from subprocess import call
import gradio as gr
import os
from TTS.api import TTS

# List available 🐸TTS models and choose the first one
all_models = TTS.list_models()
# for model in all_models:
#     print(model)

# print("Using model: ", all_models[0])
model_name = all_models[0]
# Init TTS


print("Downloading model...", '')

voiceCloneModel = TTS('tts_models/multilingual/multi-dataset/your_tts')


def run_cmd(command):
    try:
        print(command)
        call(command)
    except KeyboardInterrupt:
        print("Process interrupted")
        sys.exit(1)


def inference(text, speaker):
    if (speaker == 'Speaker-1'):
        speaker = 'input/amitabh.mp3'
    elif (speaker == 'Speaker-2'):
        speaker = 'input/amrish.mp3'
    elif (speaker == 'Speaker-3'):
        speaker = 'input/obama.mp3'
    elif (speaker == 'Speaker-4'):
        speaker = 'input/trump.wav'
    else:
        speaker = 'input/z-default.wav'
    # print("speaker: ", speaker)
    # cmd = ['tts', '--text', text, '--out_path', 'output/tts_output.wav']
    # run_cmd(cmd)
    # Text to speech to a file
    # tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts",
    #           progress_bar=False, gpu=True)
    voiceCloneModel.tts_to_file(text, speaker_wav=speaker,
                                language="en", file_path="output/output.wav")

    # for i in range(len(tts.languages)):
    #     tts.tts_to_file(text=text,
    #                     speaker=tts.speakers[i], language=tts.languages[0], file_path='output/output-'+str(i)+'.wav')

    return 'output/output.wav'


inputs = [gr.inputs.Textbox(lines=5, label="Input Text"),
          gr.inputs.Dropdown(['Speaker-1', 'Speaker-2', 'Speaker-3',
                              'Speaker-4'], label="Model")
          ]
outputs = gr.outputs.Audio(type="filepath", label="Output Audio")
title = "Text To Speech"
description = "An example of using TTS to generate speech from text."
article = ""
examples = [
    ["This is an open-source library that generates synthetic speech"]
]
gr.Interface(
    inference,
    inputs,
    outputs,
    verbose=True,
    title=title,
    description=description,
    article=article,
    examples=examples,
    enable_queue=True,
    allow_flagging="never",

).launch(debug=True)