Delete app.py

app.py

@@ -1,228 +0,0 @@
-import random
-import re
-import numpy as np
-import torch
-import torchaudio
-from src.chatterbox.mtl_tts import ChatterboxMultilingualTTS, SUPPORTED_LANGUAGES
-import gradio as gr
-import spaces
-
-DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-print(f"🚀 Running on device: {DEVICE}")
-
-MODEL = None
-
-LANGUAGE_CONFIG = {
-    "ar": {"audio": "https://storage.googleapis.com/chatterbox-demo-samples/mtl_prompts/ar_f/ar_prompts2.flac",
-           "text": "في الشهر الماضي، وصلنا إلى معلم جديد بمليارين من المشاهدات على قناتنا على يوتيوب."},
-    "en": {"audio": "https://storage.googleapis.com/chatterbox-demo-samples/mtl_prompts/en_f1.flac",
-           "text": "Last month, we reached a new milestone with two billion views on our YouTube channel."},
-    "fr": {"audio": "https://storage.googleapis.com/chatterbox-demo-samples/mtl_prompts/fr_f1.flac",
-           "text": "Le mois dernier, nous avons atteint un nouveau jalon avec deux milliards de vues sur notre chaîne YouTube."},
-    "hi": {"audio": "https://storage.googleapis.com/chatterbox-demo-samples/mtl_prompts/hi_f1.flac",
-           "text": "पिछले महीने हमने एक नया मील का पत्थर छुआ: हमारे YouTube चैनल पर दो अरब व्यूज़।"},
-    "tr": {"audio": "https://storage.googleapis.com/chatterbox-demo-samples/mtl_prompts/tr_m.flac",
-           "text": "Geçen ay YouTube kanalımızda iki milyar görüntüleme ile yeni bir dönüm noktasına ulaştık."},
-    "zh": {"audio": "https://storage.googleapis.com/chatterbox-demo-samples/mtl_prompts/zh_f2.flac",
-           "text": "上个月，我们达到了一个新的里程碑。 我们的YouTube频道观看次数达到了二十亿次，这绝对令人难以置信。"},
-}
-
-def default_audio_for_ui(lang: str) -> str | None:
-    return LANGUAGE_CONFIG.get(lang, {}).get("audio")
-
-def default_text_for_ui(lang: str) -> str:
-    return LANGUAGE_CONFIG.get(lang, {}).get("text", "")
-
-def get_supported_languages_display() -> str:
-    items = [f"**{name}** (`{code}`)" for code, name in sorted(SUPPORTED_LANGUAGES.items())]
-    mid = len(items)//2
-    return f"### 🌍 Supported Languages ({len(SUPPORTED_LANGUAGES)} total)\n" \
-           f"{' • '.join(items[:mid])}\n\n{' • '.join(items[mid:])}"
-
-def get_or_load_model():
-    global MODEL
-    if MODEL is None:
-        print("Model not loaded, initializing...")
-        MODEL = ChatterboxMultilingualTTS.from_pretrained(DEVICE)
-        if hasattr(MODEL, "to"):
-            MODEL.to(DEVICE)
-        print(f"✅ Model loaded successfully on {DEVICE}")
-    return MODEL
-
-try:
-    get_or_load_model()
-except Exception as e:
-    print(f"CRITICAL: Failed to load model. Error: {e}")
-
-def set_seed(seed: int):
-    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)
-
-def resolve_audio_prompt(language_id: str, provided_path: str | None) -> str | None:
-    if provided_path and str(provided_path).strip():
-        return provided_path
-    return LANGUAGE_CONFIG.get(language_id, {}).get("audio")
-
-
-# ======================================================
-# ⭐⭐ HÀM THÊM NGẮT NGHỈ TỰ NHIÊN (THÊM MỚI)
-# ======================================================
-def enhance_prosody(text: str) -> str:
-    text = re.sub(r"\s+", " ", text.strip())
-
-    # Pause theo dấu câu
-    text = re.sub(r"\.", ". …", text)
-    text = re.sub(r",", ", –", text)
-    text = re.sub(r";", "; …", text)
-    text = re.sub(r":", ": …", text)
-    text = re.sub(r"([!?])", r"\1 …", text)
-
-    # Từ chuyển ý
-    transition_words = [
-        "tuy nhiên", "nhưng", "vì vậy", "do đó",
-        "mặt khác", "bên cạnh đó", "ngoài ra", "tóm lại"
-    ]
-    for w in transition_words:
-        text = re.sub(fr"\b{w}\b", f"… {w}", text, flags=re.IGNORECASE)
-
-    return text
-
-
-
-# ======================================================
-# TEXT SPLITTER
-# ======================================================
-def split_text_into_chunks(text: str, max_chars: int = 500) -> list[str]:
-    text = re.sub(r"\s+", " ", text.strip())
-    if len(text) <= max_chars:
-        return [text]
-
-    sentences = re.split(r'(?<=[.!?۔،])\s+', text)
-    chunks, current_chunk = [], ""
-
-    for sent in sentences:
-        if len(current_chunk) + len(sent) < max_chars:
-            current_chunk += " " + sent
-        else:
-            chunks.append(current_chunk.strip())
-            current_chunk = sent
-    if current_chunk:
-        chunks.append(current_chunk.strip())
-
-    return [c for c in chunks if c]
-
-
-# ======================================================
-# GENERATE AUDIO
-# ======================================================
-@spaces.GPU
-def generate_tts_audio(
-    text_input: str,
-    language_id: 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
-):
-
-    current_model = get_or_load_model()
-    if current_model is None:
-        raise RuntimeError("TTS model not loaded.")
