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195 changes: 195 additions & 0 deletions docs/python_inference.md
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# VibeVoice Python Inference Guide

Complete API reference for VibeVoice text-to-speech.

## Table of Contents

- [Quick Start](#quick-start)
- [API Reference](#api-reference)
- [synthesize_speech()](#synthesize_speech)
- [list_default_voices()](#list_default_voices)
- [VibeVoiceStreamingTTS](#vibevoicestreamingtts)
- [AudioPlayer](#audioplayer)

---

## Quick Start

```python
from vibevoice import synthesize_speech

# Simplest
synthesize_speech("Hello world!")

# With device
synthesize_speech(text="Hello world!", device="cuda")
```

---

## API Reference

### synthesize_speech()

One-line function for text-to-speech.

```python
synthesize_speech(
text: str | Iterator[str],
device: str = "cuda",
output_file: str = None,
voice_prompt_path: str = None,
inference_steps: int = 5,
cfg_scale: float = 1.5,
**kwargs
)
```

**Key Parameters:**

- `text` - Text or iterator
- `device` - "cuda", "mps", or "cpu"
- `output_file` - Save path (optional)
- `inference_steps` - 5 (fast) to 50 (quality)
- `cfg_scale` - 1.0-2.0 (quality)

**Examples:**

```python
# Basic
synthesize_speech(text="Hello", device="cuda")

# Iterator (LLM streaming)
synthesize_speech(text=["Hello", "world"], device="cuda")

# Save file
synthesize_speech(text="Hello", device="cuda", output_file="out.wav")

# Custom voice
synthesize_speech(
text="Hello",
device="cuda",
voice_prompt_path="voices/custom.pt"
)

# High quality
synthesize_speech(text="Hello", device="cuda", inference_steps=50, cfg_scale=2.0)
```

---

### list_default_voices()

List available voice presets.

```python
voices = list_default_voices()
# Returns: ['en-Carter_man', 'en-Davis_man', 'en-Emma_woman', ...]
```

---

### VibeVoiceStreamingTTS

High-level TTS class for advanced usage.

**Constructor:**

```python
tts = VibeVoiceStreamingTTS(
model_path="microsoft/VibeVoice-Realtime-0.5B",
device="cuda",
voice_prompt_path=None, # Auto-loads default
inference_steps=5
)
```

**Parameters:**

- `model_path` - HuggingFace model ID
- `device` - "cuda", "mps", "cpu"
- `voice_prompt_path` - Voice file (optional, auto-loads if None)
- `inference_steps` - 5-50 (speed vs quality)

**Methods:**

#### `text_to_speech_streaming(text_iterator, cfg_scale=1.5)`

Generate speech from iterator.

```python
def text_gen():
yield "Hello world"

audio = tts.text_to_speech_streaming(text_gen())
# Returns: Iterator[np.ndarray]
```

#### `save_audio(audio, output_path)`

Save audio to WAV file.

```python
import numpy as np

chunks = list(tts.text_to_speech_streaming(text_gen()))
audio = np.concatenate(chunks)
tts.save_audio(audio, "output.wav")
```

---

### AudioPlayer

Audio playback with speaker selection.

**Constructor:**

```python
player = AudioPlayer(device_id=None, sample_rate=24000)
```

**Methods:**

#### `list_devices()` [static]

```python
AudioPlayer.list_devices()
# Shows available speakers
```

#### `play_stream(audio_iterator, realtime=True)`

```python
player.play_stream(audio, realtime=True) # Streaming
player.play_stream(audio, realtime=False) # Buffered
```

---

## Quick Reference

| Function | Purpose |
|----------|---------|
| `synthesize_speech()` | One-line TTS |
| `list_default_voices()` | See available voices |
| `VibeVoiceStreamingTTS` | Advanced TTS class |
| `AudioPlayer` | Audio playback |

**Devices:**
- `"cuda"` - NVIDIA GPU (fastest)
- `"mps"` - Apple Silicon
- `"cpu"` - CPU (slower)

**Quality Settings:**
- Fast: `inference_steps=5`, `cfg_scale=1.5`
- Quality: `inference_steps=50`, `cfg_scale=2.0`

**Default Voices:**
- en-Mike_man, en-Emma_woman, en-Carter_man, en-Davis_man, en-Frank_man, en-Grace_woman, in-Samuel_man

---

## License

See [LICENSE](../LICENSE) for details.
66 changes: 66 additions & 0 deletions examples/simple_inference.py
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"""
Simple VibeVoice Inference Example
This script demonstrates basic usage of the VibeVoice Python API.
Run from VibeVoice root:
python examples/simple_inference.py
"""

from vibevoice import VibeVoiceStreamingTTS, AudioPlayer


def main():
print("="*60)
print("VibeVoice Simple Inference Example")
print("="*60)
print()

# Configuration
MODEL_PATH = "microsoft/VibeVoice-Realtime-0.5B"
VOICE_PROMPT_PATH = "demo/voices/streaming_model/en-Emma_woman.pt" # Optional
DEVICE = "cuda" # or "cpu" or "mps"

# Initialize TTS
print("Initializing VibeVoice...")
tts = VibeVoiceStreamingTTS(
model_path=MODEL_PATH,
voice_prompt_path=VOICE_PROMPT_PATH,
device=DEVICE,
inference_steps=5 # Fast inference
)
print()

# Initialize audio player
print("Initializing audio player...")
player = AudioPlayer()
print()

# List available devices
print("Available audio devices:")
AudioPlayer.list_devices()
print()

# Generate text
def text_generator():
"""Simple text generator"""
text = "Hello! This is VibeVoice speaking. I can generate speech in real time."
for word in text.split():
yield word

# Generate and play
print("Generating and playing speech...")
print("Text: 'Hello! This is VibeVoice speaking. I can generate speech in real time.'")
print()

audio_stream = tts.text_to_speech_streaming(text_generator())
player.play_stream(audio_stream, realtime=True)

print()
print("="*60)
print("Done!")
print("="*60)


if __name__ == "__main__":
main()
26 changes: 25 additions & 1 deletion vibevoice/__init__.py
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@@ -1,4 +1,14 @@
# vibevoice/__init__.py

# High-level API
from .inference import (
VibeVoiceStreamingTTS,
AudioPlayer,
synthesize_speech,
list_default_voices
)

# Low-level API
from vibevoice.modular import (
VibeVoiceStreamingForConditionalGenerationInference,
VibeVoiceStreamingConfig,
Expand All @@ -7,10 +17,24 @@
VibeVoiceStreamingProcessor,
VibeVoiceTokenizerProcessor,
)
from .modular.streamer import (
AudioStreamer,
AsyncAudioStreamer
)

__all__ = [
# High-level API
'VibeVoiceStreamingTTS',
'AudioPlayer',
'synthesize_speech',
'list_default_voices',
# Low-level API
"VibeVoiceStreamingForConditionalGenerationInference",
"VibeVoiceStreamingConfig",
"VibeVoiceStreamingProcessor",
"VibeVoiceTokenizerProcessor",
]
'AudioStreamer',
'AsyncAudioStreamer',
]

__version__ = '0.0.1'
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