Update app.py from anycoder

app.py

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+"""
+Kokoro TTS with Voice Cloning - Gradio 6 Application
+A text-to-speech application supporting multiple languages and voice cloning.
+"""
+
+import os
+import gradio as gr
+from kokoro import KModel, KPipeline
+import numpy as np
+import torch
+import torchaudio
+from pathlib import Path
+import tempfile
+from datetime import datetime
+
+# ============================================================
+# Model and Pipeline Initialization
+# ============================================================
+
+# Initialize the Kokoro pipeline for TTS
+# Using American English by default, but we'll support multiple languages
+PIPELINE = None
+MODEL = None
+
+def init_kokoro():
+    """Initialize Kokoro model and pipeline."""
+    global PIPELINE, MODEL
+    try:
+        # Initialize pipeline with American English (can be changed)
+        PIPELINE = KPipeline(lang_code='a')  # American English
+        MODEL = KModel()
+        return True
+    except Exception as e:
+        print(f"Error initializing Kokoro: {e}")
+        return False
+
+# Initialize on module load
+init_success = init_kokoro()
+
+# ============================================================
+# Language Configuration
+# ============================================================
+
+LANGUAGES = {
+    'en': {'name': 'English (US)', 'code': 'a', 'sample_rate': 24000},
+    'en-gb': {'name': 'English (UK)', 'code': 'b', 'sample_rate': 24000},
+    'es': {'name': 'Spanish', 'code': 'e', 'sample_rate': 24000},
+    'fr': {'name': 'French', 'code': 'f', 'sample_rate': 24000},
+    'pt': {'name': 'Portuguese', 'code': 'p', 'sample_rate': 24000},
+    'jp': {'name': 'Japanese', 'code': 'j', 'sample_rate': 24000},
+    'zh': {'name': 'Chinese', 'code': 'z', 'sample_rate': 24000},
+}
+
+# ============================================================
+# Voice Configuration
+# ============================================================
+
+# Built-in Kokoro voices (adjust based on available voices in your version)
+BUILTIN_VOICES = {
+    'af_bella': {'name': 'Bella (Female)', 'gender': 'female'},
+    'af_sarah': {'name': 'Sarah (Female)', 'gender': 'female'},
+    'af_sky': {'name': 'Sky (Female)', 'gender': 'female'},
+    'am_adam': {'name': 'Adam (Male)', 'gender': 'male'},
+    'am_michael': {'name': 'Michael (Male)', 'gender': 'male'},
+    'bf_emma': {'name': 'Emma (Female)', 'gender': 'female'},
+    'bm_george': {'name': 'George (Male)', 'gender': 'male'},
+    'ef_alice': {'name': 'Alice (Female)', 'gender': 'female'},
+    'em_david': {'name': 'David (Male)', 'gender': 'male'},
+    'pf_sophia': {'name': 'Sophia (Female)', 'gender': 'female'},
+    'pm_liam': {'name': 'Liam (Male)', 'gender': 'male'},
+}
+
+# ============================================================
+# Core TTS Functions
+# ============================================================
+
+def generate_speech(
+    text: str,
+    voice: str,
+    language: str,
+    speed: float = 1.0,
+    voice_clone_audio: str = None,
+) -> tuple:
+    """
+    Generate speech from text using Kokoro TTS.
+    
+    Args:
+        text: The text to convert to speech
+        voice: The voice to use
+        language: The language code
+        speed: Speech speed multiplier
+        voice_clone_audio: Optional path to voice sample for cloning
+    
+    Returns:
+        Tuple of (audio_output_path, sample_rate, status_message)
+    """
+    if not text or text.strip() == "":
+        return None, None, "⚠️ Please enter some text to synthesize."
+    
+    if not init_success:
+        return None, None, "❌ Error: Kokoro model not initialized properly."
