app.py

import os
os.environ["NUMBA_DISABLE_CACHE"] = "1"

import os
import gradio as gr
from docx import Document
from TTS.api import TTS
import tempfile
import zipfile
from io import BytesIO
import re

from pydub import AudioSegment

final_audio = AudioSegment.empty()

from pydub import AudioSegment
from bark import generate_audio  # Importing Bark




# Voice model
VOICE_MODEL = "tts_models/en/vctk/vits"

# Embedded metadata (from your file)
SPEAKER_METADATA = {
	    300: { "age": 23, "gender": "F", "accent": "American"},
	    271: { "age": 19, "gender": "M", "accent": "Scottish"},
	    287: { "age": 23, "gender": "M", "accent": "English"},
	    262: { "age": 23, "gender": "F", "accent": "Scottish"},
	    284: { "age": 20, "gender": "M", "accent": "Scottish"},
	    297: { "age": 20, "gender": "F", "accent": "American"},
	    227: { "age": 38, "gender": "M", "accent": "English"},
	    246: { "age": 22, "gender": "M", "accent": "Scottish"},
	    225: { "age": 23, "gender": "F", "accent": "English"},
	    259: { "age": 23, "gender": "M", "accent": "English"},
	    252: { "age": 22, "gender": "M", "accent": "Scottish"},
	    231: { "age": 23, "gender": "F", "accent": "English"},
	    266: { "age": 22, "gender": "F", "accent": "Irish"},
	    241: { "age": 21, "gender": "M", "accent": "Scottish"},
	    312: { "age": 19, "gender": "F", "accent": "Canadian"},
	    329: { "age": 23, "gender": "F", "accent": "American"},
	    232: { "age": 23, "gender": "M", "accent": "English"},
	    305: { "age": 19, "gender": "F", "accent": "American"},
	    311: { "age": 21, "gender": "M", "accent": "American"},
	    301: { "age": 23, "gender": "F", "accent": "American"},
	    304: { "age": 22, "gender": "M", "accent": "NorthernIrish"},
	    310: { "age": 21, "gender": "F", "accent": "American"},
	    260: { "age": 21, "gender": "M", "accent": "Scottish"},
	    315: { "age": 18, "gender": "M", "accent": "American"},
	    374: { "age": 28, "gender": "M", "accent": "Australian"},
	    364: { "age": 23, "gender": "M", "accent": "Irish"},
	    269: { "age": 20, "gender": "F", "accent": "English"},
	    345: { "age": 22, "gender": "M", "accent": "American"},
	    326: { "age": 26, "gender": "M", "accent": "Australian"},
	    343: { "age": 27, "gender": "F", "accent": "Canadian"},
	    230: { "age": 22, "gender": "F", "accent": "English"},
	    376: { "age": 22, "gender": "M", "accent": "Indian"},
	    240: { "age": 21, "gender": "F", "accent": "English"},
	    298: { "age": 19, "gender": "M", "accent": "Irish"},
	    272: { "age": 23, "gender": "M", "accent": "Scottish"},
	    248: { "age": 23, "gender": "F", "accent": "Indian"},
	    264: { "age": 23, "gender": "F", "accent": "Scottish"},
	    250: { "age": 22, "gender": "F", "accent": "English"},
	    292: { "age": 23, "gender": "M", "accent": "NorthernIrish"},
	    237: { "age": 22, "gender": "M", "accent": "Scottish"},
	    363: { "age": 22, "gender": "M", "accent": "Canadian"},
	    313: { "age": 24, "gender": "F", "accent": "Irish"},
	    285: { "age": 21, "gender": "M", "accent": "Scottish"},
	    268: { "age": 23, "gender": "F", "accent": "English"},
	    302: { "age": 20, "gender": "M", "accent": "Canadian"},
	    261: { "age": 26, "gender": "F", "accent": "NorthernIrish"},
	    336: { "age": 18, "gender": "F", "accent": "SouthAfrican"},
	    288: { "age": 22, "gender": "F", "accent": "Irish"},
	    226: { "age": 22, "gender": "M", "accent": "English"},
	    277: { "age": 23, "gender": "F", "accent": "English"},
	    360: { "age": 19, "gender": "M", "accent": "American"},
	    257: { "age": 24, "gender": "F", "accent": "English"},
	    254: { "age": 21, "gender": "M", "accent": "English"},
	    339: { "age": 21, "gender": "F", "accent": "American"},
	    323: { "age": 19, "gender": "F", "accent": "SouthAfrican"},
	    255: { "age": 19, "gender": "M", "accent": "Scottish"},
	    249: { "age": 22, "gender": "F", "accent": "Scottish"},
	    293: { "age": 22, "gender": "F", "accent": "NorthernIrish"},
	    244: { "age": 22, "gender": "F", "accent": "English"},
	    245: { "age": 25, "gender": "M", "accent": "Irish"},
	    361: { "age": 19, "gender": "F", "accent": "American"},
	    314: { "age": 26, "gender": "F", "accent": "SouthAfrican"},
	    308: { "age": 18, "gender": "F", "accent": "American"},
	    229: { "age": 23, "gender": "F", "accent": "English"},
	    341: { "age": 26, "gender": "F", "accent": "American"},
	    275: { "age": 23, "gender": "M", "accent": "Scottish"},
	    263: { "age": 22, "gender": "M", "accent": "Scottish"},
	    253: { "age": 22, "gender": "F", "accent": "Welsh"},
	    299: { "age": 25, "gender": "F", "accent": "American"},
	    316: { "age": 20, "gender": "M", "accent": "Canadian"},
	    282: { "age": 23, "gender": "F", "accent": "English"},
	    362: { "age": 29, "gender": "F", "accent": "American"},
	    294: { "age": 33, "gender": "F", "accent": "American"},
	    274: { "age": 22, "gender": "M", "accent": "English"},
	    279: { "age": 23, "gender": "M", "accent": "English"},
	    281: { "age": 29, "gender": "M", "accent": "Scottish"},
	    286: { "age": 23, "gender": "M", "accent": "English"},
	    258: { "age": 22, "gender": "M", "accent": "English"},
	    247: { "age": 22, "gender": "M", "accent": "Scottish"},
	    351: { "age": 21, "gender": "F", "accent": "NorthernIrish"},
	    283: { "age": 24, "gender": "F", "accent": "Irish"},
	    334: { "age": 18, "gender": "M", "accent": "American"},
	    333: { "age": 19, "gender": "F", "accent": "American"},
	    295: { "age": 23, "gender": "F", "accent": "Irish"},
	    330: { "age": 26, "gender": "F", "accent": "American"},
	    335: { "age": 25, "gender": "F", "accent": "NewZealand"},
	    228: { "age": 22, "gender": "F", "accent": "English"},
	    267: { "age": 23, "gender": "F", "accent": "English"},
	    273: { "age": 18, "gender": "F", "accent": "English"}
	}



