app.py

import random
import numpy as np
import torch
from chatterbox.tts import ChatterboxTTS
import gradio as gr
import spaces

DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
print(f"🚀 Running on device: {DEVICE}")

# --- Global Model Initialization ---
MODEL = None

def get_or_load_model():
    """Loads the TTS model if it hasn't been loaded already,
    and ensures it's on the correct device."""
    global MODEL
    if MODEL is None:
        print("Model not loaded, initializing...")
        try:
            MODEL = ChatterboxTTS.from_pretrained(DEVICE)
            if hasattr(MODEL, 'to') and str(MODEL.device) != DEVICE:
                MODEL.to(DEVICE)
            print(f"Model loaded successfully. Internal device: {getattr(MODEL, 'device', 'N/A')}")
        except Exception as e:
            print(f"Error loading model: {e}")
            raise
    return MODEL

# Attempt to load the model at startup.
try:
    get_or_load_model()
except Exception as e:
    print(f"CRITICAL: Failed to load model on startup. Application may not function. Error: {e}")

def set_seed(seed: int):
    """Sets the random seed for reproducibility across torch, numpy, and random."""
    torch.manual_seed(seed)
    if DEVICE == "cuda":
        torch.cuda.manual_seed(seed)
        torch.cuda.manual_seed_all(seed)
    random.seed(seed)
    np.random.seed(seed)

@spaces.GPU
def generate_tts_audio(
    text_input: str,
    audio_prompt_path_input: str = None,
    exaggeration_input: float = 0.5,
    temperature_input: float = 0.8,
    seed_num_input: int = 0,
    cfgw_input: float = 0.5
) -> tuple[int, np.ndarray]:
    """
    Generate high-quality speech audio from text using TTS model with optional reference audio styling.
    
    This tool synthesizes natural-sounding speech from input text. When a reference audio file 
    is provided, it captures the speaker's voice characteristics and speaking style. The generated audio 
    maintains the prosody, tone, and vocal qualities of the reference speaker, or uses default voice if no reference is provided.
    Args:
        text_input (str): The text to synthesize into speech (maximum 300 characters)
        audio_prompt_path_input (str, optional): File path or URL to the reference audio file that defines the target voice style. Defaults to None.
        exaggeration_input (float, optional): Controls speech expressiveness (0.25-2.0, neutral=0.5, extreme values may be unstable). Defaults to 0.5.
        temperature_input (float, optional): Controls randomness in generation (0.05-5.0, higher=more varied). Defaults to 0.8.
        seed_num_input (int, optional): Random seed for reproducible results (0 for random generation). Defaults to 0.
        cfgw_input (float, optional): CFG/Pace weight controlling generation guidance (0.2-1.0). Defaults to 0.5.
    Returns:
        tuple[int, np.ndarray]: A tuple containing the sample rate (int) and the generated audio waveform (numpy.ndarray)
    """
    current_model = get_or_load_model()

    if current_model is None:
        raise RuntimeError("TTS model is not loaded.")

    if seed_num_input != 0:
        set_seed(int(seed_num_input))

    print(f"Generating audio for text: '{text_input[:50]}...'")
    
    # Handle optional audio prompt
    generate_kwargs = {
        "exaggeration": exaggeration_input,
        "temperature": temperature_input,
        "cfg_weight": cfgw_input,
    }
    
    if audio_prompt_path_input:
        generate_kwargs["audio_prompt_path"] = audio_prompt_path_input
    
    wav = current_model.generate(
        text_input[:300],  # Truncate text to max chars
        **generate_kwargs
    )
    print("Audio generation complete.")
    return (current_model.sr, wav.squeeze(0).numpy())

with gr.Blocks() as demo:
    gr.Markdown(
        """
        # Karay Akar TTS Demo Türkçe (Chatterbox)* 
        Yüksek kaliteli ses ve ses klonlama özellikleri ile.
        """
    )
    with gr.Row():
        with gr.Column():
            text = gr.Textbox(
                value="Yapzek.ai çok yakında ses klonlama özelliğiyle sınırları bir adım daha öteye taşıyor! Kendi sesinizi birkaç dakikalık örnekle klonlayabilecek, dilediğiniz metni kendi sesinizle, üstelik duygulu ve doğal bir şekilde seslendirebileceksiniz. ",
                label="Metin girin (maksimum 300 karekter)",
                max_lines=5
            )
            ref_wav = gr.Audio(
                sources=["upload", "microphone"],
                type="filepath",
                label="Reference ses dosyası (Opsiyonel)",
                value=None
            )
            exaggeration = gr.Slider(
                0.25, 2, step=.05, label="Exaggeration (Neutral = 0.5, extreme values can be unstable)", value=.35
            )
            cfg_weight = gr.Slider(
                0.2, 1, step=.05, label="CFG/Pace", value=0.5
            )

            with gr.Accordion("More options", open=False):
                seed_num = gr.Number(value=1000, label="Random seed (0 for random)")
                temp = gr.Slider(0.05, 5, step=.05, label="Temperature", value=.4)

            run_btn = gr.Button("Generate", variant="primary")

        with gr.Column():
            audio_output = gr.Audio(label="Output Audio")

    run_btn.click(
        fn=generate_tts_audio,
        inputs=[
            text,
            ref_wav,
            exaggeration,
            temp,
            seed_num,
            cfg_weight,
        ],
        outputs=[audio_output],
    )

demo.launch(mcp_server=True)