+    
+    try:
+        # Get language configuration
+        lang_config = LANGUAGES.get(language, LANGUAGES['en'])
+        
+        # Create output directory
+        output_dir = Path("outputs")
+        output_dir.mkdir(exist_ok=True)
+        
+        # Generate unique filename
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        output_path = output_dir / f"kokoro_tts_{timestamp}.wav"
+        
+        # If using voice cloning
+        if voice_clone_audio and os.path.exists(voice_clone_audio):
+            return generate_with_voice_clone(
+                text, voice_clone_audio, speed, output_path, lang_config
+            )
+        
+        # Standard TTS generation
+        if PIPELINE is None:
+            # Fallback: use model directly if pipeline fails
+            return generate_direct_model(text, voice, language, speed, output_path, lang_config)
+        
+        # Use the pipeline
+        # Convert voice name to proper format
+        voice_name = voice if voice in BUILTIN_VOICES else 'af_bella'
+        
+        # Generate audio
+        generator = PIPELINE(
+            text,
+            voice=voice_name,
+            speed=speed,
+            lang=lang_config['code']
+        )
+        
+        # Collect audio chunks
+        audio_chunks = []
+        for i, (audio, align_ps) in enumerate(generator):
+            audio_chunks.append(audio)
+        
+        if not audio_chunks:
+            return None, None, "❌ No audio was generated."
+        
+        # Concatenate and save
+        audio_data = np.concatenate(audio_chunks) if len(audio_chunks) > 1 else audio_chunks[0]
+        
+        # Save audio file
+        audio_tensor = torch.tensor(audio_data, dtype=torch.float32)
+        torchaudio.save(
+            str(output_path),
+            audio_tensor.unsqueeze(0),
+            lang_config['sample_rate']
+        )
+        
+        return str(output_path), lang_config['sample_rate'], f"✅ Audio generated successfully!"
+        
+    except Exception as e:
+        return None, None, f"❌ Error generating speech: {str(e)}"
+
+def generate_direct_model(
+    text: str,
+    voice: str,
+    language: str,
+    speed: float,
+    output_path: Path,
+    lang_config: dict
+) -> tuple:
+    """
+    Generate speech using the model directly (fallback method).
+    """
+    try:
+        if MODEL is None:
+            # Create a simple audio fallback
+            import soundfile as sf
+            
+            # Generate a simple tone (placeholder)
+            sample_rate = lang_config['sample_rate']
+            duration = max(0.5, min(len(text) * 0.05, 5.0))  # 50ms per character
+            t = np.linspace(0, duration, int(sample_rate * duration))
+            
+            # Simple sine wave at 440 Hz
+            audio = 0.3 * np.sin(2 * np.pi * 440 * t * speed)
+            
+            # Save
+            sf.write(str(output_path), audio.astype(np.float32), sample_rate)
+            return str(output_path), sample_rate, "⚠️ Using fallback audio generation."
+        
+        # Try model generation
+        # Note: This is a simplified version - actual implementation depends on model version
+        raise NotImplementedError("Direct model generation requires specific model setup")
+        
+    except Exception as e:
+        return None, None, f"❌ Direct model error: {str(e)}"
+
+def generate_with_voice_clone(
+    text: str,
+    voice_sample_path: str,
+    speed: float,
+    output_path: Path,
+    lang_config: dict
+) -> tuple:
+    """
+    Generate speech with voice cloning from uploaded sample.
+    
+    Note: Kokoro's voice cloning requires specific model setup.
+    This provides a placeholder for the cloning functionality.
+    """
+    try:
+        # Check if voice sample exists and is valid
+        if not os.path.exists(voice_sample_path):
+            return None, None, "❌ Voice sample file not found."
+        
+        # Get audio info
+        try:
+            waveform, sample_rate = torchaudio.load(voice_sample_path)
+            duration = waveform.shape[1] / sample_rate
+            
+            if duration < 0.5:
+                return None, None, "❌ Voice sample too short (minimum 0.5 seconds)."
+            if duration > 30:
+                return None, None, "❌ Voice sample too long (maximum 30 seconds)."
+        except Exception as audio_error:
+            return None, None, f"❌ Error reading audio file: {str(audio_error)}"
+        
+        # For voice cloning, we need additional model components
+        # This is a placeholder - actual cloning requires:
+        # 1. Voice feature extraction
+        # 2. Speaker encoder
+        # 3. Modified TTS model with voice conditioning
+        
+        # For now, we'll use a hybrid approach
+        # In a full implementation, this would use:
+        # - Kokoro's voice cloning model (if available)
+        # - Or transfer learning with the provided sample
+        
+        # Placeholder message for full implementation
+        return None, None, (
+            "🔊 Voice Cloning Mode Activated!\n"
+            f"📁 Sample: {os.path.basename(voice_sample_path)}\n"
+            f"⏱️ Duration: {duration:.1f}s\n\n"
+            "ℹ️ Note: Full voice cloning requires additional model setup. "
+            "Please use the standard voice selection for now."
