diff --git a/api/src/builds/config.json b/api/src/builds/v0_19/config.json similarity index 100% rename from api/src/builds/config.json rename to api/src/builds/v0_19/config.json diff --git a/api/src/builds/istftnet.py b/api/src/builds/v0_19/istftnet.py similarity index 100% rename from api/src/builds/istftnet.py rename to api/src/builds/v0_19/istftnet.py diff --git a/api/src/builds/models.py b/api/src/builds/v0_19/models.py similarity index 99% rename from api/src/builds/models.py rename to api/src/builds/v0_19/models.py index 5495465..9ff82ed 100644 --- a/api/src/builds/models.py +++ b/api/src/builds/v0_19/models.py @@ -338,7 +338,7 @@ def recursive_munch(d): return d async def build_model(path, device): - from ..core.paths import load_json, load_model_weights + from api.src.core.paths import load_json, load_model_weights config = Path(__file__).parent / 'config.json' assert config.exists(), f'Config path incorrect: config.json not found at {config}' diff --git a/api/src/builds/plbert.py b/api/src/builds/v0_19/plbert.py similarity index 100% rename from api/src/builds/plbert.py rename to api/src/builds/v0_19/plbert.py diff --git a/api/src/builds/v1_0/config.json b/api/src/builds/v1_0/config.json new file mode 100644 index 0000000..14a726e --- /dev/null +++ b/api/src/builds/v1_0/config.json @@ -0,0 +1,150 @@ +{ + "istftnet": { + "upsample_kernel_sizes": [20, 12], + "upsample_rates": [10, 6], + "gen_istft_hop_size": 5, + "gen_istft_n_fft": 20, + "resblock_dilation_sizes": [ + [1, 3, 5], + [1, 3, 5], + [1, 3, 5] + ], + "resblock_kernel_sizes": [3, 7, 11], + "upsample_initial_channel": 512 + }, + "dim_in": 64, + "dropout": 0.2, + "hidden_dim": 512, + "max_conv_dim": 512, + "max_dur": 50, + "multispeaker": true, + "n_layer": 3, + "n_mels": 80, + "n_token": 178, + "style_dim": 128, + "text_encoder_kernel_size": 5, + "plbert": { + "hidden_size": 768, + "num_attention_heads": 12, + "intermediate_size": 2048, + "max_position_embeddings": 512, + "num_hidden_layers": 12, + "dropout": 0.1 + }, + "vocab": { + ";": 1, + ":": 2, + ",": 3, + ".": 4, + "!": 5, + "?": 6, + "—": 9, + "…": 10, + "\"": 11, + "(": 12, + ")": 13, + "“": 14, + "”": 15, + " ": 16, + "\u0303": 17, + "ʣ": 18, + "ʥ": 19, + "ʦ": 20, + "ʨ": 21, + "ᵝ": 22, + "\uAB67": 23, + "A": 24, + "I": 25, + "O": 31, + "Q": 33, + "S": 35, + "T": 36, + "W": 39, + "Y": 41, + "ᵊ": 42, + "a": 43, + "b": 44, + "c": 45, + "d": 46, + "e": 47, + "f": 48, + "h": 50, + "i": 51, + "j": 52, + "k": 53, + "l": 54, + "m": 55, + "n": 56, + "o": 57, + "p": 58, + "q": 59, + "r": 60, + "s": 61, + "t": 62, + "u": 63, + "v": 64, + "w": 65, + "x": 66, + "y": 67, + "z": 68, + "ɑ": 69, + "ɐ": 70, + "ɒ": 71, + "æ": 72, + "β": 75, + "ɔ": 76, + "ɕ": 77, + "ç": 78, + "ɖ": 80, + "ð": 81, + "ʤ": 82, + "ə": 83, + "ɚ": 85, + "ɛ": 86, + "ɜ": 87, + "ɟ": 90, + "ɡ": 92, + "ɥ": 99, + "ɨ": 101, + "ɪ": 102, + "ʝ": 103, + "ɯ": 110, + "ɰ": 111, + "ŋ": 112, + "ɳ": 113, + "ɲ": 114, + "ɴ": 115, + "ø": 116, + "ɸ": 118, + "θ": 119, + "œ": 120, + "ɹ": 123, + "ɾ": 125, + "ɻ": 126, + "ʁ": 128, + "ɽ": 129, + "ʂ": 130, + "ʃ": 131, + "ʈ": 132, + "ʧ": 133, + "ʊ": 135, + "ʋ": 136, + "ʌ": 138, + "ɣ": 139, + "ɤ": 140, + "χ": 142, + "ʎ": 143, + "ʒ": 147, + "ʔ": 148, + "ˈ": 156, + "ˌ": 157, + "ː": 158, + "ʰ": 162, + "ʲ": 164, + "↓": 169, + "→": 171, + "↗": 172, + "↘": 173, + "ᵻ": 177 + } +} \ No newline at end of file diff --git a/api/src/builds/v1_0/models.py b/api/src/builds/v1_0/models.py new file mode 100644 index 0000000..1315685 --- /dev/null +++ b/api/src/builds/v1_0/models.py @@ -0,0 +1,33 @@ +""" +Kokoro v1.0 model build system integration. +""" +from pathlib import Path +from typing import Optional + +from .wrapper import build_model as build_v1_model + + +async def build_model(path: Optional[str] = None, device: str = "cuda"): + """Build a Kokoro v1.0 model instance. + + This function maintains compatibility with the v0.19 build_model interface + while using the new KModel/KPipeline architecture internally. + + Args: + path: Optional path to model weights. If None, uses default location. + device: Device to load model on ("cuda" or "cpu") + + Returns: + Initialized model instance + """ + if path is None: + # Use default path in models/v1_0 + path = str(Path(__file__).parent.parent.parent / "models/v1_0/kokoro-v1_0.pth") + + # Config is always in builds/v1_0 + config_path = str(Path(__file__).parent / "config.json") + + return await build_v1_model( + config_path=config_path, + model_path=path + ) \ No newline at end of file diff --git a/api/src/builds/v1_0/wrapper.py b/api/src/builds/v1_0/wrapper.py new file mode 100644 index 0000000..0f20868 --- /dev/null +++ b/api/src/builds/v1_0/wrapper.py @@ -0,0 +1,184 @@ +from pathlib import Path +from typing import AsyncGenerator, List + +import numpy as np +import torch +from kokoro import KModel +from loguru import logger + + +class KokoroV1Wrapper: + """Wrapper for Kokoro v1.0 KModel integration. + + This wrapper provides a token-based interface compatible with the TTS service, + while internally using the Kokoro KModel for direct audio generation. It handles: + + - Token-to-phoneme conversion using the model's vocab + - Voice tensor management + - Audio generation with speed control + """ + + def __init__(self, config_path: str, model_path: str): + """Initialize KModel with config and weights. + + Args: + config_path: Path to config.json in builds/v1_0/ + model_path: Path to model weights in models/v1_0/ + """ + self.model = KModel(config=config_path, model=model_path) + self.vocab = self.model.vocab # Get vocab from model for token decoding + + async def forward(self, tokens: List[int], voice_tensor: torch.Tensor, speed: float = 1.0) -> AsyncGenerator[torch.FloatTensor, None]: + """Generate audio using KModel's forward pass. + + Args: + tokens: Input token sequence to convert to phonemes + voice_tensor: Voice embedding tensor (ref_s) containing style information + speed: Speed multiplier for audio generation + + Yields: + Single audio tensor as torch.FloatTensor + + Raises: + RuntimeError: If token-to-phoneme conversion or audio generation fails + """ + try: + # Convert tokens back to phonemes using vocab + phonemes = [] + for token in tokens: + for p, idx in self.vocab.items(): + if idx == token: + phonemes.append(p) + break + text = ''.join(phonemes) + logger.debug(f"Decoded tokens to text: '{text[:100]}...'") + + # Validate and reshape voice tensor + logger.debug(f"Initial voice tensor shape: {voice_tensor.shape}") + + # Ensure tensor has correct number of dimensions + if voice_tensor.dim() == 1: + voice_tensor = voice_tensor.unsqueeze(0) # [N] -> [1, N] + if voice_tensor.dim() == 2: + voice_tensor = voice_tensor.unsqueeze(1) # [B, N] -> [B, 1, N] + logger.debug(f"After reshape voice tensor shape: {voice_tensor.shape}") + + # Validate feature dimension + if voice_tensor.size(-1) != 256: # Expected size for style + content + raise RuntimeError(f"Voice tensor has wrong feature size: expected 256, got {voice_tensor.size(-1)}") + + # Generate audio directly using KModel + audio = self.model.forward( + phonemes=text, # text is already phonemes from token conversion + ref_s=voice_tensor, + speed=speed + ) + logger.debug(f"Generated audio tensor shape: {audio.shape}") + yield audio + + except Exception as e: + logger.error(f"Error in KokoroV1Wrapper.forward: {str(e)}") + raise RuntimeError(f"Failed to generate audio: {str(e)}") + + async def generate(self, tokens: List[int], voice_tensor: torch.Tensor, speed: float = 1.0) -> np.ndarray: + """Generate audio using KModel's forward pass. + + This method provides compatibility with the TTS service interface, + internally using forward() for generation. + + Args: + tokens: Input token sequence to convert to phonemes + voice_tensor: Voice embedding tensor (ref_s) containing style information + speed: Speed multiplier for audio generation + + Returns: + Generated audio as numpy array + + Raises: + RuntimeError: If token-to-phoneme conversion or audio generation fails + """ + try: + # Convert tokens back to phonemes using vocab + phonemes = [] + for token in tokens: + for p, idx in self.vocab.items(): + if idx == token: + phonemes.append(p) + break + text = ''.join(phonemes) + logger.debug(f"Decoded tokens to text: '{text[:100]}...'") + + # Validate and reshape voice tensor + logger.debug(f"Initial voice tensor shape: {voice_tensor.shape}") + + # Ensure tensor has correct number of dimensions + if voice_tensor.dim() == 1: + voice_tensor = voice_tensor.unsqueeze(0) # [N] -> [1, N] + if voice_tensor.dim() == 2: + voice_tensor = voice_tensor.unsqueeze(1) # [B, N] -> [B, 1, N] + logger.debug(f"After reshape voice tensor shape: {voice_tensor.shape}") + + # Validate feature dimension + if voice_tensor.size(-1) != 256: # Expected size for style + content + raise RuntimeError(f"Voice tensor has wrong feature size: expected 256, got {voice_tensor.size(-1)}") + + try: + # Generate audio directly using KModel + audio = self.model.forward( + phonemes=text, + ref_s=voice_tensor, + speed=speed + ) + logger.debug(f"Generated audio tensor shape: {audio.shape}") + except Exception as e: + raise RuntimeError(f"Model forward pass failed: {e}. Input shapes: voice={voice_tensor.shape}, text_len={len(text)}") + + # Convert to numpy if needed + if isinstance(audio, torch.Tensor): + audio = audio.cpu().numpy() + + return audio + + except Exception as e: + logger.error(f"Error in KokoroV1Wrapper.generate: {str(e)}") + raise RuntimeError(f"Failed to generate audio: {str(e)}") + + +async def build_model(config_path: str = None, model_path: str = None) -> KokoroV1Wrapper: + """Build a v1.0 model instance. + + Args: + config_path: Optional path to config.json. If None, uses default in builds/v1_0/ + model_path: Optional path to model weights. If None, uses default in models/v1_0/ + + Returns: + Initialized KokoroV1Wrapper instance + + Raises: + RuntimeError: If model initialization fails + """ + try: + if config_path is None: + config_path = str(Path(__file__).parent / "config.json") + if model_path is None: + model_path = str(Path(__file__).parent.parent.parent / "models/v1_0/kokoro-v1_0.pth") + + logger.info(f"Initializing KokoroV1Wrapper with:") + logger.info(f" Config: {config_path}") + logger.info(f" Model: {model_path}") + + if not Path(config_path).exists(): + raise RuntimeError(f"Config file not found: {config_path}") + if not Path(model_path).exists(): + raise RuntimeError(f"Model file not found: {model_path}") + + wrapper = KokoroV1Wrapper( + config_path=config_path, + model_path=model_path + ) + logger.info("Successfully initialized KokoroV1Wrapper") + return wrapper + + except Exception as e: + logger.error(f"Failed to initialize KokoroV1Wrapper: {str(e)}") + raise RuntimeError(f"Failed to initialize v1.0 model: {str(e)}") \ No newline at end of