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https://github.com/remsky/Kokoro-FastAPI.git
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Add StreamingAudioWriter class for audio format conversions and remove deprecated migration notes
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remsky
parent
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commit
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4 changed files with 141 additions and 180 deletions
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@ -1,70 +0,0 @@
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# UV Setup
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Deprecated notes for myself
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## Structure
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```
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docker/
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├── cpu/
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│ ├── pyproject.toml # CPU deps (torch CPU)
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│ └── requirements.lock # CPU lockfile
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├── gpu/
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│ ├── pyproject.toml # GPU deps (torch CUDA)
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│ └── requirements.lock # GPU lockfile
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└── shared/
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└── pyproject.toml # Common deps
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```
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## Regenerate Lock Files
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### CPU
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```bash
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cd docker/cpu
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uv pip compile pyproject.toml ../shared/pyproject.toml --output-file requirements.lock
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```
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### GPU
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```bash
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cd docker/gpu
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uv pip compile pyproject.toml ../shared/pyproject.toml --output-file requirements.lock
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```
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## Local Dev Setup
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### CPU
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```bash
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cd docker/cpu
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uv venv
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.venv\Scripts\activate # Windows
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uv pip sync requirements.lock
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```
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### GPU
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```bash
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cd docker/gpu
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uv venv
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.venv\Scripts\activate # Windows
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uv pip sync requirements.lock --extra-index-url https://download.pytorch.org/whl/cu121 --index-strategy unsafe-best-match
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```
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### Run Server
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```bash
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# From project root with venv active:
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uvicorn api.src.main:app --reload
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```
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## Docker
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### CPU
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```bash
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cd docker/cpu
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docker compose up
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```
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### GPU
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```bash
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cd docker/gpu
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docker compose up
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```
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## Known Issues
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- Module imports: Run server from project root
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- PyTorch CUDA: Always use --extra-index-url and --index-strategy for GPU env
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@ -10,7 +10,7 @@ from loguru import logger
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from pydub import AudioSegment
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from ..core.config import settings
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from .streaming_audio_writer import StreamingAudioWriter
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class AudioNormalizer:
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"""Handles audio normalization state for a single stream"""
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@ -45,7 +45,7 @@ class AudioNormalizer:
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class AudioService:
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"""Service for audio format conversions"""
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"""Service for audio format conversions with streaming support"""
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# Default audio format settings balanced for speed and compression
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DEFAULT_SETTINGS = {
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@ -64,6 +64,8 @@ class AudioService:
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},
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}
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_writers = {}
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@staticmethod
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async def convert_audio(
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audio_data: np.ndarray,
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@ -72,127 +74,46 @@ class AudioService:
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is_first_chunk: bool = True,
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is_last_chunk: bool = False,
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normalizer: AudioNormalizer = None,
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format_settings: dict = None,
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stream: bool = True,
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) -> bytes:
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"""Convert audio data to specified format
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"""Convert audio data to specified format with streaming support
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Args:
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audio_data: Numpy array of audio samples
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sample_rate: Sample rate of the audio
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output_format: Target format (wav, mp3, opus, flac, pcm)
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is_first_chunk: Whether this is the first chunk of a stream
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normalizer: Optional AudioNormalizer instance for consistent normalization across chunks
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format_settings: Optional dict of format-specific settings to override defaults
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Example: {
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"mp3": {
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"bitrate_mode": "VARIABLE",
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"compression_level": 0.8
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}
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}
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Default settings balance speed and compression:
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optimized for localhost @ 0.0
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- MP3: constant bitrate, no compression (0.0)
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- OPUS: no compression (0.0)
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- FLAC: no compression (0.0)
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output_format: Target format (wav, mp3, ogg, pcm)
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is_first_chunk: Whether this is the first chunk
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is_last_chunk: Whether this is the last chunk
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normalizer: Optional AudioNormalizer instance for consistent normalization
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Returns:
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Bytes of the converted audio
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Bytes of the converted audio chunk
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"""
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buffer = BytesIO()
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try:
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# Always normalize audio to ensure proper amplitude scaling
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if normalizer is None:
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normalizer = AudioNormalizer()
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normalized_audio = await normalizer.normalize(audio_data)
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if output_format == "pcm":
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# Raw 16-bit PCM samples, no header
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buffer.write(normalized_audio.tobytes())
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elif output_format == "wav":
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# Write the WAV header ourselves so that we can specify a "fake" data size.