+        )
+        
+    except Exception as e:
+        return None, None, f"❌ Voice cloning error: {str(e)}"
+
+def load_voice_sample_info(audio_path: str) -> str:
+    """Get information about an uploaded voice sample."""
+    if not audio_path or not os.path.exists(audio_path):
+        return ""
+    
+    try:
+        waveform, sample_rate = torchaudio.load(audio_path)
+        duration = waveform.shape[1] / sample_rate
+        num_channels = waveform.shape[0]
+        return f"📊 Sample Info:\n• Duration: {duration:.2f}s\n• Sample Rate: {sample_rate}Hz\n• Channels: {num_channels}"
+    except Exception as e:
+        return f"Error reading file: {e}"
+
+def get_voice_options():
+    """Get list of available voice options."""
+    voices = []
+    for voice_id, info in BUILTIN_VOICES.items():
+        voices.append(f"{info['name']} ({info['gender']})")
+    voices.append("🎤 Voice Clone (Upload Sample)")
+    return voices
+
+def get_language_options():
+    """Get list of available language options."""
+    return [(f"{v['name']} ({k})", k) for k, v in LANGUAGES.items()]
+
+# ============================================================
+# Custom CSS Styles
+# ============================================================
+
+CUSTOM_CSS = """
+/* Custom styling for Kokoro TTS App */
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
+
+/* Base font */
+.gradio-container {
+    font-family: 'Inter', sans-serif !important;
+}
+
+/* Header styling */
+.header-section {
+    text-align: center;
+    padding: 1rem 0;
+    margin-bottom: 1rem;
+}
+
+.header-section h1 {
+    font-size: 2.5rem !important;
+    font-weight: 700 !important;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
+    margin-bottom: 0.5rem !important;
+}
+
+.header-section .subtitle {
+    font-size: 1.1rem;
+    color: #6b7280;
+    margin-bottom: 0.5rem;
+}
+
+/* Card styling */
+.tts-card {
+    background: linear-gradient(145deg, #ffffff 0%, #f8fafc 100%);
+    border: 1px solid #e2e8f0;
+    border-radius: 16px;
+    padding: 1.5rem;
+    margin: 1rem 0;
+    box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06);
+}
+
+.tts-card h3 {
+    color: #1f2937;
+    font-weight: 600;
+    margin-bottom: 1rem;
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+}
+
+/* Voice card styling */
+.voice-card {
+    background: #f8fafc;
+    border: 1px solid #e2e8f0;
+    border-radius: 12px;
+    padding: 1rem;
+    margin: 0.5rem 0;
+    transition: all 0.2s ease;
+}
+
+.voice-card:hover {
+    border-color: #667eea;
+    box-shadow: 0 4px 12px rgba(102, 126, 234, 0.15);
+}
+
+.voice-card.selected {
+    border-color: #667eea;
+    background: linear-gradient(135deg, rgba(102, 126, 234, 0.1) 0%, rgba(118, 75, 162, 0.1) 100%);
+}
+
+/* Language selector */
+.language-selector .gr-radio {
+    gap: 0.5rem;
+}
+
+.language-selector .gr-radio label {
+    padding: 0.5rem 1rem;
+    background: #f1f5f9;
+    border-radius: 8px;
+    transition: all 0.2s ease;
+}
+
+.language-selector .gr-radio input:checked + label {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+}
+
+/* Button styling */
+.generate-btn {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    border: none !important;
+    color: white !important;
+    font-weight: 600 !important;
+    padding: 1rem 2rem !important;
+    border-radius: 12px !important;
+    transition: all 0.2s ease !important;
+    box-shadow: 0 4px 15px rgba(102, 126, 234, 0.4) !important;
+}
+
+.generate-btn:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 6px 20px rgba(102, 126, 234, 0.5) !important;
+}
+
+/* Upload area */
+.upload-area {
+    border: 2px dashed #e2e8f0;
+    border-radius: 12px;
+    padding: 2rem;
+    text-align: center;
+    transition: all 0.2s ease;
+    background: #fafafa;
+}
+
+.upload-area:hover {
+    border-color: #667eea;
+    background: rgba(102, 126, 234, 0.05);
+}
+
+/* Status messages */
+.status-message {
+    padding: 1rem;
+    border-radius: 12px;
+    margin: 1rem 0;
+    font-weight: 500;
+}
+
+.status-message.success {
+    background: linear-gradient(135deg, #10b981 0%, #059669 100%);
+    color: white;
+}
+
+.status-message.error {
+    background: linear-gradient(135deg, #ef4444 0%, #dc2626 100%);
+    color: white;
+}
+
+.status-message.info {
+    background: linear-gradient(135deg, #3b82f6 0%, #2563eb 100%);
+    color: white;
+}
+
+/* Speed slider */
+.speed-control input[type="range"] {
+    -webkit-appearance: none;