file diff --git a/api/src/core/config.py b/api/src/core/config.py index e9f67cc..02d8ba2 100644 --- a/api/src/core/config.py +++ b/api/src/core/config.py @@ -12,7 +12,7 @@ class Settings(BaseSettings): # Application Settings output_dir: str = "output" output_dir_size_limit_mb: float = 500.0 # Maximum size of output directory in MB - default_voice: str = "af" + default_voice: str = "af_aoede" # Default to v1.0 voice use_gpu: bool = True # Whether to use GPU acceleration if available use_onnx: bool = False # Whether to use ONNX runtime allow_local_voice_saving: bool = False # Whether to allow saving combined voices locally diff --git a/api/src/core/paths.py b/api/src/core/paths.py index 0c6bfff..d3a3a1a 100644 --- a/api/src/core/paths.py +++ b/api/src/core/paths.py @@ -97,8 +97,12 @@ async def get_model_path(model_name: str) -> str: # Ensure model directory exists os.makedirs(model_dir, exist_ok=True) - # Search in model directory - search_paths = [model_dir] + # Search in model directory and version subdirectories + search_paths = [ + model_dir, + os.path.join(model_dir, "v1_0"), + os.path.join(model_dir, "v0_19") + ] logger.debug(f"Searching for model in path: {model_dir}") return await _find_file(model_name, search_paths) @@ -178,8 +182,7 @@ async def load_voice_tensor(voice_path: str, device: str = "cpu") -> torch.Tenso data = await f.read() return torch.load( io.BytesIO(data), - map_location=device, - weights_only=True + map_location=device ) except Exception as e: raise RuntimeError(f"Failed to load voice tensor from {voice_path}: {e}") @@ -242,8 +245,7 @@ async def load_model_weights(path: str, device: str = "cpu") -> dict: data = await f.read() return torch.load( io.BytesIO(data), - map_location=device, - weights_only=True + map_location=device ) except Exception as e: raise RuntimeError(f"Failed to load model weights from {path}: {e}") diff --git a/api/src/inference/pytorch_backend.py b/api/src/inference/pytorch_backend.py index 4ad5095..fefe680 100644 --- a/api/src/inference/pytorch_backend.py +++ b/api/src/inference/pytorch_backend.py @@ -9,7 +9,7 @@ import numpy as np import torch from loguru import logger -from ..builds.models import build_model +from ..builds.v0_19.models import build_model from ..core import paths from ..core.model_config import model_config from ..core.config import settings diff --git a/api/src/inference/version_manager.py b/api/src/inference/version_manager.py new file mode 100644 index 0000000..342fc72 --- /dev/null +++ b/api/src/inference/version_manager.py @@ -0,0 +1,143 @@ +"""Version-aware model management.""" + +import asyncio +from pathlib import Path +from typing import Dict, Optional, Union + +import torch +from loguru import logger + +from ..builds.v0_19.models import build_model as build_v0_19 +from ..builds.v1_0.models import build_model as build_v1 +from ..core.config import settings + + +# Global singleton instance and lock for thread-safe initialization +_manager_instance = None +_manager_lock = asyncio.Lock() + + +class VersionManager: + """Manages different versions of Kokoro models.""" + + def __init__(self): + """Initialize version manager.""" + self.models: Dict[str, Union[dict, object]] = {} + self._version_locks: Dict[str, asyncio.Lock] = { + "v0.19": asyncio.Lock(), + "v1.0": asyncio.Lock() + } + self._current_version = "v1.0" # Default to v1.0 with af_bella voice + + async def get_model(self, version: Optional[str] = None) -> object: + """Get model for specified version. + + Args: + version: Model version ("v0.19" or "v1.0"). Uses default if None. + + Returns: + Model instance + + Raises: + ValueError: If version is invalid + RuntimeError: If model loading fails + """ + if version is None: + version = self._current_version + + if version not in self._version_locks: + raise ValueError( + f"Invalid version: {version}. " + f"Available versions: {', '.join(self._version_locks.keys())}" + ) + + # Fast path - return existing model + if version in self.models and self.models[version] is not None: + return self.models[version] + + # Slow path - load model with lock + async with self._version_locks[version]: + # Double-check pattern + if version not in self.models or self.models[version] is None: + try: + if version == "v0.19": + # Use existing model path logic for v0.19 + from ..core.model_config import model_config + model_file = (model_config.onnx_model_file + if settings.use_onnx + else model_config.pytorch_model_file) + from ..core.paths import get_model_path + model_path = await get_model_path(model_file) + self.models[version] = await build_v0_19( + path=model_path, + device="cuda" if settings.use_gpu else "cpu" + ) + else: # v1.0 + # Use paths module for v1.0 model loading + from ..core.paths import get_model_path + model_path = await get_model_path("kokoro-v1_0.pth") + self.models[version] = await build_v1( + path=model_path, + device="cuda" if settings.use_gpu else "cpu" + ) + logger.info(f"Loaded {version} model") + except Exception as e: + logger.error(f"Failed to load {version} model: {e}") + raise RuntimeError(f"Failed to load {version} model: {e}") + + return self.models[version] + + def set_default_version(self, version: str) -> None: + """Set default model version. + + Args: + version: Version to set as default ("v0.19" or "v1.0") + + Raises: + ValueError: If version is invalid + """ + if version not in self._version_locks: + raise ValueError( + f"Invalid version: {version}. " + f"Available versions: {', '.join(self._version_locks.keys())}" + ) + self._current_version = version + logger.info(f"Set default version to {version}") + + @property + def current_version(self) -> str: + """Get current default version.""" + return self._current_version + + @property + def available_versions(self) -> list[str]: + """Get list of available versions.""" + return list(self._version_locks.keys()) + + def unload_all(self) -> None: + """Unload all model versions.""" + self.models.clear() + logger.info("Unloaded all model versions") + + +async def get_version_manager() -> VersionManager: + """Get global version manager instance. + + Returns: + VersionManager instance + + Thread Safety: + This function is thread-safe + """ + global _manager_instance + + # Fast path - return existing instance + if _manager_instance is not None: + return _manager_instance + + # Slow path - create new instance with lock + async with _manager_lock: + # Double-check pattern + if _manager_instance is None: + _manager_instance = VersionManager() + return _manager_instance \ No newline at end of file diff --git a/api/src/inference/voice_manager.py b/api/src/inference/voice_manager.py index 56557e6..6a70b50 100644 --- a/api/src/inference/voice_manager.py +++ b/api/src/inference/voice_manager.py @@ -23,20 +23,33 @@ class VoiceManager: self._config = config or VoiceConfig() self._voice_cache: Dict[str, torch.Tensor] = {} - def get_voice_path(self, voice_name: str) -> Optional[str]: + def get_voice_path(self, voice_name: str, version: Optional[str] = None) -> Optional[str]: """Get path to voice file. Args: voice_name: Name of voice + version: Optional version to filter by ("v0.19" or "v1.0") Returns: Path to voice file if exists, None otherwise """ api_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__))) - voice_path = os.path.join(api_dir, settings.voices_dir, f"{voice_name}.pt") - return voice_path if os.path.exists(voice_path) else None + + if version == "v1.0" or version is None: + # Check v1.0 voices + voice_path = os.path.join(api_dir, settings.voices_dir, "v1_0", f"{voice_name}.pt") + if os.path.exists(voice_path): + return voice_path + + if version == "v0.19" or version is None: + # Check v0.19 voices + voice_path = os.path.join(api_dir, settings.voices_dir, "v0_19", f"{voice_name}.pt") + if os.path.exists(voice_path): + return voice_path + + return None - async def load_voice(self, voice_name: str, device: str = "cpu") -> torch.Tensor: + async def load_voice(self, voice_name: str, device: str = "cpu", version: Optional[str] = None) -> torch.Tensor: """Load voice tensor. Args: @@ -64,12 +77,35 @@ class VoiceManager: except Exception as e: raise RuntimeError(f"Failed to load base voice {voice}: {e}") - return torch.mean(torch.stack(voice_tensors), dim=0) + # Find maximum size + max_size = max(tensor.size(0) for tensor in voice_tensors) + + # Pad tensors to match size + padded_tensors = [] + for tensor in voice_tensors: + if tensor.size(0) < max_size: + padding = torch.zeros(max_size - tensor.size(0), *tensor.size()[1:], device=tensor.device) + padded_tensor = torch.cat([tensor, padding], dim=0) + padded_tensors.append(padded_tensor) + else: + padded_tensors.append(tensor) + + # Stack and average + combined = torch.mean(torch.stack(padded_tensors), dim=0) + + # For v1.0, attach combined voice ID + if version == "v1.0" or (version is None and any("v1_0" in str(t.voice_id) if hasattr(t, 'voice_id') else False for t in voice_tensors)): + combined.voice_id = voice_name + + return combined - # Handle single voice - voice_path = self.get_voice_path(voice_name) + # Handle single voice with version + voice_path = self.get_voice_path(voice_name, version) if not voice_path: - raise RuntimeError(f"Voice not found: {voice_name}") + available_voices = await self.list_voices(version) + raise RuntimeError( + f"Voice not found: {voice_name}. Available voices for version {version or 'any'}: {', '.join(sorted(available_voices))}" + ) # Check cache cache_key = f"{voice_path}_{device}" @@ -79,6 +115,9 @@ class VoiceManager: # Load voice tensor try: voice = await paths.load_voice_tensor(voice_path, device=device) + # Attach voice name as attribute for v1.0 models + if version == "v1.0" or (version is None and "v1_0" in voice_path): + voice.voice_id = voice_name except Exception as e: raise RuntimeError(f"Failed to load voice {voice_name}: {e}") @@ -99,7 +138,7 @@ class VoiceManager: torch.cuda.empty_cache() # Clean up GPU memory if needed logger.debug(f"Removed LRU voice from cache: {oldest}") - async def combine_voices(self, voices: List[str], device: str = "cpu") -> str: + async def combine_voices(self, voices: List[str], device: str = "cpu", version: Optional[str] = None) -> str: """Combine multiple voices into a new voice. Args: @@ -125,11 +164,20 @@ class VoiceManager: # Load and combine voices combined_tensor = await self.load_voice(combined_name, device) - # Save to disk + # Save to disk in version-specific directory api_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__))) - voices_dir = os.path.join(api_dir, settings.voices_dir) - os.makedirs(voices_dir, exist_ok=True) + base_voices_dir = os.path.join(api_dir, settings.voices_dir) + # Determine version directory + if version == "v1.0": + voices_dir = os.path.join(base_voices_dir, "v1_0") + elif version == "v0.19": + voices_dir = os.path.join(base_voices_dir, "v0_19") + else: + # Default to v1.0 if no version specified + voices_dir = os.path.join(base_voices_dir, "v1_0") + + os.makedirs(voices_dir, exist_ok=True) combined_path = os.path.join(voices_dir, f"{combined_name}.pt") try: torch.save(combined_tensor, combined_path) @@ -144,22 +192,35 @@ class VoiceManager: return combined_name - async def list_voices(self) -> List[str]: + async def list_voices(self, version: Optional[str] = None) -> List[str]: """List available voices. + Args: + version: Optional version to filter by ("v0.19" or "v1.0") + Returns: List of voice names """ voices = set() # Use set to avoid duplicates try: - # Get voices from disk api_dir = os.path.dirname(os.path.dirname(os.path.dirname(__file__))) - voices_dir = os.path.join(api_dir, settings.voices_dir) - os.makedirs(voices_dir, exist_ok=True) + base_voices_dir = os.path.join(api_dir, settings.voices_dir) - for entry in os.listdir(voices_dir): - if entry.endswith(".pt"): - voices.add(entry[:-3]) + if version == "v1.0" or version is None: + # Check v1.0 voices + v1_voices_dir = os.path.join(base_voices_dir, "v1_0") + os.makedirs(v1_voices_dir, exist_ok=True) + for entry in os.listdir(v1_voices_dir): + if entry.endswith(".pt"): + voices.add(entry[:-3]) + + if version == "v0.19" or version is None: + # Check v0.19 voices + v0_voices_dir = os.path.join(base_voices_dir, "v0_19") + os.makedirs(v0_voices_dir, exist_ok=True) + for entry in os.listdir(v0_voices_dir): + if entry.endswith(".pt"): + voices.add(entry[:-3]) except Exception as e: logger.error(f"Error listing voices: {e}") diff --git a/api/src/main.py b/api/src/main.py index 5932020..2de9fdf 100644 --- a/api/src/main.py +++ b/api/src/main.py @@ -17,6 +17,7 @@ from .core.config import settings from .routers.web_player import router as web_router from .routers.development import router as dev_router from .routers.openai_compatible import router as openai_router +from .routers.openai_compatible_v2 import router as openai_router_v2 from .routers.debug import router as debug_router @@ -46,6 +47,7 @@ setup_logger() async def lifespan(app: FastAPI): """Lifespan context manager for model initialization""" from .inference.model_manager import get_manager + from .inference.version_manager import get_version_manager from .inference.voice_manager import get_manager as get_voice_manager from .services.temp_manager import cleanup_temp_files @@ -56,11 +58,17 @@ async def lifespan(app: FastAPI): try: # Initialize managers globally - model_manager = await get_manager() + model_manager = await get_manager() # For v0.19 compatibility + version_manager = await get_version_manager() # For v1.0 support voice_manager = await get_voice_manager() - # Initialize model with warmup and get status + # Initialize v0.19 model with warmup and get status device, model, voicepack_count = await model_manager.initialize_with_warmup(voice_manager) + + # Pre-load v1.0 model + v1_model = await version_manager.get_model("v1.0") + logger.info("Initialized v1.0 model") + except FileNotFoundError: logger.error(""" Model files not found! You need to either: @@ -94,6 +102,7 @@ Model files not found! You need to either: """ startup_msg += f"\nModel warmed up on {device}: {model}" startup_msg += f"\n{voicepack_count} voice packs loaded" + startup_msg += f"\nKokoro v1.0 model loaded" # Add web player info if enabled if settings.enable_web_player: @@ -127,7 +136,8 @@ if settings.cors_enabled: ) # Include routers -app.include_router(openai_router, prefix="/v1") +app.include_router(openai_router, prefix="/v1") # Legacy v0.19 endpoints +app.include_router(openai_router_v2) # New v2 endpoints with version support app.include_router(dev_router) # Development endpoints app.include_router(debug_router) # Debug endpoints if settings.enable_web_player: diff --git a/api/src/routers/openai_compatible_v2.py b/api/src/routers/openai_compatible_v2.py new file mode 100644 index 0000000..b863625 --- /dev/null +++ b/api/src/routers/openai_compatible_v2.py @@ -0,0 +1,395 @@ +"""OpenAI-compatible router with version support""" + +import json +import os +from typing import AsyncGenerator, Dict, List, Optional, Union + +from fastapi import APIRouter, Depends, Header, HTTPException, Request, Response +from fastapi.responses import StreamingResponse, FileResponse +from loguru import logger +from pydantic import BaseModel + +from ..services.audio import AudioService +from ..services.tts_service_v2 import TTSService +from ..structures.schemas import OpenAISpeechRequest +from ..core.config import settings + + +class OpenAISpeechRequestV2(OpenAISpeechRequest): + """Extended OpenAI speech request with version support.""" + version: Optional[str] = None # "v0.19" or "v1.0" + + +def load_openai_mappings() -> Dict: + """Load OpenAI voice and model mappings from JSON""" + api_dir = os.path.dirname(os.path.dirname(__file__)) + mapping_path = os.path.join(api_dir, "core", "openai_mappings.json") + try: + with open(mapping_path, 'r') as f: + return json.load(f) + except Exception as e: + logger.error(f"Failed to load OpenAI mappings: {e}") + return {"models": {}, "voices": {}} + + +# Global mappings +_openai_mappings = load_openai_mappings() + + +router = APIRouter( + tags=["OpenAI Compatible TTS V2"], + responses={404: {"description": "Not found"}}, +) + +# Global TTSService instance with lock +_tts_service = None +_init_lock = None + + +async def get_tts_service() -> TTSService: + """Get global TTSService instance""" + global _tts_service, _init_lock + + if _init_lock is None: + import asyncio + _init_lock = asyncio.Lock() + + if _tts_service is None: + async with _init_lock: + if _tts_service is None: + _tts_service = await TTSService.create() + logger.info("Created global TTSService V2 instance") + + return _tts_service + + +async def process_voices( + voice_input: Union[str, List[str]], + tts_service: TTSService, + version: Optional[str] = None +) -> str: + """Process voice input into a combined voice, handling both string and list formats""" + if isinstance(voice_input, str): + mapped_voice = _openai_mappings["voices"].get(voice_input) + if mapped_voice: + voice_input = mapped_voice + voices = [v.strip() for v in voice_input.split("+") if v.strip()] + else: + voices = [_openai_mappings["voices"].get(v, v) for v in voice_input] + voices = [v.strip() for v in voices if v.strip()] + + if not voices: + raise ValueError("No voices provided") + + if len(voices) == 1: + available_voices = await tts_service.list_voices(version) + if voices[0] not in available_voices: + raise ValueError( + f"Voice '{voices[0]}' not found for version {version or 'any'}. " + f"Available voices: {', '.join(sorted(available_voices))}" + ) + return voices[0] + + # For voice combinations, validate all voices exist for the specified version + available_voices = await tts_service.list_voices(version) + for voice in voices: + if voice not in available_voices: + raise ValueError( + f"Base voice '{voice}' not found for version {version or 'any'}. " + f"Available voices: {', '.join(sorted(available_voices))}" + ) + + return await tts_service.combine_voices(voices=voices, version=version) + + +async def stream_audio_chunks( + tts_service: TTSService, + request: OpenAISpeechRequestV2, + client_request: Request +) -> AsyncGenerator[bytes, None]: + """Stream audio chunks as they're generated with client disconnect handling""" + voice_to_use = await process_voices(request.voice, tts_service, request.version) + + try: + async for chunk in tts_service.generate_audio_stream( + text=request.input, + voice=voice_to_use, + speed=request.speed, + version=request.version, + output_format=request.response_format, + ): + is_disconnected = client_request.is_disconnected + if callable(is_disconnected): + is_disconnected = await is_disconnected() + if is_disconnected: + logger.info("Client disconnected, stopping audio generation") + break + yield chunk + except Exception as e: + logger.error(f"Error in audio streaming: {str(e)}") + raise + + +@router.post("/v2/audio/speech") +async def create_speech( + request: OpenAISpeechRequestV2, + client_request: Request, + x_raw_response: str = Header(None, alias="x-raw-response"), +): + """OpenAI-compatible endpoint for text-to-speech with version support""" + if request.model not in _openai_mappings["models"]: + raise HTTPException( + status_code=400, + detail={ + "error": "invalid_model", + "message": f"Unsupported model: {request.model}", + "type": "invalid_request_error" + } + ) + + try: + tts_service = await get_tts_service() + voice_to_use = await process_voices(request.voice, tts_service, request.version) + + content_type = { + "mp3": "audio/mpeg", + "opus": "audio/opus", + "aac": "audio/aac", + "flac": "audio/flac", + "wav": "audio/wav", + "pcm": "audio/pcm", + }.get(request.response_format, f"audio/{request.response_format}") + + if request.stream: + generator = stream_audio_chunks(tts_service, request, client_request) + + if request.return_download_link: + from ..services.temp_manager import TempFileWriter + + temp_writer = TempFileWriter(request.response_format) + await temp_writer.__aenter__() + + download_path = temp_writer.download_path + + headers = { + "Content-Disposition": f"attachment; filename=speech.{request.response_format}", + "X-Accel-Buffering": "no", + "Cache-Control": "no-cache", + "Transfer-Encoding": "chunked", + "X-Download-Path": download_path + } + + async def dual_output(): + try: + async for chunk in generator: + if chunk: + await temp_writer.write(chunk) + yield chunk + + await temp_writer.finalize() + except Exception as e: + logger.error(f"Error in dual output streaming: {e}") + await temp_writer.__aexit__(type(e), e, e.__traceback__) + raise + finally: + if not temp_writer._finalized: + await temp_writer.__aexit__(None, None, None) + + return StreamingResponse( + dual_output(), + media_type=content_type, + headers=headers + ) + + return StreamingResponse( + generator, + media_type=content_type, + headers={ + "Content-Disposition": f"attachment; filename=speech.{request.response_format}", + "X-Accel-Buffering": "no", + "Cache-Control": "no-cache", + "Transfer-Encoding": "chunked" + } + ) + else: + audio, _ = await tts_service.generate_audio( + text=request.input, + voice=voice_to_use, + speed=request.speed, + version=request.version + ) + + content = await AudioService.convert_audio( + audio, 24000, request.response_format, + is_first_chunk=True, + is_last_chunk=True + ) + + return Response( + content=content, + media_type=content_type, + headers={ + "Content-Disposition": f"attachment; filename=speech.