| from typing import Dict, Any | |
| import torch | |
| # Import your specific VITS inference pipeline here | |
| class EndpointHandler: | |
| def __init__(self, path=""): | |
| # 1. Load your VITS model weights from 'path' | |
| # 2. Load your config.json parameters | |
| self.device = "cuda" if torch.cuda.is_available() else "cpu" | |
| def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]: | |
| """ | |
| data: JSON payload sent to the API | |
| """ | |
| # 1. Get the text to synthesize | |
| text = data.get("inputs", "") | |
| # 2. Run your VITS text-to-speech generation logic here | |
| # audio_data = self.model(text) | |
| # 3. Return the audio (usually base64 encoded or raw bytes) | |
| return {"audio": "base64_encoded_audio_string_here"} | |