-
-    if seed_num_input == 0:
-        seed_num_input = random.randint(1, 2**32 - 1)
-        print(f"🌱 Random seed generated: {seed_num_input}")
-    else:
-        print(f"🌱 Using provided seed: {seed_num_input}")
-
-    set_seed(int(seed_num_input))
-
-    chosen_prompt = audio_prompt_path_input or default_audio_for_ui(language_id)
-    generate_kwargs = {
-        "exaggeration": exaggeration_input,
-        "temperature": temperature_input,
-        "cfg_weight": cfgw_input,
-    }
-    if chosen_prompt:
-        generate_kwargs["audio_prompt_path"] = chosen_prompt
-
-    # ⭐⭐ ÁP DỤNG NGẮT NGHỈ TỰ NHIÊN TRƯỚC KHI GENERATE ⭐⭐
-    text_input = enhance_prosody(text_input)
-
-    chunks = split_text_into_chunks(text_input)
-
-    all_audio = []
-    for chunk in chunks:
-        wav = current_model.generate(chunk, language_id=language_id, **generate_kwargs)
-        all_audio.append(wav.squeeze(0).cpu())
-
-    final_audio = torch.cat(all_audio, dim=-1)
-    return (current_model.sr, final_audio.numpy()), str(seed_num_input)
-
-
-
-# ======================================================
-# GRADIO UI
-# ======================================================
-with gr.Blocks() as demo:
-    gr.Markdown("""
-    # 🎙️ Multi Language Realistic Voice Cloner
-    Generate long-form multilingual speech with reference audio styling and auto-chunking.
-    """)
-
-    gr.Markdown(get_supported_languages_display())
-
-    with gr.Row():
-        with gr.Column():
-            initial_lang = "en"
-            text = gr.Textbox(
-                value=default_text_for_ui(initial_lang),
-                label="Text to synthesize",
-                lines=8
-            )
-            language_id = gr.Dropdown(
-                choices=list(ChatterboxMultilingualTTS.get_supported_languages().keys()),
-                value=initial_lang,
-                label="Language"
-            )
-            ref_wav = gr.Audio(
-                sources=["upload", "microphone"],
-                type="filepath",
-                label="Reference Audio (Optional)",
-                value=default_audio_for_ui(initial_lang)
-            )
-            exaggeration = gr.Slider(0.25, 2, step=.05, label="Exaggeration", value=.5)
-            cfg_weight = gr.Slider(0.2, 1, step=.05, label="CFG Weight", value=0.5)
-
-            with gr.Accordion("Advanced", open=False):
-                seed_num = gr.Number(value=0, label="Random Seed (0=random)")
-                temp = gr.Slider(0.05, 5, step=.05, label="Temperature", value=.8)
-
-            run_btn = gr.Button("Generate", variant="primary")
-
-        with gr.Column():
-            audio_output = gr.Audio(label="Output Audio")
-            seed_output = gr.Textbox(label="Seed Used", interactive=False)
-
-        def on_lang_change(lang, current_ref, current_text):
-            return default_audio_for_ui(lang), default_text_for_ui(lang)
-
-        language_id.change(
-            fn=on_lang_change,
-            inputs=[language_id, ref_wav, text],
-            outputs=[ref_wav, text],
-            show_progress=False
-        )
-
-    run_btn.click(
-        fn=generate_tts_audio,
-        inputs=[text, language_id, ref_wav, exaggeration, temp, seed_num, cfg_weight],
-        outputs=[audio_output, seed_output],
-    )
-
-demo.launch(mcp_server=True, share=True)