# Bark prompts (example)
BARK_PROMPTS = [
    "Shy girl",
    "Old man",
    "Excited child",
    "Angry woman"
]

def list_speaker_choices(metadata):
    """Helper function to list speakers from metadata (for VCTK and Coqui)"""
    return [f"Speaker {sid} | {meta['gender']} | {meta['accent']}" for sid, meta in SPEAKER_METADATA.items()]

def get_speaker_id_from_label(label):
    """Extract speaker ID from label string"""
    return label.split('|')[0].strip()

def generate_audio(sample_text, speaker_label, engine):
    """Generate audio based on engine choice"""
    speaker_id = get_speaker_id_from_label(speaker_label)
    model = None

    # Engine selection logic
    if engine == "bark":
        model = TTS("bark_model_path")  # Replace with actual path for Bark model
    elif engine == "coqui":
        model = TTS("tts_models/multilingual/multi-dataset/xtts_v2")  # Replace with actual path for Coqui model
    elif engine == "vctk":
        model = TTS(VOICE_MODEL)  # Replace with actual path for VCTK model

    # Temporary file creation for output audio
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_wav:
        model.tts_to_file(text=sample_text, speaker="p"+speaker_id, file_path=tmp_wav.name)
        return tmp_wav.name

# --- UI Components ---
with gr.Blocks() as demo:
    gr.Markdown("## 📄 TTS Voice Generator with Multiple Engines")
    
    # Engine dropdown
    engine_dropdown = gr.Dropdown(
        label="Select TTS Engine", 
        choices=["bark", "coqui", "vctk"], 
        value="vctk"
    )

    # Speaker/Prompt dropdown (dynamic)
    speaker_dropdown = gr.Dropdown(label="Select Speaker", visible=False)
    prompt_dropdown = gr.Dropdown(label="Select Prompt", visible=False)

    # Sample text box
    sample_textbox = gr.Textbox(label="Enter Sample Text (Max 500 characters)", max_lines=5)
    sample_audio = gr.Audio(label="Sample Output Audio", type="filepath")
    
    # Define metadata choices for speakers (Coqui and VCTK)
    speaker_choices_vctk_coqui = list_speaker_choices(SPEAKER_METADATA)
    speaker_dropdown.choices = speaker_choices_vctk_coqui  # Use metadata for VCTK/Coqui speakers

    # Define Bark prompts (choose from predefined prompts)
    prompt_dropdown.choices = BARK_PROMPTS
    
    # Dynamically update dropdown visibility based on engine selection
    def update_dropdowns(engine):
        if engine == "bark":
            speaker_dropdown.visible = False
            prompt_dropdown.visible = True
        elif engine == "coqui" or engine == "vctk":
            speaker_dropdown.visible = True
            prompt_dropdown.visible = False
        return gr.update(visible=speaker_dropdown.visible), gr.update(visible=prompt_dropdown.visible)

    # Trigger dropdown visibility changes
    engine_dropdown.change(update_dropdowns, inputs=engine_dropdown, outputs=[speaker_dropdown, prompt_dropdown])

    # Button to generate audio from sample text
    generate_button = gr.Button("Generate Audio")
    generate_button.click(
        fn=generate_audio, 
        inputs=[sample_textbox, speaker_dropdown, engine_dropdown], 
        outputs=[sample_audio]
    )

    # Button to clear the sample text and audio
    def clear_sample():
        return "", None

    clear_button = gr.Button("Clear")
    clear_button.click(fn=clear_sample, inputs=[], outputs=[sample_textbox, sample_audio])


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