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| # app.py (for MeloTTS API Space) | |
| import gradio as gr | |
| import os | |
| import torch | |
| import io | |
| import soundfile as sf | |
| import base64 | |
| import logging | |
| # --- Setup --- | |
| # This command is crucial and needs to run once. | |
| # It downloads the dictionary needed for Japanese/Korean. | |
| os.system('python -m unidic download') | |
| from melo.api import TTS | |
| # --- Logging --- | |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') | |
| logger = logging.getLogger(__name__) | |
| # --- Model Loading --- | |
| MODEL = None | |
| DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu' | |
| LANGUAGE = 'KR' | |
| # We will use 0.9 for a slightly faster than normal, clear pace. | |
| SPEED = 0.9 | |
| try: | |
| logger.info(f"Loading MeloTTS model for language: {LANGUAGE} on device: {DEVICE}") | |
| MODEL = TTS(language=LANGUAGE, device=DEVICE) | |
| SPEAKER_ID = 'KR' # For Korean, the main speaker is just 'KR' | |
| logger.info("MeloTTS model loaded successfully.") | |
| logger.info(f"Default speaker: {SPEAKER_ID}, Default speed: {SPEED}") | |
| except Exception as e: | |
| logger.exception(f"FATAL: MeloTTS model initialization error: {e}") | |
| MODEL = None | |
| # --- Main TTS Synthesis Function --- | |
| def synthesize(text_to_synthesize): | |
| if not MODEL: | |
| raise gr.Error("TTS Model is not loaded. Cannot process request.") | |
| if not text_to_synthesize or not text_to_synthesize.strip(): | |
| # Create and return a silent audio data URI | |
| silent_audio = np.zeros(int(0.1 * 24000), dtype=np.int16) # Melo uses 24kHz | |
| wav_buffer = io.BytesIO() | |
| sf.write(wav_buffer, silent_audio, 24000, format='WAV') | |
| wav_buffer.seek(0) | |
| wav_base64 = base64.b64encode(wav_buffer.read()).decode('utf-8') | |
| return f"data:audio/wav;base64,{wav_base64}" | |
| try: | |
| logger.info(f"Synthesizing for text: '{text_to_synthesize[:80]}...'") | |
| # Use an in-memory BytesIO object to store the audio | |
| wav_buffer = io.BytesIO() | |
| MODEL.tts_to_file(text_to_synthesize, SPEAKER_ID, wav_buffer, speed=SPEED, format='wav') | |
| # Reset buffer position to the beginning | |
| wav_buffer.seek(0) | |
| # Read the bytes and encode to base64 | |
| wav_base64 = base64.b64encode(wav_buffer.read()).decode('utf-8') | |
| logger.info("Synthesis complete.") | |
| return f"data:audio/wav;base64,{wav_base64}" | |
| except Exception as e: | |
| logger.exception(f"MeloTTS synthesis error: {e}") | |
| raise gr.Error(f"An error occurred during synthesis: {str(e)}") | |
| # --- Create and Launch the Gradio Interface --- | |
| # We create a pure API without a complex UI. | |
| iface = gr.Interface( | |
| fn=synthesize, | |
| inputs=gr.Textbox(label="Text to Synthesize"), | |
| outputs=gr.Textbox(label="Base64 Audio Output"), # Output is a text string for the API | |
| title="MeloTTS API for Korean", | |
| description="A simplified API for MeloTTS, configured for Korean language.", | |
| api_name="synthesize" | |
| ) | |
| # The .queue() is important for handling multiple requests on HF Spaces. | |
| iface.queue().launch() |