Streaming & Advanced Usage - travisvn/chatterbox-tts-api GitHub Wiki

Streaming TTS API Documentation

🎵 Overview

The Chatterbox TTS API supports real-time audio streaming, allowing clients to receive audio data as it's generated rather than waiting for complete processing. This significantly reduces perceived latency and improves user experience, especially for longer texts.

✨ Key Benefits

  • Lower Latency: Start receiving audio before full generation is complete
  • Better User Experience: Perceived faster response times for long texts
  • Resource Efficiency: Lower memory usage as chunks are processed individually
  • Real-time Processing: Audio generation happens progressively
  • Interruption Support: Can potentially stop generation mid-stream if needed
  • Memory Optimization: Automatic cleanup of processed chunks

🚀 Streaming Endpoints

Basic Streaming

POST /audio/speech/stream

Generate and stream speech audio in real-time using the configured voice sample.

Request Body (JSON):

{
  "input": "Text to convert to speech",
  "exaggeration": 0.7,
  "cfg_weight": 0.4,
  "temperature": 0.9,
  "streaming_chunk_size": 200,
  "streaming_strategy": "sentence"
}

Streaming with Voice Upload

POST /audio/speech/stream/upload

Generate and stream speech audio with optional custom voice file upload.

Request (Multipart Form):

  • input (string): Text to convert to speech
  • voice_file (file, optional): Custom voice sample file
  • exaggeration (float, optional): Emotion intensity (0.25-2.0)
  • cfg_weight (float, optional): Pace control (0.0-1.0)
  • temperature (float, optional): Sampling randomness (0.05-5.0)
  • streaming_chunk_size (int, optional): Characters per streaming chunk
  • streaming_strategy (string, optional): Chunking strategy

🎛️ Streaming Parameters

Core TTS Parameters

Parameter Type Range Default Description
exaggeration float 0.25-2.0 0.5 Emotion intensity
cfg_weight float 0.0-1.0 0.5 Pace control
temperature float 0.05-5.0 0.8 Sampling randomness

Streaming-Specific Parameters

Parameter Type Options Default Description
streaming_chunk_size int 50-500 200 Characters per streaming chunk
streaming_strategy string sentence, paragraph, fixed, word "sentence" How to break up text for streaming
streaming_buffer_size int 1-10 3 Number of chunks to buffer
streaming_quality string fast, balanced, high "balanced" Speed vs quality trade-off

📝 Streaming Strategies

Sentence Strategy (Default)

{
  "streaming_strategy": "sentence",
  "streaming_chunk_size": 200
}
  • Splits at sentence boundaries (., !, ?)
  • Respects sentence integrity
  • Good balance of latency and naturalness
  • Best for: General use, reading content

Paragraph Strategy

{
  "streaming_strategy": "paragraph",
  "streaming_chunk_size": 400
}
  • Splits at paragraph breaks (\n\n, double line breaks)
  • Maintains paragraph context
  • Longer chunks, more natural flow
  • Best for: Articles, stories, structured content

Fixed Strategy

{
  "streaming_strategy": "fixed",
  "streaming_chunk_size": 150
}
  • Fixed character count chunks
  • Predictable timing
  • May break mid-sentence
  • Best for: Consistent streaming timing, testing

Word Strategy

{
  "streaming_strategy": "word",
  "streaming_chunk_size": 100
}
  • Splits at word boundaries
  • Very fine-grained streaming
  • Maximum responsiveness
  • Best for: Real-time chat, interactive applications

🎯 Quality vs Speed Settings

Fast Mode

{
  "streaming_quality": "fast",
  "streaming_chunk_size": 100,
  "streaming_strategy": "word"
}
  • Smaller chunks for faster initial response
  • Lower quality synthesis parameters
  • Use case: Chat applications, real-time feedback

Balanced Mode (Default)

{
  "streaming_quality": "balanced",
  "streaming_chunk_size": 200,
  "streaming_strategy": "sentence"
}
  • Good balance of speed and quality
  • Sentence-aware chunking
  • Use case: General applications

High Quality Mode

{
  "streaming_quality": "high",
  "streaming_chunk_size": 300,
  "streaming_strategy": "paragraph"
}
  • Larger chunks for better context
  • Higher quality synthesis
  • Use case: Audiobooks, professional content

💻 Usage Examples

Basic cURL Examples

Simple Streaming:

curl -X POST http://localhost:4123/v1/audio/speech/stream \
  -H "Content-Type: application/json" \
  -d '{"input": "This will stream as it generates!"}' \
  --output streaming.wav

Advanced Streaming with Custom Settings:

curl -X POST http://localhost:4123/v1/audio/speech/stream \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Long text that will be streamed efficiently...",
    "exaggeration": 0.8,
    "streaming_strategy": "sentence",
    "streaming_chunk_size": 150,
    "streaming_quality": "balanced"
  }' \
  --output advanced_stream.wav