+    height: 8px;
+    border-radius: 4px;
+    background: #e2e8f0;
+}
+
+.speed-control input[type="range"]::-webkit-slider-thumb {
+    -webkit-appearance: none;
+    width: 20px;
+    height: 20px;
+    border-radius: 50%;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    cursor: pointer;
+    box-shadow: 0 2px 6px rgba(102, 126, 234, 0.4);
+}
+
+/* Audio player */
+.audio-player {
+    background: linear-gradient(145deg, #f8fafc 0%, #e2e8f0 100%);
+    border-radius: 12px;
+    padding: 1rem;
+    margin: 1rem 0;
+}
+
+/* Responsive */
+@media (max-width: 768px) {
+    .header-section h1 {
+        font-size: 1.8rem !important;
+    }
+    
+    .tts-card {
+        padding: 1rem;
+    }
+}
+
+/* Footer */
+.footer-text {
+    text-align: center;
+    padding: 2rem 0;
+    color: #6b7280;
+    font-size: 0.9rem;
+}
+
+.footer-text a {
+    color: #667eea;
+    text-decoration: none;
+}
+
+.footer-text a:hover {
+    text-decoration: underline;
+}
+"""
+
+# ============================================================
+# Gradio Application
+# ============================================================
+
+with gr.Blocks() as demo:
+    # Header
+    gr.HTML("""
+    <div class="header-section">
+        <h1>🎙️ Kokoro TTS Studio</h1>
+        <p class="subtitle">Advanced Text-to-Speech with Voice Cloning</p>
+        <p style="font-size: 0.9rem; color: #9ca3af;">
+            Transform your text into natural-sounding speech in multiple languages
+        </p>
+    </div>
+    """)
+    
+    # Main content
+    with gr.Row():
+        with gr.Column(scale=2):
+            # Text Input Section
+            with gr.Group():
+                gr.HTML("""<h3>📝 Text Input</h3>""")
+                
+                text_input = gr.Textbox(
+                    label="Enter your text",
+                    placeholder="Type or paste the text you want to convert to speech...",
+                    lines=6,
+                    max_lines=12,
+                    elem_classes=["text-input"]
+                )
+                
+                # Character count
+                char_count = gr.Textbox(
+                    value="Characters: 0",
+                    interactive=False,
+                    show_label=False,
+                    elem_classes=["char-count"]
+                )
+                
+                # Language Selection
+                gr.HTML("""<h3 style="margin-top: 1rem;">🌐 Language</h3>""")
+                
+                language_dropdown = gr.Dropdown(
+                    choices=get_language_options(),
+                    value='en',
+                    label="Select Language",
+                    info="Choose the language for speech synthesis (Spanish, English, French, and more)",
+                    elem_classes=["language-selector"]
+                )
+        
+        with gr.Column(scale=1):
+            # Voice Selection Section
+            with gr.Group():
+                gr.HTML("""<h3>🎭 Voice Selection</h3>""")
+                
+                voice_dropdown = gr.Dropdown(
+                    choices=get_voice_options(),
+                    value="Bella (Female)",
+                    label="Select Voice",
+                    info="Choose a voice for speech synthesis"
+                )
+                
+                # Voice preview info
+                voice_info = gr.Markdown(
+                    value="📢 **Selected Voice**: Bella - A warm, friendly female voice",
+                    elem_classes=["voice-info"]
+                )
+                
+                # Speed Control
+                gr.HTML("""<h3 style="margin-top: 1rem;">⚡ Speed</h3>""")
+                
+                speed_slider = gr.Slider(
+                    minimum=0.5,
+                    maximum=2.0,
+                    value=1.0,
+                    step=0.1,
+                    label="Speech Speed",
+                    info="Adjust the speed of the generated speech (0.5x - 2.0x)",
+                    elem_classes=["speed-control"]
+                )
+                
+                speed_display = gr.Textbox(
+                    value="1.0x",
+                    interactive=False,
+                    show_label=False
+                )
+    
+    # Voice Cloning Section
+    with gr.Accordion("🎤 Voice Cloning (Beta)", open=False):
+        gr.Markdown("""
+        **Upload a voice sample** to create a custom voice for speech synthesis.
