import gradio as gr
import os
os.system('cd monotonic_align && python setup.py build_ext --inplace && cd ..')


import json
import math
import torch
from torch import nn
from torch.nn import functional as F
from torch.utils.data import DataLoader

import commons
import utils
from data_utils import TextAudioLoader, TextAudioCollate, TextAudioSpeakerLoader, TextAudioSpeakerCollate
from models import SynthesizerTrn
from text.symbols import symbols
from text import text_to_sequence, cleaned_text_to_sequence
from text.cleaners import japanese_cleaners
from scipy.io.wavfile import write


def get_text(text, hps):
    text_norm = text_to_sequence(text, hps.data.text_cleaners)
    if hps.data.add_blank:
        text_norm = commons.intersperse(text_norm, 0)
    text_norm = torch.LongTensor(text_norm)
    # print(text_norm.shape)
    return text_norm

hps = utils.get_hparams_from_file("/ai-koni/configs/japanese_base.json")

net_g = SynthesizerTrn(
    len(symbols),
    hps.data.filter_length // 2 + 1,
    hps.train.segment_size // hps.data.hop_length,
    **hps.model)
_ = net_g.eval()


_ = utils.load_checkpoint("/ai-koni/MyDrive/japanese_base/G_42000.pth", net_g, None)


def tts(text):
    if len(text) > 150:
        return "Error: Text is too long", None
    stn_tst = get_text(text, hps)

    with torch.no_grad():
        x_tst = stn_tst.unsqueeze(0)
        x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
        # print(stn_tst.size())
        audio = net_g.infer(x_tst, x_tst_lengths, noise_scale=.667, noise_scale_w=0.8, length_scale=2)[0][
            0, 0].data.float().numpy()
    return "Success", (hps.data.sampling_rate, audio)






app = gr.Blocks()
with app:
    with gr.Tabs():
        with gr.TabItem("AI koni"):
            tts_input1 = gr.TextArea(label="Text in Japanese (150 words limitation)", value="こんにちは。")
            # tts_input2 = gr.Dropdown(label="Speaker", choices=hps.speakers, type="index", value=hps.speakers[0])
            tts_submit = gr.Button("Generate", variant="primary")
            tts_output1 = gr.Textbox(label="Message")
            tts_output2 = gr.Audio(label="Output")
            tts_submit.click(tts, [tts_input1], [tts_output1, tts_output2])
      
    app.launch()