Real-time Playback:

curl -X POST http://localhost:4123/v1/audio/speech/stream \
  -H "Content-Type: application/json" \
  -d '{"input": "Play this as it streams!", "streaming_quality": "fast"}' \
  | ffplay -f wav -i pipe:0 -autoexit -nodisp

Python Examples

Basic Streaming

import requests

response = requests.post(
    "http://localhost:4123/v1/audio/speech/stream",
    json={
        "input": "This streams as it's generated!",
        "streaming_strategy": "sentence",
        "streaming_chunk_size": 200
    },
    stream=True
)

with open("streaming_output.wav", "wb") as f:
    for chunk in response.iter_content(chunk_size=8192):
        if chunk:
            f.write(chunk)
            print(f"Received chunk: {len(chunk)} bytes")

Advanced Streaming with Progress

import requests
import threading
import time

def stream_with_progress(text, **params):
    """Stream TTS with real-time progress monitoring"""

    # Start streaming request
    response = requests.post(
        "http://localhost:4123/v1/audio/speech/stream",
        json={"input": text, **params},
        stream=True
    )

    # Monitor progress in separate thread
    def monitor_progress():
        while True:
            try:
                progress = requests.get("http://localhost:4123/v1/status/progress").json()
                if progress.get("is_processing"):
                    print(f"Progress: {progress.get('progress_percentage', 0):.1f}%")
                    print(f"Step: {progress.get('current_step', '')}")
                else:
                    break
                time.sleep(0.5)
            except:
                break

    progress_thread = threading.Thread(target=monitor_progress)
    progress_thread.start()

    # Stream audio
    with open("streaming_output.wav", "wb") as f:
        total_bytes = 0
        for chunk in response.iter_content(chunk_size=4096):
            if chunk:
                f.write(chunk)
                total_bytes += len(chunk)
                print(f"Streamed {total_bytes:,} bytes")

    progress_thread.join()
    print("Streaming complete!")

# Usage
stream_with_progress(
    "This is a long text that demonstrates streaming with progress monitoring.",
    streaming_strategy="sentence",
    streaming_chunk_size=180,
    streaming_quality="balanced"
)

Real-time Playback with pyaudio

import requests
import pyaudio
import wave
import io
import threading

def stream_and_play_realtime(text, **params):
    """Stream TTS and play audio in real-time using pyaudio"""

    # Audio settings
    CHUNK = 1024
    FORMAT = pyaudio.paInt16
    CHANNELS = 1
    RATE = 22050  # Adjust based on your TTS model

    # Initialize PyAudio
    p = pyaudio.PyAudio()
    stream = p.open(
        format=FORMAT,
        channels=CHANNELS,
        rate=RATE,
        output=True,
        frames_per_buffer=CHUNK
    )

    # Start streaming request
    response = requests.post(
        "http://localhost:4123/v1/audio/speech/stream",
        json={"input": text, **params},
        stream=True
    )

    # Buffer for WAV processing
    audio_buffer = io.BytesIO()
    header_processed = False

    try:
        for chunk in response.iter_content(chunk_size=4096):
            if chunk:
                audio_buffer.write(chunk)

                # Skip WAV header for first chunk
                if not header_processed:
                    audio_buffer.seek(44)  # Skip WAV header
                    header_processed = True

                # Read and play audio data
                audio_buffer.seek(-len(chunk), 1)
                audio_data = audio_buffer.read()
                if len(audio_data) >= CHUNK:
                    stream.write(audio_data[:CHUNK])

    finally:
        stream.stop_stream()
        stream.close()
        p.terminate()

# Usage
stream_and_play_realtime(
    "This plays in real-time as it streams!",
    streaming_quality="fast",
    streaming_strategy="word"
)

JavaScript/TypeScript Examples

Basic Streaming

async function streamTTS(text: string, options: any = {}) {
  const response = await fetch('/v1/audio/speech/stream', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      input: text,
      streaming_strategy: 'sentence',
      streaming_chunk_size: 200,
      ...options,
    }),
  });

  const reader = response.body?.getReader();
  const chunks: Uint8Array[] = [];

  while (true) {
    const { done, value } = await reader!.read();
    if (done) break;

    chunks.push(value);
    console.log(`Received chunk: ${value.length} bytes`);
  }

  // Combine chunks into final audio
  const totalLength = chunks.reduce((sum, chunk) => sum + chunk.length, 0);
  const audioData = new Uint8Array(totalLength);
  let offset = 0;

  for (const chunk of chunks) {
    audioData.set(chunk, offset);
    offset += chunk.length;
  }

  return audioData;
}

Real-time Audio Playback

async function streamAndPlayTTS(text: string) {
  const audioContext = new AudioContext();
  const response = await fetch('/v1/audio/speech/stream', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      input: text,
      streaming_quality: 'fast',
    }),
  });

  const reader = response.body?.getReader();
  let audioBuffer = new Uint8Array();

  while (true) {
    const { done, value } = await reader!.read();
    if (done) break;