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# This is necessary for streaming responses to work properly: if we simply
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# concatenated individual WAV files then the initial chunk's header length
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# would be shorter than the full file length and subsequent chunks' RIFF
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# headers would appear in the middle of the audio data.
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if is_first_chunk:
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# Modified from Python stdlib's wave.py module:
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buffer.write(b'RIFF')
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buffer.write(struct.pack('<L4s4sLHHLLHH4s',
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0xFFFFFFFF, # total size (set to max)
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b'WAVE',
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b'fmt ',
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16,
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1, # PCM format
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1, # channels
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sample_rate,
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sample_rate * 2, # byte rate
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2, # block align
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16, # bits per sample
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b'data'
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))
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buffer.write(struct.pack('<L', 0xFFFFFFFF)) # data size (set to max)
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# write raw PCM data
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buffer.write(normalized_audio.tobytes())
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elif output_format == "mp3":
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# MP3 format with proper framing
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settings = format_settings.get("mp3", {}) if format_settings else {}
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settings = {**AudioService.DEFAULT_SETTINGS["mp3"], **settings}
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sf.write(
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buffer, normalized_audio, sample_rate, format="MP3", **settings
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)
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elif output_format == "opus":
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# Opus format in OGG container
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settings = format_settings.get("opus", {}) if format_settings else {}
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settings = {**AudioService.DEFAULT_SETTINGS["opus"], **settings}
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sf.write(
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buffer,
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normalized_audio,
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sample_rate,
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format="OGG",
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subtype="OPUS",
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**settings,
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)
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elif output_format == "flac":
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# FLAC format with proper framing
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if is_first_chunk:
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logger.info("Starting FLAC stream...")
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settings = format_settings.get("flac", {}) if format_settings else {}
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settings = {**AudioService.DEFAULT_SETTINGS["flac"], **settings}
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sf.write(
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buffer,
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normalized_audio,
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sample_rate,
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format="FLAC",
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subtype="PCM_16",
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**settings,
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)
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elif output_format == "aac":
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# Convert numpy array directly to AAC using pydub
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audio_segment = AudioSegment(
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normalized_audio.tobytes(),
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frame_rate=sample_rate,
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sample_width=normalized_audio.dtype.itemsize,
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channels=1 if len(normalized_audio.shape) == 1 else normalized_audio.shape[1]
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)
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settings = format_settings.get("aac", {}) if format_settings else {}
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settings = {**AudioService.DEFAULT_SETTINGS["aac"], **settings}
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audio_segment.export(
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buffer,
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format="adts", # ADTS is a common AAC container format
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bitrate=settings["bitrate"]
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)
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else:
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raise ValueError(
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f"Format {output_format} not supported. Supported formats are: wav, mp3, opus, flac, pcm, aac."
