app.py

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

import gradio as gr
from docx import Document
from TTS.api import TTS
import tempfile
import zipfile

# 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"}
	}



# Return dropdown list like: "p225 - F, English"
def get_speaker_dropdown_choices():
    choices = []
    for speaker_id, meta in SPEAKER_METADATA.items():
        desc = f"p{speaker_id} - {meta['gender']}, {meta['accent']}"
        choices.append((desc, f"p{speaker_id}"))
    return choices

# Cache TTS model
MODEL_CACHE = {}

def load_tts_model():
    if VOICE_MODEL not in MODEL_CACHE:
        MODEL_CACHE[VOICE_MODEL] = TTS(model_name=VOICE_MODEL, progress_bar=False, gpu=False)
    return MODEL_CACHE[VOICE_MODEL]

def docx_to_wav(doc_file, selected_desc):
    speaker_id = next((sid for desc, sid in get_speaker_dropdown_choices() if desc == selected_desc), None)
    if not speaker_id:
        raise ValueError("Invalid speaker selection")

    tts = load_tts_model()
    document = Document(doc_file.name)
    full_text = "\n".join([para.text for para in document.paragraphs if para.text.strip()])

    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_wav:
        wav_path = tmp_wav.name

    tts.tts_to_file(text=full_text, file_path=wav_path, speaker=speaker_id)
    return wav_path


def docx_to_zipped_wavs(doc_file, selected_desc):
    speaker_id = next((sid for desc, sid in get_speaker_dropdown_choices() if desc == selected_desc), None)
    if not speaker_id:
        raise ValueError("Invalid speaker selection")

    tts = load_tts_model()
    document = Document(doc_file.name)
    paragraphs = [p.text.strip() for p in document.paragraphs if p.text.strip()]

    if not paragraphs:
        raise ValueError("No non-empty paragraphs found in the document.")

    with tempfile.TemporaryDirectory() as temp_dir:
        wav_paths = []
        for i, para in enumerate(paragraphs, start=1):
            wav_path = os.path.join(temp_dir, f"chunk_{i:02d}.wav")
            tts.tts_to_file(text=para, file_path=wav_path, speaker=speaker_id)
            wav_paths.append(wav_path)

        # Create a zip file
        zip_path = os.path.join(temp_dir, "voice_chunks.zip")
        with zipfile.ZipFile(zip_path, "w") as zipf:
            for wav in wav_paths:
                zipf.write(wav, os.path.basename(wav))

        # Copy zip to a final temp file for Gradio to return
        final_zip = tempfile.NamedTemporaryFile(suffix=".zip", delete=False)
        with open(zip_path, "rb") as src, open(final_zip.name, "wb") as dst:
            dst.write(src.read())

    return final_zip.name


# Gradio UI
with gr.Blocks() as interface:
    gr.Markdown("# 🎤 English Voice Generator from DOCX")
    gr.Markdown("Upload a `.docx` file and select a speaker to generate a WAV voiceover.")

    doc_input = gr.File(label="Upload .docx File", type="filepath")
    speaker_dropdown = gr.Dropdown(
        choices=[desc for desc, _ in get_speaker_dropdown_choices()],
        label="Select Speaker",
        value=None
    )

    generate_btn = gr.Button("Generate WAV")
    output_audio = gr.Audio(label="Generated Audio", type="filepath")

    generate_btn.click(
    fn=docx_to_zipped_wavs,
    inputs=[doc_input, speaker_dropdown],
    outputs=gr.File(label="Download ZIP of Audio Files")
)

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