{request.response_format}", + "Cache-Control": "no-cache", + }, + ) + + except ValueError as e: + logger.warning(f"Invalid request: {str(e)}") + raise HTTPException( + status_code=400, + detail={ + "error": "validation_error", + "message": str(e), + "type": "invalid_request_error" + } + ) + except RuntimeError as e: + logger.error(f"Processing error: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "processing_error", + "message": str(e), + "type": "server_error" + } + ) + except Exception as e: + logger.error(f"Unexpected error in speech generation: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "processing_error", + "message": str(e), + "type": "server_error" + } + ) + + +@router.get("/v2/audio/versions") +async def list_versions(): + """List available model versions""" + try: + tts_service = await get_tts_service() + return { + "versions": tts_service.available_versions, + "current": tts_service.current_version + } + except Exception as e: + logger.error(f"Error listing versions: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "server_error", + "message": "Failed to retrieve version list", + "type": "server_error" + } + ) + + +@router.post("/v2/audio/version") +async def set_version(version: str): + """Set default model version""" + try: + tts_service = await get_tts_service() + tts_service.set_version(version) + return { + "message": f"Set default version to {version}", + "versions": tts_service.available_versions, + "current": tts_service.current_version + } + except ValueError as e: + raise HTTPException( + status_code=400, + detail={ + "error": "validation_error", + "message": str(e), + "type": "invalid_request_error" + } + ) + except Exception as e: + logger.error(f"Error setting version: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "server_error", + "message": "Failed to set version", + "type": "server_error" + } + ) + + +@router.get("/v2/audio/voices") +async def list_voices(version: Optional[str] = None): + """List all available voices for text-to-speech. + + Args: + version: Optional version to filter voices by ("v0.19" or "v1.0") + """ + try: + tts_service = await get_tts_service() + voices = await tts_service.list_voices(version) + return { + "voices": voices, + "version": version or tts_service.current_version + } + except Exception as e: + logger.error(f"Error listing voices: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "server_error", + "message": "Failed to retrieve voice list", + "type": "server_error" + } + ) + + +@router.post("/v2/audio/voices/combine") +async def combine_voices(request: Union[str, List[str]], version: Optional[str] = None): + """Combine multiple voices into a new voice. + + Args: + request: Either a string with voices separated by + or a list of voice names + version: Optional version to filter voices by ("v0.19" or "v1.0") + """ + try: + tts_service = await get_tts_service() + combined_voice = await process_voices(request, tts_service, version) + voices = await tts_service.list_voices(version) + return { + "voices": voices, + "voice": combined_voice, + "version": version or tts_service.current_version + } + + except ValueError as e: + logger.warning(f"Invalid voice combination request: {str(e)}") + raise HTTPException( + status_code=400, + detail={ + "error": "validation_error", + "message": str(e), + "type": "invalid_request_error" + } + ) + except RuntimeError as e: + logger.error(f"Voice combination processing error: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "processing_error", + "message": "Failed to process voice combination request", + "type": "server_error" + } + ) + except Exception as e: + logger.error(f"Unexpected error in voice combination: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "error": "server_error", + "message": "An unexpected error occurred", + "type": "server_error" + } + ) \ No newline at end of file diff --git a/api/src/services/tts_service_v2.py b/api/src/services/tts_service_v2.py new file mode 100644 index 0000000..4644122 --- /dev/null +++ b/api/src/services/tts_service_v2.py @@ -0,0 +1,294 @@ +"""TTS service with version support.""" + +import time +from typing import List, Tuple, Optional, AsyncGenerator, Union + +import numpy as np +import torch +from loguru import logger + +from ..core.config import settings +from ..inference.version_manager import get_version_manager +from ..inference.voice_manager import get_manager as get_voice_manager +from .audio import AudioNormalizer, AudioService +from .text_processing.text_processor import process_text_chunk, smart_split +from .text_processing import tokenize + + +class TTSService: + """Text-to-speech service with version support.""" + + def __init__(self, output_dir: str = None): + """Initialize service.""" + self.output_dir = output_dir + self.version_manager = None + self._voice_manager = None + + @classmethod + async def create(cls, output_dir: str = None) -> 'TTSService': + """Create and initialize TTSService instance.""" + service = cls(output_dir) + service.version_manager = await get_version_manager() + service._voice_manager = await get_voice_manager() + return service + + async def _process_chunk( + self, + tokens: List[int], + voice_tensor: torch.Tensor, + speed: float, + version: Optional[str] = None, + output_format: Optional[str] = None, + is_first: bool = False, + is_last: bool = False, + normalizer: Optional[AudioNormalizer] = None, + ) -> AsyncGenerator[Union[np.ndarray, bytes], None]: + """Process tokens into audio.""" + try: + # Handle stream finalization + if is_last: + if not output_format: + yield np.array([], dtype=np.float32) + return + + final_chunk = await AudioService.convert_audio( + np.array([0], dtype=np.float32), + 24000, + output_format, + is_first_chunk=False, + normalizer=normalizer, + is_last_chunk=True + ) + if final_chunk is not None: + yield final_chunk + return + + # Skip empty chunks + if not tokens: + return + + # Get model for specified version + model = await self.version_manager.get_model(version) + + if version == "v1.0": + # For v1.0, we need to handle the generator + try: + # Split long sequences to avoid index out of bounds + max_length = 500 # v1.0 model context limit + if len(tokens) > max_length: + logger.warning(f"Truncating sequence from {len(tokens)} to {max_length} tokens") + tokens = tokens[:max_length] + + # Process all chunks from the generator + async for audio in model.forward(tokens, voice_tensor, speed=speed): + if audio is None: + continue + + # Convert tensor to numpy if needed + if isinstance(audio, torch.Tensor): + audio = audio.cpu().numpy() + + # Convert audio if needed + if output_format: + converted = await AudioService.convert_audio( + audio, + 24000, + output_format, + is_first_chunk=is_first, + normalizer=normalizer, + is_last_chunk=is_last + ) + if converted is not None: + yield converted + else: + yield audio + except Exception as e: + logger.error(f"Generation failed: {str(e)}") + return + else: + # For v0.19, use existing generate method + audio = await model.generate(tokens, voice_tensor, speed=speed) + + if audio is None: + logger.error("Model generated None for audio chunk") + return + + if len(audio) == 0: + logger.error("Model generated empty audio chunk") + return + + # Convert audio if needed + if output_format: + try: + converted = await AudioService.convert_audio( + audio, + 24000, + output_format, + is_first_chunk=is_first, + normalizer=normalizer, + is_last_chunk=is_last + ) + if converted is not None: + yield converted + except Exception as e: + logger.error(f"Failed to convert audio: {str(e)}") + return + else: + yield audio + + except Exception as e: + logger.error(f"Failed to process tokens: {str(e)}") + return + + async def generate_audio_stream( + self, + text: str, + voice: str, + speed: float = 1.0, + version: Optional[str] = None, + output_format: str = "wav", + ) -> AsyncGenerator[bytes, None]: + """Generate and stream audio chunks.""" + stream_normalizer = AudioNormalizer() + voice_tensor = None + chunk_index = 0 + + try: + # Get model and load voice + model = await self.version_manager.get_model(version) + device = "cuda" if settings.use_gpu else "cpu" + voice_tensor = await self._voice_manager.load_voice(voice, device=device, version=version) + + # Process text in chunks with smart splitting + async for chunk_text, tokens in smart_split(text): + try: + # Process audio for chunk + async for result in self._process_chunk( + tokens, + voice_tensor, + speed, + version=version, + output_format=output_format, + is_first=(chunk_index == 0), + is_last=False, + normalizer=stream_normalizer + ): + if result is not None: + yield result + chunk_index += 1 + + except Exception as e: + logger.error(f"Failed to process audio for chunk: '{chunk_text[:100]}...'. Error: {str(e)}") + continue + + # Only finalize if we successfully processed at least one chunk + if chunk_index > 0: + try: + async for final_result in self._process_chunk( + [], + voice_tensor, + speed, + version=version, + output_format=output_format, + is_first=False, + is_last=True, + normalizer=stream_normalizer + ): + if final_result is not None: + logger.debug("Yielding final chunk to finalize audio") + yield final_result + except Exception as e: + logger.error(f"Failed to process final chunk: {str(e)}") + else: + logger.warning("No audio chunks were successfully processed") + + except Exception as e: + logger.error(f"Error in audio generation stream: {str(e)}") + raise + finally: + if voice_tensor is not None: + del voice_tensor + torch.cuda.empty_cache() + + async def generate_audio( + self, + text: str, + voice: str, + speed: float = 1.0, + version: Optional[str] = None, + ) -> Tuple[np.ndarray, float]: + """Generate complete audio for text using streaming internally.""" + start_time = time.time() + chunks = [] + voice_tensor = None + + try: + # Get model and load voice + model = await self.version_manager.get_model(version) + device = "cuda" if settings.use_gpu else "cpu" + voice_tensor = await self._voice_manager.load_voice(voice, device=device, version=version) + + if version == "v1.0": + # For v1.0, use streaming internally + async for chunk in self.generate_audio_stream( + text, voice, speed, version, output_format=None + ): + if chunk is not None and isinstance(chunk, np.ndarray): + chunks.append(chunk) + else: + # For v0.19, use direct generation + async for chunk_text, tokens in smart_split(text): + try: + audio = await model.generate(tokens, voice_tensor, speed=speed) + if audio is not None: + chunks.append(audio) + except Exception as e: + logger.error(f"Failed to generate audio for chunk: '{chunk_text[:100]}...'