reproducibility |
+| `response_format` | string | "wav" | Output format: wav, mp3, flac, pcm |
+
+### Response
+
+Returns audio data in the requested format (default: WAV).
+
+## Usage Examples
+
+### Basic Generation
+
+```bash
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "The sound of ocean waves"
+    }' --output ocean.wav
+```
+
+### Custom Duration
+
+```bash
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "A dog barking",
+        "audio_length": 5.0
+    }' --output dog_5s.wav
+```
+
+### High Quality with Negative Prompt
+
+```bash
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "A piano playing a gentle melody",
+        "audio_length": 10.0,
+        "negative_prompt": "Low quality, distorted, noisy",
+        "guidance_scale": 8.0,
+        "num_inference_steps": 150
+    }' --output piano_hq.wav
+```
+
+### Reproducible Generation
+
+```bash
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "Thunder and rain sounds",
+        "audio_length": 15.0,
+        "seed": 42
+    }' --output thunder.wav
+```
+
+### Quick Generation (Fewer Steps)
+
+For faster generation with slightly lower quality:
+
+```bash
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "Birds chirping in a forest",
+        "audio_length": 8.0,
+        "num_inference_steps": 50
+    }' --output birds_quick.wav
+```
+
+## Python Client Examples
+
+### Simple Generation
+
+```bash
+python stable_audio_client.py \
+    --text "The sound of a cat purring"
+```
+
+### Custom Parameters
+
+```bash
+python stable_audio_client.py \
+    --text "Thunder and rain" \
+    --audio_length 15.0 \
+    --negative_prompt "Low quality" \
+    --guidance_scale 7.0 \
+    --num_inference_steps 100 \
+    --seed 42 \
+    --output thunder.wav
+```
+
+### Different Output Format
+
+```bash
+python stable_audio_client.py \
+    --text "Guitar playing" \
+    --response_format mp3 \
+    --output guitar.mp3
+```
+
+## Tips
+
+1. **Audio Length**: Keep under 47 seconds for `stable-audio-open-1.0`
+2. **Quality vs Speed**: 
+   - 50 steps: Fast, decent quality
+   - 100 steps: Good balance (default)
+   - 150+ steps: High quality, slower
+3. **Guidance Scale**: 
+   - Lower (3-5): More creative/varied
+   - Default (7): Good balance
+   - Higher (10+): More literal to prompt
+4. **Negative Prompts**: Use to avoid "Low quality", "distorted", "noisy", etc.
+5. **Seeds**: Use same seed for reproducible results
+
+## Performance
+
+| Inference Steps | Quality | Speed | Use Case |
+|----------------|---------|-------|----------|
+| 50 | Good | Fast | Quick previews |
+| 100 (default) | Very Good | Medium | Production |
+| 150+ | Excellent | Slow | Final/critical audio |
+
+## Troubleshooting
+
+### Server not responding
+- Check if server is running: `curl http://localhost:8000/health`
+- Check server logs for errors
+
+### Audio quality issues
+- Increase `num_inference_steps` (e.g., 150)
+- Add negative prompts: `"Low quality, distorted, noisy"`
+- Increase `guidance_scale` for more prompt adherence
+
+### Generation timeout
+- Reduce `num_inference_steps`
+- Reduce `audio_length`
+- Check GPU memory with `nvidia-smi`
+
+### Wrong audio length
+- Ensure `audio_length` is within model limits (~47s max)
+- Adjust `audio_start` if trimming is needed
+
+## See Also
+
+- [Offline Inference Example](../../offline_inference/text_to_audio/README.md)
+- [Stable Audio Model Card](https://huggingface.co/stabilityai/stable-audio-open-1.0)
+- [vLLM-Omni Documentation](https://github.com/vllm-project/vllm-omni)

examples/online_serving/stable_audio/curl_examples.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+# Examples for using Stable Audio with curl via /v1/audio/speech endpoint
+
+# Example 1: Simple request with default parameters
+echo "Example 1: Simple request with default parameters"
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "The sound audience clapping and cheering in a stadium"
+    }' --output stadium.wav
+
+# Example 2: Request with custom audio_length
+echo "Example 2: Custom audio length (5 seconds)"
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "The sound of a dog barking",
+        "audio_length": 5.0
+    }' --output dog_5s.wav
+
+# Example 3: Request with negative prompt for quality control
+echo "Example 3: With negative prompt"
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "A piano playing a gentle melody",
+        "audio_length": 10.0,
+        "negative_prompt": "Low quality, distorted, noisy"
+    }' --output piano.wav
+
+# Example 4: Full control with all parameters
+echo "Example 4: Full control (custom length, guidance, steps, seed)"
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "Thunder and rain sounds",
+        "audio_length": 15.0,
+        "negative_prompt": "Low quality",
+        "guidance_scale": 7.0,
+        "num_inference_steps": 100,
+        "seed": 42
+    }' --output thunder_rain.wav
+
+# Example 5: Quick generation with fewer steps (faster but lower quality)
+echo "Example 5: Quick generation (fewer steps)"
+curl -X POST http://localhost:8000/v1/audio/speech \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "Ocean waves crashing on a beach",
+        "audio_length": 8.0,
+        "num_inference_steps": 50
+    }' --output ocean.wav
+
+echo "All examples completed!"