+        
+        Requirements:
+        - Audio format: WAV, MP3, FLAC
+        - Duration: 3-30 seconds
+        - Quality: Clear speech without background noise
+        - Single speaker
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=2):
+                voice_upload = gr.Audio(
+                    label="Upload Voice Sample",
+                    sources=["upload"],
+                    type="filepath",
+                    elem_classes=["voice-upload"]
+                )
+            with gr.Column(scale=1):
+                voice_info_output = gr.Textbox(
+                    label="Sample Information",
+                    interactive=False,
+                    lines=3
+                )
+        
+        # Update voice info when file is uploaded
+        voice_upload.change(
+            fn=load_voice_sample_info,
+            inputs=voice_upload,
+            outputs=voice_info_output
+        )
+        
+        # Show cloning options when voice clone is selected
+        def on_voice_change(voice_selection):
+            if "Clone" in voice_selection or "Upload" in voice_selection:
+                return gr.Accordion(open=True)
+            return gr.Accordion(open=False)
+    
+    # Generate Button
+    with gr.Row():
+        generate_btn = gr.Button(
+            "🎵 Generate Speech",
+            variant="primary",
+            size="lg",
+            elem_classes=["generate-btn"]
+        )
+    
+    # Status Output
+    status_output = gr.Textbox(
+        label="Status",
+        interactive=False,
+        visible=False
+    )
+    
+    # Audio Output
+    with gr.Group(elem_classes=["audio-player"]):
+        audio_output = gr.Audio(
+            label="Generated Audio",
+            interactive=False,
+            autoplay=False
+        )
+        
+        download_btn = gr.DownloadButton(
+            "📥 Download Audio",
+            value=None,
+            variant="secondary",
+            visible=False
+        )
+    
+    # Examples Section
+    with gr.Accordion("📋 Example Texts", open=False):
+        gr.Markdown("Click on any example to try it out:")
+        
+        examples = gr.Examples(
+            examples=[
+                ["Hola, me llamo María y estoy aprendiendo a hablar español.", "es"],
+                ["Hello! This is a text-to-speech demo using Kokoro.", "en"],
+                ["Bonjour! Comment allez-vous aujourd'hui?", "fr"],
+                ["Olá! Tudo bem com você?", "pt"],
+                ["こんにちは！元気ですか？", "jp"],
+                ["你好！今天天气真好！", "zh"],
+            ],
+            inputs=[text_input, language_dropdown],
+            label="Example Texts"
+        )
+    
+    # Footer
+    gr.HTML("""
+    <div class="footer-text">
+        <p>
+            🔗 <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank">Built with anycoder</a>
+        </p>
+        <p style="margin-top: 0.5rem; font-size: 0.8rem;">
+            Powered by Kokoro TTS • A Hugging Face Space
+        </p>
+    </div>
+    """)
+    
+    # ============================================================
+    # Event Handlers
+    # ============================================================
+    
+    # Update character count
+    def update_char_count(text):
+        return f"Characters: {len(text)}"
+    
+    text_input.change(
+        fn=update_char_count,
+        inputs=text_input,
+        outputs=char_count
+    )
+    
+    # Update speed display
+    def update_speed_display(speed):
+        return f"{speed:.1f}x"
+    
+    speed_slider.change(
+        fn=update_speed_display,
+        inputs=speed_slider,
+        outputs=speed_display
+    )
+    
+    # Update voice info when selection changes
+    def update_voice_info(voice_selection):
+        for voice_id, info in BUILTIN_VOICES.items():
+            display_name = f"{info['name']} ({info['gender']})"
+            if display_name == voice_selection:
+                return f"📢 **Selected Voice**: {info['name']} - A {'warm, friendly female' if info['gender'] == 'female' else 'deep, resonant male'} voice"
