import tempfile
from typing import Optional
from TTS.config import load_config
import gradio as gr
import numpy as np
import os
import json
from TTS.utils.manage import ModelManager
from TTS.utils.synthesizer import Synthesizer


MAX_TXT_LEN = 800


def tts(text: str):
    if len(text) > MAX_TXT_LEN:
        text = text[:MAX_TXT_LEN]
        print(f"Input text was cutoff since it went over the {MAX_TXT_LEN} character limit.")
    print(text)

    model_path = os.getcwd() + "/best_model.pth"
    config_path = os.getcwd() + "/config.json"
   

    synthesizer = Synthesizer(
        model_path, config_path, speakers_file_path
    )


    # synthesize
    if synthesizer is None:
        raise NameError("model not found")
    wavs = synthesizer.tts(text, speaker_idx)
    # return output
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp:
        synthesizer.save_wav(wavs, fp)
        return fp.name


description="""
This is a demo of first public free persian text to speech model.
Model trained on this dataset : https://www.kaggle.com/datasets/magnoliasis/persian-tts-dataset-famale
"""
article= ""

iface = gr.Interface(
    fn=tts,
    inputs=[
        gr.inputs.Textbox(
            label="Text",
            default="زندگی فقط یک بار است؛ از آن به خوبی استفاده کن",
        )
    ],
    outputs=gr.outputs.Audio(label="Output"),
    title="🗣️Persian ttt - glow_tts 🗣️",
    theme="grass",
    description=description,
    article=article,
    allow_flagging=False,
    flagging_options=['error', 'bad-quality', 'wrong-pronounciation'],
    layout="vertical",
    live=False
)
iface.launch(share=False)