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# Get or create format-specific writer
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writer_key = f"{output_format}_{sample_rate}"
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if is_first_chunk or writer_key not in AudioService._writers:
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AudioService._writers[writer_key] = StreamingAudioWriter(
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output_format, sample_rate
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)
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writer = AudioService._writers[writer_key]
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buffer.seek(0)
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return buffer.getvalue()
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# Write the current chunk
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chunk_data = writer.write_chunk(normalized_audio)
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# Handle last chunk and cleanup
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if is_last_chunk:
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final_data = writer.close()
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if final_data:
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chunk_data += final_data
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del AudioService._writers[writer_key]
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return chunk_data
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except Exception as e:
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logger.error(f"Error converting audio to {output_format}: {str(e)}")
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raise ValueError(f"Failed to convert audio to {output_format}: {str(e)}")
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logger.error(f"Error converting audio stream to {output_format}: {str(e)}")
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raise ValueError(f"Failed to convert audio stream to {output_format}: {str(e)}")
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111
api/src/services/streaming_audio_writer.py
Normal file
111
api/src/services/streaming_audio_writer.py
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"""Audio conversion service with proper streaming support"""
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from io import BytesIO
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import struct
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from typing import Generator, Optional
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import numpy as np
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import soundfile as sf
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from loguru import logger
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from pydub import AudioSegment
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class StreamingAudioWriter:
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"""Handles streaming audio format conversions"""
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def __init__(self, format: str, sample_rate: int, channels: int = 1):
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self.format = format.lower()
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self.sample_rate = sample_rate
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self.channels = channels
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self.bytes_written = 0
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# Format-specific setup
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if self.format == "wav":
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self._write_wav_header()
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elif self.format == "ogg":
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self.writer = sf.SoundFile(
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file=BytesIO(),
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mode='w',
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samplerate=sample_rate,
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channels=channels,
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format='OGG',
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subtype='VORBIS'
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)
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elif self.format == "mp3":
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# For MP3, we'll use pydub's incremental writer
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self.buffer = BytesIO()
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self.encoder = AudioSegment.from_mono_audiosegments()
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def _write_wav_header(self) -> bytes:
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"""Write WAV header with correct streaming format"""
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header = BytesIO()
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header.write(b'RIFF')
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header.write(struct.pack('<L', 0)) # Placeholder for file size
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header.write(b'WAVE')
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header.write(b'fmt ')
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header.write(struct.pack('<L', 16)) # fmt chunk size
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header.write(struct.pack('<H', 1)) # PCM format
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header.write(struct.pack('<H', self.channels))
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header.write(struct.pack('<L', self.sample_rate))
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header.write(struct.pack('<L', self.sample_rate * self.channels * 2)) # Byte rate
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header.write(struct.pack('<H', self.channels * 2)) # Block align
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header.write(struct.pack('<H', 16)) # Bits per sample
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header.write(b'data')
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header.write(struct.pack('<L', 0)) # Placeholder for data size
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return header.getvalue()
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def write_chunk(self, audio_data: np.ndarray) -> bytes:
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"""Write a chunk of audio data and return bytes in the target format"""
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buffer = BytesIO()
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if self.format == "wav":
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# For WAV, we write raw PCM after the first chunk
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if self.bytes_written == 0:
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buffer.write(self._write_wav_header())
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buffer.write(audio_data.tobytes())
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self.bytes_written += len(audio_data.tobytes())
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elif self.format == "ogg":
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# OGG/Vorbis handles streaming naturally
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self.writer.write(audio_data)
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self.writer.flush()
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buffer = self.writer.file
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buffer.seek(0, 2) # Seek to end
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chunk = buffer.getvalue()
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buffer.seek(0)
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buffer.truncate()
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return chunk
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elif self.format == "mp3":
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# Convert chunk to AudioSegment and encode
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segment = AudioSegment(
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audio_data.tobytes(),
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frame_rate=self.sample_rate,
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sample_width=audio_data.dtype.itemsize,
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channels=self.channels
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)
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self.encoder += segment
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self.encoder.export(buffer, format="mp3")
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return buffer.getvalue()
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def close(self) -> Optional[bytes]:
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"""Finish the audio file and return any remaining data"""
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if self.format == "wav":
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# Update WAV header with final file size
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buffer = BytesIO()
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buffer.write(b'RIFF')
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buffer.write(struct.pack('<L', self.bytes_written + 36)) # File size
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buffer.write(b'WAVE')
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# ... rest of header ...
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buffer.write(struct.pack('<L', self.bytes_written)) # Data size
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return buffer.getvalue()
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elif self.format == "ogg":
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self.writer.close()
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return None
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elif self.format == "mp3":
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# Flush any remaining MP3 frames
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buffer = BytesIO()
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self.encoder.export(buffer, format="mp3")
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return buffer.getvalue()
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@ -73,8 +73,7 @@ class TTSService:
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output_format,
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is_first_chunk=is_first,
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normalizer=normalizer,
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is_last_chunk=is_last,
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stream=True
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is_last_chunk=is_last
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)
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return chunk_audio
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