    // Append new chunk
    const newBuffer = new Uint8Array(audioBuffer.length + value.length);
    newBuffer.set(audioBuffer);
    newBuffer.set(value, audioBuffer.length);
    audioBuffer = newBuffer;

    // Try to decode and play if we have enough data
    if (audioBuffer.length > 8192) {
      try {
        const audioData = await audioContext.decodeAudioData(
          audioBuffer.buffer.slice()
        );
        const source = audioContext.createBufferSource();
        source.buffer = audioData;
        source.connect(audioContext.destination);
        source.start();
      } catch (e) {
        // Not enough data yet, continue streaming
      }
    }
  }
}

📊 Performance Optimization

Choosing Optimal Settings

For Lowest Latency:

{
  "streaming_quality": "fast",
  "streaming_strategy": "word",
  "streaming_chunk_size": 80,
  "streaming_buffer_size": 1
}

For Best Quality:

{
  "streaming_quality": "high",
  "streaming_strategy": "paragraph",
  "streaming_chunk_size": 350,
  "streaming_buffer_size": 5
}

For Balanced Performance:

{
  "streaming_quality": "balanced",
  "streaming_strategy": "sentence",
  "streaming_chunk_size": 200,
  "streaming_buffer_size": 3
}

Memory Optimization

The streaming implementation includes automatic memory management:

  • Chunks are processed and freed immediately
  • GPU memory is cleared periodically
  • Temporary files are cleaned up automatically
  • Progress tracking prevents memory leaks

🔄 Progress Monitoring

Real-time Progress API

While streaming is active, you can monitor progress:

curl "http://localhost:4123/v1/status/progress"

Response:

{
  "is_processing": true,
  "status": "generating_audio",
  "current_step": "Streaming audio for chunk 3/8",
  "current_chunk": 3,
  "total_chunks": 8,
  "progress_percentage": 37.5,
  "duration_seconds": 2.1,
  "estimated_completion": 1704067205.0,
  "text_preview": "This is the text being streamed..."
}

Integration with Frontend

// Monitor streaming progress
const monitorStreaming = async () => {
  const interval = setInterval(async () => {
    try {
      const response = await fetch('/v1/status/progress');
      const progress = await response.json();

      if (progress.is_processing) {
        updateProgressBar(progress.progress_percentage);
        updateStatus(progress.current_step);
      } else {
        clearInterval(interval);
        onStreamingComplete();
      }
    } catch (error) {
      console.error('Progress monitoring failed:', error);
    }
  }, 500);
};

🛠️ Troubleshooting

Common Issues

Streaming Stops Unexpectedly:

  • Check network stability
  • Verify streaming headers are set correctly
  • Ensure client supports chunked transfer encoding

Audio Quality Issues:

  • Try larger streaming_chunk_size
  • Use "sentence" or "paragraph" strategy
  • Increase streaming_quality to "balanced" or "high"

High Latency:

  • Reduce streaming_chunk_size
  • Use "word" strategy for maximum responsiveness
  • Set streaming_quality to "fast"

Memory Issues:

  • Reduce streaming_buffer_size
  • Use smaller streaming_chunk_size
  • Monitor memory usage via /memory endpoint

Debugging Commands

# Test streaming endpoint
curl -v -X POST http://localhost:4123/v1/audio/speech/stream \
  -H "Content-Type: application/json" \
  -d '{"input": "Test streaming"}' \
  --output debug_stream.wav

# Monitor memory during streaming
watch -n 1 'curl -s http://localhost:4123/memory | jq .memory_info'

# Check streaming progress
watch -n 0.5 'curl -s http://localhost:4123/v1/status/progress | jq .'

🔄 Comparison: Streaming vs Standard

When to Use Streaming

Use Streaming When:

  • Text length > 500 characters
  • Building real-time applications
  • Memory usage is a concern
  • Users expect immediate audio feedback
  • Implementing chat or interactive features

Use Standard When:

  • Text length < 200 characters
  • Need complete audio file before processing
  • Working with simple integrations
  • Bandwidth is limited
  • Processing batch content

Performance Comparison

Aspect Standard Generation Streaming Generation
Initial Latency Full generation time ~1-2 seconds
Memory Usage Peak during concat Constant low usage
User Experience Wait then play Progressive playback
Network Usage Single large transfer Multiple small chunks
Complexity Simple Moderate

🚀 Future Enhancements

Planned improvements to the streaming functionality:

  • Adaptive Chunking: Automatically adjust chunk size based on content
  • Quality Adaptation: Dynamic quality adjustment based on network conditions
  • Interruption Support: Ability to stop streaming mid-generation
  • Buffer Prediction: Intelligent buffering based on generation speed
  • Multi-voice Streaming: Stream different voices for different speakers
  • WebSocket Support: Real-time bidirectional streaming

📖 API Reference

For complete API documentation including all endpoints, parameters, and examples, visit:

The streaming endpoints are fully documented with request/response schemas, parameter validation, and example payloads.