. Error: {str(e)}") + continue + + if not chunks: + raise ValueError("No audio chunks were generated successfully") + + # Concatenate chunks + audio = np.concatenate(chunks) if len(chunks) > 1 else chunks[0] + processing_time = time.time() - start_time + return audio, processing_time + + except Exception as e: + logger.error(f"Error in audio generation: {str(e)}") + raise + finally: + if voice_tensor is not None: + del voice_tensor + torch.cuda.empty_cache() + + async def combine_voices(self, voices: List[str], version: Optional[str] = None) -> str: + """Combine multiple voices. + + Args: + voices: List of voice names to combine + version: Optional version to filter voices by + """ + return await self._voice_manager.combine_voices(voices, version=version) + + async def list_voices(self, version: Optional[str] = None) -> List[str]: + """List available voices. + + Args: + version: Optional version to filter voices by + """ + return await self._voice_manager.list_voices(version) + + def set_version(self, version: str) -> None: + """Set default model version.""" + self.version_manager.set_default_version(version) + + @property + def current_version(self) -> str: + """Get current model version.""" + return self.version_manager.current_version + + @property + def available_versions(self) -> List[str]: + """Get list of available model versions.""" + return self.version_manager.available_versions \ No newline at end of file diff --git a/api/src/voices/af.pt b/api/src/voices/v0_19/af.pt similarity index 100% rename from api/src/voices/af.pt rename to api/src/voices/v0_19/af.pt diff --git a/api/src/voices/af_bella.pt b/api/src/voices/v0_19/af_bella.pt similarity index 100% rename from api/src/voices/af_bella.pt rename to api/src/voices/v0_19/af_bella.pt diff --git a/api/src/voices/af_irulan.pt b/api/src/voices/v0_19/af_irulan.pt similarity index 100% rename from api/src/voices/af_irulan.pt rename to api/src/voices/v0_19/af_irulan.pt diff --git 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b/api/src/voices/v1_0/zm_yunxia.pt new file mode 100644 index 0000000..4aa15ae Binary files /dev/null and b/api/src/voices/v1_0/zm_yunxia.pt differ diff --git a/api/src/voices/v1_0/zm_yunyang.pt b/api/src/voices/v1_0/zm_yunyang.pt new file mode 100644 index 0000000..4c44a0d Binary files /dev/null and b/api/src/voices/v1_0/zm_yunyang.pt differ diff --git a/api/tests/test_openai_endpoints_v2.py b/api/tests/test_openai_endpoints_v2.py new file mode 100644 index 0000000..b0279b5 --- /dev/null +++ b/api/tests/test_openai_endpoints_v2.py @@ -0,0 +1,229 @@ +"""Tests for OpenAI-compatible v2 endpoints.""" + +import pytest +from fastapi.testclient import TestClient +from loguru import logger + +from ..main import app + + +@pytest.fixture +def client(): + """Test client fixture.""" + return TestClient(app) + + +def test_health_check(client): + """Test health check endpoint.""" + response = client.get("/health") + assert response.status_code == 200 + assert response.json() == {"status": "healthy"} + + +def test_list_versions(client): + """Test version listing endpoint.""" + response = client.get("/v2/audio/versions") + assert response.status_code == 200 + data = response.json() + assert "versions" in data + assert "current" in data + assert "v0.19" in data["versions"] + assert "v1.0" in data["versions"] + + +def test_set_version(client): + """Test version setting endpoint.""" + # Set to v1.0 + response = client.post("/v2/audio/version", json="v1.0") + assert response.status_code == 200 + data = response.json() + assert data["current"] == "v1.0" + + # Set back to v0.19 + response = client.post("/v2/audio/version", json="v0.19") + assert response.status_code == 200 + data = response.json() + assert data["current"] == "v0.19" + + # Test invalid version + response = client.post("/v2/audio/version", json="invalid_version") + assert response.status_code == 400 + + +def test_list_voices(client): + """Test voice listing endpoint.""" + response = client.get("/v2/audio/voices") + assert response.status_code == 200 + data = response.json() + assert "voices" in data + assert len(data["voices"]) > 0 + + +def test_combine_voices(client): + """Test voice combination endpoint.""" + # Test with string input + response = client.post("/v2/audio/voices/combine", json="af_bella+af_nicole") + assert response.status_code == 200 + data = response.json() + assert "voice" in data + assert "voices" in data + + # Test with list input + response = client.post("/v2/audio/voices/combine", json=["af_bella", "af_nicole"]) + assert response.status_code == 200 + data = response.json() + assert "voice" in data + assert "voices" in data + + +def test_speech_generation_v0_19(client): + """Test speech generation with v0.19.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "speed": 1.0, + "stream": False, + "version": "v0.19" + } + + response = client.post("/v2/audio/speech", json=request_data) + assert response.status_code == 200 + assert response.headers["content-type"] == "audio/wav" + assert len(response.content) > 0 + + +def test_speech_generation_v1_0(client): + """Test speech generation with v1.0.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "speed": 1.0, + "stream": False, + "version": "v1.0" + } + + response = client.post("/v2/audio/speech", json=request_data) + assert response.status_code == 200 + assert response.headers["content-type"] == "audio/wav" + assert len(response.content) > 0 + + +def test_streaming_speech_v0_19(client): + """Test streaming speech generation with v0.19.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "speed": 1.0, + "stream": True, + "version": "v0.19" + } + + with client.stream("POST", "/v2/audio/speech", json=request_data) as response: + assert response.status_code == 200 + content = b"" + for chunk in response.iter_bytes(): + assert len(chunk) > 0 + content += chunk + assert len(content) > 0 + + +def test_streaming_speech_v1_0(client): + """Test streaming speech generation with v1.0.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "speed": 1.0, + "stream": True, + "version": "v1.0" + } + + with client.stream("POST", "/v2/audio/speech", json=request_data) as response: + assert response.status_code == 200 + content = b"" + for chunk in response.iter_bytes(): + assert len(chunk) > 0 + content += chunk + assert len(content) > 0 + + +def test_invalid_model(client): + """Test invalid model handling.""" + request_data = { + "model": "invalid-model", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "version": "v1.0" + } + + response = client.post("/v2/audio/speech", json=request_data) + assert response.status_code == 400 + data = response.json() + assert "error" in data + assert data["error"] == "invalid_model" + + +def test_invalid_voice(client): + """Test invalid voice handling.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "invalid_voice", + "response_format": "wav", + "version": "v1.0" + } + + response = client.post("/v2/audio/speech", json=request_data) + assert response.status_code == 400 + data = response.json() + assert "error" in data + assert data["error"] == "validation_error" + + +def test_invalid_version(client): + """Test invalid version handling.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "version": "invalid_version" + } + + response = client.post("/v2/audio/speech", json=request_data) + assert response.status_code == 400 + data = response.json() + assert "error" in data + assert data["error"] == "validation_error" + + +def test_download_link(client): + """Test download link functionality.""" + request_data = { + "model": "tts-1", + "input": "Hello, world!", + "voice": "af_bella", + "response_format": "wav", + "speed": 1.0, + "stream": True, + "return_download_link": True, + "version": "v1.0" + } + + with client.stream("POST", "/v2/audio/speech", json=request_data) as response: + assert response.status_code == 200 + assert "X-Download-Path" in response.headers + download_path = response.headers["X-Download-Path"] + + # Try downloading the file + download_response = client.get(f"/download/{download_path}") + assert download_response.status_code == 200 + assert len(download_response.content) > 0 \ No newline at end of file diff --git a/api/tests/test_tts_service_v2.py b/api/tests/test_tts_service_v2.py new file mode 100644 index 0000000..7f83d08 --- /dev/null +++ b/api/tests/test_tts_service_v2.py @@ -0,0 +1,207 @@ +"""Tests for TTSService v2 with version support.""" + +import numpy as np +import pytest +from loguru import logger + +from ..services.tts_service_v2 import TTSService + + +@pytest.fixture +async def tts_service(): + """Fixture for TTSService instance.""" + service = await TTSService.create() + yield service + + +@pytest.mark.asyncio +async def test_service_initialization(tts_service): + """Test TTSService initialization.""" + assert tts_service is not None + assert tts_service.version_manager is not None + assert tts_service._voice_manager is not None + + +@pytest.mark.asyncio +async def test_version_selection(tts_service): + """Test version selection in TTSService.""" + # Default version should be v0.19 + assert tts_service.current_version == "v0.19" + + # Change version + tts_service.set_version("v1.0") + assert tts_service.current_version == "v1.0" + + # List available versions + versions = tts_service.available_versions + assert "v0.19" in versions + assert "v1.0" in versions + + +@pytest.mark.asyncio +async def test_audio_generation_v0_19(tts_service): + """Test audio generation with v0.19.""" + text = "Hello, world!" + voice = "af_bella" # Use a known test voice + + # Set version explicitly + tts_service.set_version("v0.19") + + # Generate audio + audio, processing_time = await tts_service.generate_audio( + text=text, + voice=voice, + speed=1.0, + version="v0.19" + ) + + assert isinstance(audio, np.ndarray) + assert len(audio) > 0 + assert processing_time > 0 + + +@pytest.mark.asyncio +async def test_audio_generation_v1_0(tts_service): + """Test audio generation with v1.0.""" + text = "Hello, world!" + voice = "af_bella" # Use a known test voice + + # Set version explicitly + tts_service.set_version("v1.0") + + # Generate audio + audio, processing_time = await tts_service.generate_audio( + text=text, + voice=voice, + speed=1.0, + version="v1.0" + ) + + assert isinstance(audio, np.ndarray) + assert len(audio) > 0 + assert processing_time > 0 + + +@pytest.mark.asyncio +async def test_streaming_v0_19(tts_service): + """Test audio streaming with v0.19.""" + text = "Hello, world!" + voice = "af_bella" + chunks = [] + + async for chunk in tts_service.generate_audio_stream( + text=text, + voice=voice, + speed=1.0, + version="v0.19", + output_format="wav" + ): + assert chunk is not None + assert len(chunk) > 0 + chunks.append(chunk) + + assert len(chunks) > 0 + + +@pytest.mark.asyncio +async def test_streaming_v1_0(tts_service): + """Test audio streaming with v1.0.""" + text = "Hello, world!" + voice = "af_bella" + chunks = [] + + async for chunk in tts_service.generate_audio_stream( + text=text, + voice=voice, + speed=1.0, + version="v1.0", + output_format="wav" + ): + assert chunk is not None + assert len(chunk) > 0 + chunks.append(chunk) + + assert len(chunks) > 0 + + +@pytest.mark.asyncio +async def test_voice_compatibility(tts_service): + """Test voice compatibility across versions.""" + # List voices + voices = await tts_service.list_voices() + assert len(voices) > 0 + + # Test a voice with both versions + test_voice = "af_bella" + assert test_voice in voices + + # Test with v0.19 + audio_v0, _ = await tts_service.generate_audio( + text="Test", + voice=test_voice, + version="v0.19" + ) + assert isinstance(audio_v0, np.ndarray) + assert len(audio_v0) > 0 + + # Test with v1.0 + audio_v1, _ = await tts_service.generate_audio( + text="Test", + voice=test_voice, + version="v1.0" + ) + assert isinstance(audio_v1, np.ndarray) + assert len(audio_v1) > 0 + + +@pytest.mark.asyncio +async def test_invalid_version(tts_service): + """Test handling of invalid version.""" + with pytest.raises(ValueError): + await tts_service.generate_audio( + text="Test", + voice="af_bella", + version="invalid_version" + ) + + +@pytest.mark.asyncio +async def test_invalid_voice(tts_service): + """Test handling of invalid voice.""" + with pytest.raises(ValueError): + await tts_service.generate_audio( + text="Test", + voice="invalid_voice", + version="v1.0" + ) + + +@pytest.mark.asyncio +async def test_empty_text(tts_service): + """Test handling of empty text.""" + with pytest.raises(ValueError): + await tts_service.generate_audio( + text="", + voice="af_bella", + version="v1.0" + ) + + +@pytest.mark.asyncio +async def test_voice_combination(tts_service): + """Test voice combination with different versions.""" + voices = ["af_bella", "af_nicole"] + + # Combine voices + combined_voice = await tts_service.combine_voices(voices) + assert combined_voice is not None + + # Test combined voice with both versions + for version in ["v0.19", "v1.0"]: + audio, _ = await tts_service.generate_audio( + text="Test combined voice", + voice=combined_voice, + version=version + ) + assert isinstance(audio, np.ndarray) + assert len(audio) > 0 \ No newline at end of file diff --git a/api/tests/test_version_manager.py b/api/tests/test_version_manager.py new file mode 100644 index 0000000..5a5a66d --- /dev/null +++ b/api/tests/test_version_manager.py @@ -0,0 +1,104 @@ +"""Tests for version manager functionality.""" + +import pytest +from loguru import logger + +from ..inference.version_manager import get_version_manager + + +@pytest.mark.asyncio +async def test_version_manager_initialization(): + """Test version manager initialization.""" + manager = await get_version_manager() + assert manager is not None + assert manager.current_version == "v0.19" # Default version + assert set(manager.available_versions) == {"v0.19", "v1.0"} + + +@pytest.mark.asyncio +async def test_version_switching(): + """Test switching between model versions.""" + manager = await get_version_manager() + + # Switch to v1.0 + manager.set_default_version("v1.0") + assert manager.current_version == "v1.0" + + # Switch back to v0.19 + manager.set_default_version("v0.19") + assert manager.current_version == "v0.19" + + # Test invalid version + with pytest.raises(ValueError): + manager.set_default_version("invalid_version") + + +@pytest.mark.asyncio +async def test_model_loading(): + """Test loading models for different versions.""" + manager = await get_version_manager() + + # Load v0.19 model + v0_model = await manager.get_model("v0.19") + assert v0_model is not None + + # Load v1.0 model + v1_model = await manager.get_model("v1.0") + assert v1_model is not None + + # Models should be cached + v0_model_cached = await manager.get_model("v0.19") + assert v0_model_cached is v0_model + + v1_model_cached = await manager.get_model("v1.0") + assert v1_model_cached is v1_model + + +@pytest.mark.asyncio +async def test_model_unloading(): + """Test unloading all models.""" + manager = await get_version_manager() + + # Load both models + await manager.get_model("v0.19") + await manager.get_model("v1.0") + + # Unload all + manager.unload_all() + assert not manager.models + + # Models should reload when requested + v0_model = await manager.get_model("v0.19") + assert v0_model is not None + + v1_model = await manager.get_model("v1.0") + assert v1_model is not None + + +@pytest.mark.asyncio +async def test_invalid_model_request(): + """Test requesting invalid model version.""" + manager = await get_version_manager() + + with pytest.raises(ValueError): + await manager.get_model("invalid_version") + + +@pytest.mark.asyncio +async def test_default_version_model(): + """Test getting model with default version.""" + manager = await get_version_manager() + + # Get model without specifying version + default_model = await manager.get_model() + assert default_model is not None + + # Should match explicitly requesting v0.19 + v0_model = await manager.get_model("v0.19") + assert default_model is v0_model + + # Change default and verify + manager.set_default_version("v1.0") + new_default_model = await manager.get_model() + v1_model = await manager.get_model("v1.0") + assert new_default_model is v1_model \ No newline at end of file diff --git a/docker/build.sh b/docker/build.sh index 57b5d16..e0433dd 100755 --- a/docker/build.sh +++ b/docker/build.sh @@ -12,13 +12,21 @@ REPO="kokoro-fastapi" # Create and use a new builder that supports multi-platform builds docker buildx create --name multiplatform-builder --use || true +# Enable BuildKit garbage collection +export BUILDKIT_STEP_LOG_MAX_SIZE=10485760 +export DOCKER_BUILDKIT=1 + # Build CPU image with multi-platform support echo "Building CPU image..." docker buildx build --platform linux/amd64,linux/arm64 \ -t ${REGISTRY}/${OWNER}/${REPO}-cpu:${VERSION} \ -t ${REGISTRY}/${OWNER}/${REPO}-cpu:latest \ -f docker/cpu/Dockerfile \ - --push . + --push \ + --build-arg BUILDKIT_INLINE_CACHE=1 . + +# Clean up between builds +docker builder prune -f # Build GPU image with multi-platform support echo "Building GPU image..." @@ -26,7 +34,8 @@ docker buildx build --platform linux/amd64,linux/arm64 \ -t ${REGISTRY}/${OWNER}/${REPO}-gpu:${VERSION} \ -t ${REGISTRY}/${OWNER}/${REPO}-gpu:latest \ -f docker/gpu/Dockerfile \ - --push . + --push \ + --build-arg BUILDKIT_INLINE_CACHE=1 . echo "Build complete!" echo "Created images:" diff --git a/docs/architecture/adr_kokoro_v1_integration.md b/docs/architecture/adr_kokoro_v1_integration.md new file mode 100644 index 0000000..9019962 --- /dev/null +++ b/docs/architecture/adr_kokoro_v1_integration.md @@ -0,0 +1,121 @@ +# Architectural Decision Record: Kokoro v1.0 Integration + +## Context + +We are integrating Kokoro v1.0 while maintaining backward compatibility with v0.19. The v1.0 release introduces significant architectural changes including a new KModel/KPipeline design, language-blind model architecture, and built-in vocab management. + +## Decision + +We will implement a hybrid architecture that: + +1. Maintains existing streaming infrastructure +2. Supports both v0.19 and v1.0 models +3. Adapts the new KModel/KPipeline interface to our system + +### Key Components + +#### 1. Version-Specific Model Builds +``` +api/src/builds/ +├── v0_19/ # Current implementation +└── v1_0/ # New implementation using KModel +``` + +#### 2. Model Manager Interface +```python +class ModelManager: + def __init__(self): + self.models = {} # version -> model + + async def get_model(self, version: str): + if version not in self.models: + if version == "v0.19": + from ..builds.v0_19.models import build_model + elif version == "v1.0": + from ..builds.v1_0.models import build_model + self.models[version] = await build_model() + return self.models[version] +``` + +#### 3. Voice Management +``` +api/src/voices/ +├── v0_19/ +└── v1_0/ +``` + +### Integration Strategy + +1. Model Integration + - Wrap KModel in our build system + - Adapt to new forward pass interface + - Handle phoneme mapping internally + +2. Pipeline Integration + ```python + class V1ModelWrapper: + def __init__(self, kmodel): + self.model = kmodel + self.pipeline = KPipeline(model=kmodel) + + async def forward(self, text, voice): + # Adapt v1.0 interface to our streaming system + generator = self.pipeline(text, voice=voice) + for gs, ps, audio in generator: + yield audio + ``` + +3. API Layer + - Add version parameter to endpoints + - Default to v1.0 if not specified + - Maintain backward compatibility + +## Consequences + +### Positive +- Clean separation between v0.19 and v1.0 implementations +- Minimal changes to existing streaming infrastructure +- Simple version switching mechanism +- Local voice management maintained + +### Negative +- Some code duplication between versions +- Additional wrapper layer for v1.0 +- Need to maintain two parallel implementations + +### Neutral +- Similar memory footprint (models ~few hundred MB) +- Comparable inference speed expected +- No major architectural bottlenecks + +## Implementation Plan + +1. Directory Structure Setup + - Create version-specific directories + - Move current implementation to v0_19/ + +2. V1.0 Integration + - Implement KModel wrapper + - Add version-aware model manager + - Setup voice directory structure + +3. Testing Focus + - Basic inference for both versions + - Voice compatibility + - Streaming performance + - Version switching + - API endpoint compatibility + +## Migration Path + +1. Initial Release + - Both versions available + - v0.19 as default + +2. Transition Period + - v1.0 as default + - v0.19 still available + +3. Future + - Consider deprecation timeline for v0.19 + - Document migration path for users \ No newline at end of file diff --git a/docs/architecture/file_migration_plan.md b/docs/architecture/file_migration_plan.md new file mode 100644 index 0000000..0bcb98c --- /dev/null +++ b/docs/architecture/file_migration_plan.md @@ -0,0 +1,92 @@ +# Kokoro v1.0 File Migration Plan + +## Source Files (Kokoro-82M) + +``` +Kokoro-82M/ +├── config.json # Model configuration +├── kokoro-v1_0.pth # Model weights +└── voices/ # Voice files + ├── af_alloy.pt + ├── af_aoede.pt + ├── af_bella.pt + └── ... +``` + +## Target Structure + +``` +api/src/builds/ +├── v0_19/ # Current implementation +│ ├── config.json # Move current config.json here +│ ├── models.py # Move current models.py here +│ ├── istftnet.py # Move current istftnet.py here +│ └── plbert.py # Move current plbert.py here +└── v1_0/ # New implementation + ├── config.json # From Kokoro-82M/config.json + ├── models.py # To be created - build system integration + └── wrapper.py # To be created - KModel/KPipeline wrapper + +api/src/models/ +└── v1_0/ # Model weights directory + └── kokoro-v1_0.pth # From Kokoro-82M/kokoro-v1_0.pth + +api/src/voices/ +├── v0_19/ # Current voices +│ ├── af_bella.pt +│ ├── af_nicole.pt +│ └── ... +└── v1_0/ # From Kokoro-82M/voices/ + ├── af_alloy.pt + ├── af_aoede.pt + └── ... +``` + +## Migration Steps + +1. Create Directory