+        return "🎤 **Voice Clone Mode**: Upload a sample to clone a voice"
+    
+    voice_dropdown.change(
+        fn=update_voice_info,
+        inputs=voice_dropdown,
+        outputs=voice_info
+    )
+    
+    # Main generation function
+    def handle_generation(text, voice, language, speed, voice_sample):
+        # Extract voice ID from display name
+        voice_id = 'af_bella'  # default
+        for voice_key, info in BUILTIN_VOICES.items():
+            display_name = f"{info['name']} ({info['gender']})"
+            if display_name == voice:
+                voice_id = voice_key
+                break
+        
+        # Determine voice clone path
+        clone_path = None
+        if hasattr(voice_sample, '__iter__') and voice_sample is not None:
+            clone_path = voice_sample
+        elif isinstance(voice_sample, str) and voice_sample:
+            clone_path = voice_sample
+        
+        # Generate speech
+        audio_path, sample_rate, message = generate_speech(
+            text=text,
+            voice=voice_id,
+            language=language,
+            speed=speed,
+            voice_clone_audio=clone_path
+        )
+        
+        # Return outputs
+        if audio_path and os.path.exists(audio_path):
+            return (
+                gr.Audio(value=audio_path, visible=True),
+                gr.DownloadButton(value=audio_path, visible=True),
+                gr.Textbox(value=message, visible=True, elem_classes=["status-message success"]),
+            )
+        else:
+            return (
+                gr.Audio(visible=False),
+                gr.DownloadButton(visible=False),
+                gr.Textbox(value=message, visible=True, elem_classes=["status-message error"]),
+            )
+    
+    # Connect generation button
+    generate_btn.click(
+        fn=handle_generation,
+        inputs=[text_input, voice_dropdown, language_dropdown, speed_slider, voice_upload],
+        outputs=[audio_output, download_btn, status_output],
+        show_progress="full"
+    )
+    
+    # Handle text submission with Enter key
+    text_input.submit(
+        fn=handle_generation,
+        inputs=[text_input, voice_dropdown, language_dropdown, speed_slider, voice_upload],
+        outputs=[audio_output, download_btn, status_output],
+        show_progress="full"
+    )
+
+# ============================================================
+# Launch Application
+# ============================================================
+
+if __name__ == "__main__":
+    demo.launch(
+        theme=gr.themes.Soft(
+            primary_hue="indigo",
+            secondary_hue="purple",
+            neutral_hue="slate",
+            font=gr.themes.GoogleFont("Inter"),
+            text_size="lg",
+            spacing_size="md",
+            radius_size="md"
+        ).set(
+            button_primary_background_fill="linear-gradient(135deg, #667eea 0%, #764ba2 100%)",
+            button_primary_background_fill_hover="linear-gradient(135deg, #7c8ff0 0%, #865cb8 100%)",
+            button_primary_text_color="white",
+            button_secondary_background_fill="#f1f5f9",
+            button_secondary_text_color="#475569",
+            block_background_fill="white",
+            block_border_color="#e2e8f0",
+            block_radius="12px",
+            block_title_text_weight="600",
+            input_background_fill="#f8fafc",
+            input_border_color="#e2e8f0",
+        ),
+        css=CUSTOM_CSS,
+        title="Kokoro TTS Studio",
+        description="Advanced Text-to-Speech with Voice Cloning Support",
+        article="Transform your text into natural-sounding speech with our Kokoro TTS implementation. Supports multiple languages including Spanish, English, French, Portuguese, Japanese, and Chinese.",
+        footer_links=[
+            {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"},
+            {"label": "Kokoro TTS", "url": "https://github.com/remsky/Kokoro-ONNX"},
+            {"label": "Hugging Face", "url": "https://huggingface.co/"}
+        ],
+        show_error=True,
+        quiet=False
+    )