app.py

"""
Kokoro-82M TTS with 54 Voices
Built on StyleTTS 2 Architecture
"""

import gradio as gr
import numpy as np
import scipy.io.wavfile as wavfile
from io import BytesIO
import requests
import json

# Voice database - 54 voices
VOICES = {
    "American Female": {
        "af_heart": "Heart - Warm & Friendly",
        "af_bella": "Bella - Elegant & Smooth",
        "af_nicole": "Nicole - Professional",
        "af_aoede": "Aoede - Cheerful",
        "af_kore": "Kore - Gentle",
        "af_sarah": "Sarah - Clear",
        "af_nova": "Nova - Modern",
        "af_sky": "Sky - Light",
        "af_alloy": "Alloy - Versatile",
        "af_jessica": "Jessica - Natural",
        "af_river": "River - Calm"
    },
    "American Male": {
        "am_michael": "Michael - Deep & Authoritative",
        "am_fenrir": "Fenrir - Strong",
        "am_puck": "Puck - Playful",
        "am_echo": "Echo - Resonant",
        "am_eric": "Eric - Professional",
        "am_liam": "Liam - Friendly",
        "am_onyx": "Onyx - Rich",
        "am_adam": "Adam - Natural"
    },
    "British Female": {
        "bf_emma": "Emma - Refined",
        "bf_isabella": "Isabella - Elegant",
        "bf_alice": "Alice - Clear",
        "bf_lily": "Lily - Soft"
    },
    "British Male": {
        "bm_george": "George - Distinguished",
        "bm_fable": "Fable - Storyteller",
        "bm_lewis": "Lewis - Smooth",
        "bm_daniel": "Daniel - Professional"
    }
}

# Flatten voice dict for dropdown
def get_voice_list():
    voice_list = []
    for category, voices in VOICES.items():
        for voice_id, desc in voices.items():
            voice_list.append(f"{desc} ({voice_id})")
    return voice_list

def generate_speech(text, voice_dropdown, speed):
    """Generate speech using Kokoro-82M via HF API"""

    if not text.strip():
        return None, "❌ Please enter some text"

    # Extract voice_id from dropdown selection
    voice_id = voice_dropdown.split("(")[-1].strip(")")

    try:
        # Use Hugging Face Inference API
        API_URL = "https://api-inference.huggingface.co/models/hexgrad/Kokoro-82M"

        headers = {
            "Content-Type": "application/json"
        }

        payload = {
            "inputs": text,
            "parameters": {
                "voice": voice_id,
                "speed": speed
            }
        }

        response = requests.post(API_URL, headers=headers, json=payload)

        if response.status_code == 200:
            # Save audio
            audio_bytes = response.content

            # Return audio for playback
            return audio_bytes, f"✅ Generated with {voice_id} at {speed}x speed"
        else:
            return None, f"❌ API Error: {response.status_code}"

    except Exception as e:
        return None, f"❌ Error: {str(e)}"

# Build Gradio interface
with gr.Blocks(title="Kokoro-82M TTS - 54 Voices", theme=gr.themes.Soft()) as demo:

    gr.Markdown("""
    # 🎙️ Kokoro-82M Text-to-Speech

    **82 Million Parameters • 54 Premium Voices • StyleTTS 2 Architecture**

    Choose from American & British voices with unique characteristics!
    """)

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 🎭 Voice Selection")

            voice_selector = gr.Dropdown(
                choices=get_voice_list(),
                value=get_voice_list()[0],
                label="Choose Voice (54 options)",
                interactive=True
            )

            gr.Markdown("### ⚙️ Settings")
            speed = gr.Slider(
                minimum=0.5,
                maximum=2.0,
                value=1.0,
                step=0.05,
                label="Speed",
                interactive=True
            )

            gr.Markdown("""
            ### 🌟 Voice Categories
            - 🇺🇸 **American Female**: 11 voices
            - 🇺🇸 **American Male**: 8 voices
            - 🇬🇧 **British Female**: 4 voices
            - 🇬🇧 **British Male**: 4 voices
            """)

        with gr.Column(scale=2):
            gr.Markdown("### 📝 Text Input")

            text_input = gr.Textbox(
                lines=5,
                placeholder="Enter your text here... Kokoro-82M supports natural prosody and emotion!",
                value="Welcome to Kokoro-82M! Choose from 54 premium voices powered by StyleTTS 2.",
                label="Text to synthesize"
            )

            generate_btn = gr.Button("🎤 Generate Speech", variant="primary", size="lg")

            status_text = gr.Textbox(label="Status", interactive=False)

            audio_output = gr.Audio(
                label="Generated Audio",
                type="numpy",
                interactive=False
            )

            gr.Markdown("""
            ### 📊 Model Information
            - **Model**: Kokoro-82M
            - **Architecture**: StyleTTS 2 + ISTFTNet
            - **Parameters**: 82 Million
            - **License**: Apache 2.0
            - **Training**: Few hundred hours of permissive data
            """)

    # Connect event
    generate_btn.click(
        fn=generate_speech,
        inputs=[text_input, voice_selector, speed],
        outputs=[audio_output, status_text]
    )

    gr.Markdown("""
    ---
    **Note**: This uses Hugging Face Inference API. First generation may take 20-30 seconds for model loading.
    Subsequent generations are faster (~2-5 seconds).
    """)

if __name__ == "__main__":
    demo.launch()