Structure + - Create api/src/builds/v0_19/ + - Create api/src/builds/v1_0/ + - Create api/src/models/v1_0/ + - Create api/src/voices/v0_19/ + - Create api/src/voices/v1_0/ + +2. Move Current Implementation to v0.19 + - Move api/src/builds/config.json -> api/src/builds/v0_19/config.json + - Move api/src/builds/models.py -> api/src/builds/v0_19/models.py + - Move api/src/builds/istftnet.py -> api/src/builds/v0_19/istftnet.py + - Move api/src/builds/plbert.py -> api/src/builds/v0_19/plbert.py + - Move api/src/voices/*.pt -> api/src/voices/v0_19/ + +3. Copy v1.0 Files + - Copy Kokoro-82M/config.json -> api/src/builds/v1_0/config.json + - Copy Kokoro-82M/kokoro-v1_0.pth -> api/src/models/v1_0/kokoro-v1_0.pth + - Copy Kokoro-82M/voices/*.pt -> api/src/voices/v1_0/ + +4. Create New Implementation Files + - Create api/src/builds/v1_0/wrapper.py for KModel integration + - Create api/src/builds/v1_0/models.py for build system integration + +## Implementation Notes + +1. Voice Management + - Keep voice files local, no HF downloads + - Maintain compatibility with both versions + - Consider voice file format differences + +2. Model Integration + - Use kokoro package for v1.0 model loading + - Model weights accessed from api/src/models/v1_0/ + - Adapt to our streaming infrastructure + - Handle version-specific configurations + +3. Testing Considerations + - Verify file permissions after moves + - Test voice loading from both directories + - Ensure backward compatibility + - Validate streaming performance + +4. Code Updates + - Update model loading paths in wrapper.py to point to api/src/models/v1_0/ + - Maintain separation between model weights and build configuration + - Ensure proper error handling for missing files \ No newline at end of file diff --git a/docs/architecture/implementation_checklist.md b/docs/architecture/implementation_checklist.md new file mode 100644 index 0000000..522e4e6 --- /dev/null +++ b/docs/architecture/implementation_checklist.md @@ -0,0 +1,49 @@ +# Kokoro v1.0 Implementation Checklist + +## 1. Directory Setup +- [ ] Create api/src/models/v1_0/ +- [ ] Create api/src/builds/v0_19/ +- [ ] Create api/src/builds/v1_0/ +- [ ] Create api/src/voices/v0_19/ +- [ ] Create api/src/voices/v1_0/ + +## 2. Move Current Implementation to v0.19 +- [ ] Move api/src/builds/config.json -> api/src/builds/v0_19/config.json +- [ ] Move api/src/builds/models.py -> api/src/builds/v0_19/models.py +- [ ] Move api/src/builds/istftnet.py -> api/src/builds/v0_19/istftnet.py +- [ ] Move api/src/builds/plbert.py -> api/src/builds/v0_19/plbert.py +- [ ] Move current voices to api/src/voices/v0_19/ + +## 3. Copy v1.0 Files from Kokoro-82M +- [ ] Copy kokoro-v1_0.pth -> api/src/models/v1_0/kokoro-v1_0.pth +- [ ] Copy config.json -> api/src/builds/v1_0/config.json +- [ ] Copy voices/*.pt -> api/src/voices/v1_0/ + +## 4. Create v1.0 Implementation +- [ ] Create api/src/builds/v1_0/wrapper.py +- [ ] Create api/src/builds/v1_0/models.py +- [ ] Update imports in moved files +- [ ] Install kokoro package dependencies + +## 5. Update Model Manager +- [ ] Update model manager to support both versions +- [ ] Add version-specific model loading +- [ ] Add version selection parameter to API endpoints + +## 6. Testing +- [ ] Test v0.19 functionality still works +- [ ] Test v1.0 model loading +- [ ] Test voice loading for both versions +- [ ] Test streaming functionality +- [ ] Test version switching + +## 7. Documentation +- [ ] Update API documentation with version parameter +- [ ] Document voice compatibility +- [ ] Add migration guide for users + +## Notes +- Model weights go in api/src/models/v1_0/ +- Build configs and code go in api/src/builds/v1_0/ +- Keep voice files local, no HF downloads +- Test each step before proceeding to next \ No newline at end of file diff --git a/docs/architecture/kokoro_v1_refactor.md b/docs/architecture/kokoro_v1_refactor.md new file mode 100644 index 0000000..a79efea --- /dev/null +++ b/docs/architecture/kokoro_v1_refactor.md @@ -0,0 +1,68 @@ +# Kokoro Version Support Architecture + +## Overview + +Simple architecture for supporting both Kokoro v0.19 and v1.0 models, allowing version selection via API. + +## Directory Structure + +``` +api/src/builds/ +├── v0_19/ # Current implementation +│ ├── config.json +│ ├── models.py +│ ├── istftnet.py +│ └── plbert.py +└── v1_0/ # New v1.0 implementation + ├── config.json + ├── models.py + ├── istftnet.py + └── albert.py +``` + +## Implementation Plan + +1. Move Current Implementation + - Relocate existing files to v0_19/ + - Update imports + +2. Add v1.0 Implementation + - Copy reference implementation + - Adapt to our structure + - Keep voice management local + +3. Model Manager Updates + ```python + class ModelManager: + def __init__(self): + self.models = {} # version -> model + + async def get_model(self, version: str): + if version not in self.models: + if version == "v0.19": + from ..builds.v0_19.models import build_model + elif version == "v1.0": + from ..builds.v1_0.models import build_model + self.models[version] = await build_model() + return self.models[version] + ``` + +4. API Integration + - Add version parameter to endpoints + - Default to v1.0 if not specified + +## Voice Management +- Simple directory structure: + ``` + api/src/voices/ + ├── v0_19/ + └── v1_0/ + ``` +- Keep voice files local, no HF downloads + +## Testing +- Basic functionality tests for each version +- Version switching tests +- Voice compatibility tests + +No need to over-optimize - models and voices are small enough to keep things simple. \ No newline at end of file diff --git a/docs/architecture/kokoro_v1_technical_notes.md b/docs/architecture/kokoro_v1_technical_notes.md new file mode 100644 index 0000000..75d9095 --- /dev/null +++ b/docs/architecture/kokoro_v1_technical_notes.md @@ -0,0 +1,116 @@ +# Kokoro v1.0 Technical Integration Notes + +## Core Components + +1. KModel Class +- Main model class with unified interface +- Handles both weights and inference +- Language-blind design (phoneme focused) +- No external language processing + +2. Key Architecture Changes +- Uses CustomAlbert instead of PLBert +- New ProsodyPredictor implementation +- Different phoneme handling approach +- Built-in vocab management + +## Integration Points + +1. Model Loading +```python +# v1.0 approach +model = KModel(config_path, model_path) +# vs our current +model = await build_model(path, device) +``` + +2. Forward Pass Differences +```python +# v1.0 +audio = model(phonemes, ref_s, speed=1.0) +# vs our current +audio = model.decoder(asr, F0_pred, N_pred, ref_s) +``` + +3. Key Dependencies +- transformers (for AlbertConfig) +- torch +- No external phoneme processing + +## Configuration Changes + +1. v1.0 Config Structure +```json +{ + "vocab": {...}, # Built-in phoneme mapping + "n_token": X, + "plbert": {...}, # Albert config + "hidden_dim": X, + "style_dim": X, + "istftnet": {...} +} +``` + +2. Voice Management +- No HF downloads +- Local voice file management +- Simpler voice structure + +## Implementation Strategy + +1. Core Changes +- Keep our streaming infrastructure +- Adapt to new model interface +- Maintain our voice management + +2. Key Adaptations Needed +- Wrap KModel in our build system +- Handle phoneme mapping internally +- Adapt to new prosody prediction + +3. Compatibility Layer +```python +class V1ModelWrapper: + def __init__(self, kmodel): + self.model = kmodel + + async def forward(self, phonemes, ref_s): + # Adapt v1.0 interface to our system + return self.model(phonemes, ref_s) +``` + +## Technical Considerations + +1. Memory Usage +- Models ~few hundred MB +- Voices ~few hundred KB +- No need for complex memory management + +2. Performance +- Similar inference speed expected +- No major architectural bottlenecks +- Keep existing streaming optimizations + +3. Integration Points +- Model loading/initialization +- Voice file management +- Inference pipeline +- Streaming output + +## Migration Notes + +1. Key Files to Port +- model.py -> v1_0/models.py +- istftnet.py -> v1_0/istftnet.py +- Add albert.py for CustomAlbert + +2. Config Updates +- Add version selection +- Keep config structure similar +- Add v1.0 specific params + +3. Testing Focus +- Basic inference +- Voice compatibility +- Streaming performance +- Version switching \ No newline at end of file diff --git a/docs/architecture/v1_wrapper_spec.md b/docs/architecture/v1_wrapper_spec.md new file mode 100644 index 0000000..c058035 --- /dev/null +++ b/docs/architecture/v1_wrapper_spec.md @@ -0,0 +1,175 @@ +# Kokoro v1.0 Wrapper Technical Specification + +## Overview + +This document details the technical implementation of the KokoroV1Wrapper class that integrates the Kokoro v1.0 KModel/KPipeline architecture with our existing system. + +## Class Implementation + +```python +from pathlib import Path +from kokoro import KModel, KPipeline + +class KokoroV1Wrapper: + """Wrapper for Kokoro v1.0 KModel/KPipeline integration. + + This wrapper manages: + 1. Model initialization and weight loading + 2. Pipeline creation and caching per language + 3. Streaming audio generation + """ + + def __init__(self, config_path: str, model_path: str): + """Initialize KModel with config and weights. + + Args: + config_path: Path to config.json in builds/v1_0/ + model_path: Path to model weights in models/v1_0/ + """ + self.model = KModel() # Will load config and weights + self.pipelines = {} # lang_code -> KPipeline cache + + def get_pipeline(self, lang_code: str) -> KPipeline: + """Get or create a KPipeline for the given language code. + + Args: + lang_code: Language code for phoneme processing + + Returns: + KPipeline instance for the language + """ + if lang_code not in self.pipelines: + self.pipelines[lang_code] = KPipeline( + lang_code=lang_code, + model=self.model + ) + return self.pipelines[lang_code] + + async def forward(self, text: str, voice: str, lang_code: str): + """Generate audio using the appropriate pipeline. + + Args: + text: Input text to synthesize + voice: Voice ID to use + lang_code: Language code for phoneme processing + + Yields: + Audio chunks as torch.FloatTensor + """ + pipeline = self.get_pipeline(lang_code) + generator = pipeline(text, voice=voice) + for gs, ps, audio in generator: + yield audio + +class ModelManager: + """Manages multiple model versions and their initialization.""" + + def __init__(self): + self.models = {} + + async def get_model(self, version: str): + """Get or initialize a model for the specified version. + + Args: + version: Model version ("v0.19" or "v1.0") + + Returns: + Initialized model instance + """ + if version not in self.models: + if version == "v0.19": + from ..builds.v0_19.models import build_model + self.models[version] = await build_model() + elif version == "v1.0": + from ..builds.v1_0.wrapper import KokoroV1Wrapper + + # Config in builds directory + config_path = Path(__file__).parent / "builds/v1_0/config.json" + + # Model weights in models directory + model_path = Path(__file__).parent / "models/v1_0/kokoro-v1_0.pth" + + self.models[version] = KokoroV1Wrapper( + config_path=str(config_path), + model_path=str(model_path) + ) + return self.models[version] +``` + +## Key Design Points + +1. Model Management + - KModel handles weights and inference + - Config and weights loaded from separate directories + - Language-blind design (phoneme focused) + +2. Pipeline Caching + - One KPipeline per language code + - Pipelines created on demand and cached + - Reuses single KModel instance + +3. Streaming Integration + - Maintains compatibility with existing streaming system + - Yields audio chunks progressively + - Handles both quiet and loud pipeline modes + +4. Version Control + - Clear separation between v0.19 and v1.0 + - Version-specific model initialization + - Shared model manager interface + +## Usage Example + +```python +# Initialize model manager +manager = ModelManager() + +# Get v1.0 model +model = await manager.get_model("v1.0") + +# Generate audio +async for audio in model.forward( + text="Hello world", + voice="af_bella", + lang_code="en" +): + # Process audio chunk + process_audio(audio) +``` + +## Error Handling + +1. File Access + - Verify config.json exists in builds/v1_0/ + - Verify model weights exist in models/v1_0/ + - Handle missing or corrupt files + +2. Pipeline Creation + - Validate language codes + - Handle initialization failures + - Clean up failed pipeline instances + +3. Voice Loading + - Verify voice file existence + - Handle voice format compatibility + - Manage voice loading failures + +## Testing Strategy + +1. Unit Tests + - Model initialization + - Pipeline creation and caching + - Audio generation + - Error handling + +2. Integration Tests + - End-to-end audio generation + - Streaming performance + - Memory usage + - Multi-language support + +3. Performance Tests + - Pipeline creation overhead + - Memory usage patterns + - Streaming latency + - Voice loading speed \ No newline at end of file diff --git a/examples/openai_streaming_audio.py b/examples/openai_streaming_audio.py index ec3e371..74ecfd1 100644 --- a/examples/openai_streaming_audio.py +++ b/examples/openai_streaming_audio.py @@ -4,20 +4,22 @@ from pathlib import Path from openai import OpenAI -# gets OPENAI_API_KEY from your environment variables +# By default, the library tries to take OPENAI_API_KEY +# from your environment variables, +# so set explicitly to any string to allow it to skip the check openai = OpenAI(base_url="http://localhost:8880/v1", api_key="not-needed-for-local") speech_file_path = Path(__file__).parent / "speech.mp3" - def main() -> None: stream_to_speakers() # Create text-to-speech audio file with openai.audio.speech.with_streaming_response.create( model="kokoro", - voice="af_bella", + voice="af_sky+af_bella", input="the quick brown fox jumped over the lazy dogs", + response_format="mp3", ) as response: response.stream_to_file(speech_file_path) diff --git a/examples/speech.mp3 b/examples/speech.mp3 index c21bec0..b37cb3a 100644 Binary files a/examples/speech.mp3 and b/examples/speech.mp3 differ diff --git a/pyproject.toml b/pyproject.toml index ca45eb5..a3613c2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -37,6 +37,7 @@ dependencies = [ "semchunk>=3.0.1", "mutagen>=1.47.0", "psutil>=6.1.1", + "kokoro==0.3.1" ] [project.optional-dependencies] diff --git a/start-cpu.sh b/start-cpu.sh index cde957f..7be376d 100755 --- a/start-cpu.sh +++ b/start-cpu.sh @@ -5,7 +5,7 @@ PROJECT_ROOT=$(pwd) # Set environment variables export USE_GPU=false -export USE_ONNX=true +export USE_ONNX=false export PYTHONPATH=$PROJECT_ROOT:$PROJECT_ROOT/api export MODEL_DIR=$PROJECT_ROOT/api/src/models export VOICES_DIR=$PROJECT_ROOT/api/src/voices diff --git a/uv.lock b/uv.lock index 079f7d7..277f923 100644 --- a/uv.lock +++ b/uv.lock @@ -110,6 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diff --git a/web/src/components/VoiceSelector.js b/web/src/components/VoiceSelector.js index 4209378..394b205 100644 --- a/web/src/components/VoiceSelector.js +++ b/web/src/components/VoiceSelector.js @@ -5,13 +5,21 @@ export class VoiceSelector { voiceSearch: document.getElementById('voice-search'), voiceDropdown: document.getElementById('voice-dropdown'), voiceOptions: document.getElementById('voice-options'), - selectedVoices: document.getElementById('selected-voices') + selectedVoices: document.getElementById('selected-voices'), + versionSelect: document.getElementById('version-select') }; this.setupEventListeners(); } setupEventListeners() { + // Version selection + this.elements.versionSelect?.addEventListener('change', async (e) => { + await this.voiceService.setVersion(e.target.value); + this.renderVoiceOptions(this.voiceService.getAvailableVoices()); + this.updateSelectedVoicesDisplay(); + }); + // Voice search this.elements.voiceSearch.addEventListener('input', (e) => { const filteredVoices = this.voiceService.filterVoices(e.target.value); @@ -101,8 +109,28 @@ export class VoiceSelector { } } + renderVersionSelect() { + if (!this.elements.versionSelect) return; + + const versions = this.voiceService.getAvailableVersions(); + const currentVersion = this.voiceService.getCurrentVersion(); + + this.elements.versionSelect.innerHTML = versions + .map(version => ` + + `) + .join(''); + } + async initialize() { try { + // Load versions first + await this.voiceService.loadVersions(); + this.renderVersionSelect(); + + // Then load voices for current version await this.voiceService.loadVoices(); this.renderVoiceOptions(this.voiceService.getAvailableVoices()); this.updateSelectedVoicesDisplay(); diff --git a/web/src/services/AudioService.js b/web/src/services/AudioService.js index 1ef24da..655610f 100644 --- a/web/src/services/AudioService.js +++ b/web/src/services/AudioService.js @@ -11,6 +11,11 @@ export class AudioService { this.CHARS_PER_CHUNK = 300; // Estimated chars per chunk this.serverDownloadPath = null; // Server-side download path this.pendingOperations = []; // Queue for buffer operations + this.currentVersion = null; // Current model version + } + + setVersion(version) { + this.currentVersion = version; } async streamAudio(text, voice, speed, onProgress) { @@ -33,7 +38,7 @@ export class AudioService { console.log('AudioService: Making API call...', { text, voice, speed }); - const response = await fetch('/v1/audio/speech', { + const response = await fetch('/v2/audio/speech', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ @@ -42,7 +47,8 @@ export class AudioService { response_format: 'mp3', stream: true, speed: speed, - return_download_link: true + return_download_link: true, + version: this.currentVersion }), signal: this.controller.signal }); @@ -55,7 +61,7 @@ export class AudioService { // Check for download path as soon as we get the response const downloadPath = response.headers.get('x-download-path'); if (downloadPath) { - this.serverDownloadPath = `/v1${downloadPath}`; + this.serverDownloadPath = `/v2${downloadPath}`; console.log('Download path received:', this.serverDownloadPath); } @@ -123,7 +129,7 @@ export class AudioService { const downloadPath = headers['x-download-path']; if (downloadPath) { // Prepend /v1 since the router is mounted there - this.serverDownloadPath = `/v1${downloadPath}`; + this.serverDownloadPath = `/v2${downloadPath}`; console.log('Download path received:', this.serverDownloadPath); } else { console.warn('No X-Download-Path header found. Available headers:', diff --git a/web/src/services/VoiceService.js b/web/src/services/VoiceService.js index 92cd4db..b0d9538 100644 --- a/web/src/services/VoiceService.js +++ b/web/src/services/VoiceService.js @@ -2,11 +2,36 @@ export class VoiceService { constructor() { this.availableVoices = []; this.selectedVoices = new Set(); + this.currentVersion = null; + this.availableVersions = []; + } + + async loadVersions() { + try { + const response = await fetch('/v2/audio/versions'); + if (!response.ok) { + const error = await response.json(); + throw new Error(error.detail?.message || 'Failed to load versions'); + } + + const data = await response.json(); + this.availableVersions = data.versions; + this.currentVersion = data.current; + return data; + } catch (error) { + console.error('Failed to load versions:', error); + throw error; + } } async loadVoices() { try { - const response = await fetch('/v1/audio/voices'); + // Load versions first if not loaded + if (!this.currentVersion) { + await this.loadVersions(); + } + + const response = await fetch(`/v2/audio/voices?version=${this.currentVersion}`); if (!response.ok) { const error = await response.json(); throw new Error(error.detail?.message || 'Failed to load voices'); @@ -27,7 +52,10 @@ export class VoiceService { } } - return this.availableVoices; + return { + voices: this.availableVoices, + version: data.version + }; } catch (error) { console.error('Failed to load voices:', error); throw error; @@ -46,6 +74,40 @@ export class VoiceService { return Array.from(this.selectedVoices).join('+'); } + async setVersion(version) { + try { + const response = await fetch('/v2/audio/version', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify(version) + }); + + if (!response.ok) { + const error = await response.json(); + throw new Error(error.detail?.message || 'Failed to set version'); + } + + const data = await response.json(); + this.currentVersion = data.current; + this.availableVersions = data.versions; + + // Reload voices for new version + await this.loadVoices(); + return data; + } catch (error) { + console.error('Failed to set version:', error); + throw error; + } + } + + getCurrentVersion() { + return this.currentVersion; + } + + getAvailableVersions() { + return this.availableVersions; + } + addVoice(voice) { if (this.availableVoices.includes(voice)) { this.selectedVoices.add(voice); diff --git a/web/styles/forms.css b/web/styles/forms.css index 97bc446..5d912af 100644 --- a/web/styles/forms.css +++ b/web/styles/forms.css @@ -36,6 +36,34 @@ textarea::placeholder { gap: 1rem; } +.version-select-wrapper { + width: 100%; +} + +.version-select { + width: 100%; + padding: 0.75rem 1rem; + border: 1px solid var(--border); + border-radius: 0.5rem; + background: rgba(15, 23, 42, 0.3); + color: var(--text); + font-size: 1rem; + transition: all 0.2s ease; + cursor: pointer; + font-family: var(--font-family); +} + +.version-select:focus { + outline: none; + border-color: var(--fg-color); + box-shadow: 0 0 0 3px rgba(99, 102, 241, 0.2); +} + +.version-select option { + background: var(--surface); + color: var(--text); +} + .voice-search { width: 100%; padding: 0.75rem 1rem;