Streaming & Advanced Usage

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:

Interactive Documentation: http://localhost:4123/docs
Alternative Documentation: http://localhost:4123/redoc
OpenAPI Schema: http://localhost:4123/openapi.json

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

Streaming & Advanced Usage

Streaming TTS API Documentation

🎵 Overview

✨ Key Benefits

🚀 Streaming Endpoints

Basic Streaming

Streaming with Voice Upload

🎛️ Streaming Parameters

Core TTS Parameters

Streaming-Specific Parameters

📝 Streaming Strategies

Sentence Strategy (Default)

Paragraph Strategy

Fixed Strategy

Word Strategy

🎯 Quality vs Speed Settings

Fast Mode

Balanced Mode (Default)

High Quality Mode

💻 Usage Examples

Basic cURL Examples

Python Examples

Basic Streaming

Advanced Streaming with Progress

Real-time Playback with pyaudio

JavaScript/TypeScript Examples

Basic Streaming

Real-time Audio Playback

📊 Performance Optimization

Choosing Optimal Settings

Memory Optimization

🔄 Progress Monitoring

Real-time Progress API

Integration with Frontend

🛠️ Troubleshooting

Common Issues

Debugging Commands

🔄 Comparison: Streaming vs Standard

When to Use Streaming

Performance Comparison

🚀 Future Enhancements

📖 API Reference

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