import numpy as np
import torch
import gradio as gr
from TTS.api import TTS  # Import TTS library

# Placeholder for model loading and voice cloning logic
class VoiceCloner:
    def __init__(self):
        self.model = None
        self.tts = None
    
    def load_model(self, npz_file):
        data = np.load(npz_file)
        # Load your model parameters from the npz file
        # Initialize your model here with the loaded parameters
        self.model = data  # Example; replace with your actual model loading code

    def clone_voice(self, audio_file):
        # Implement the logic to clone voice from the uploaded audio file
        return audio_file  # Placeholder; return processed audio

    def load_tts_model(self):
        # Load a pretrained TTS model
        self.tts = TTS(model_name="tts_models/en/ljspeech/glow-tts")  # You can choose a different model if needed

    def text_to_speech(self, text):
        # Use the loaded TTS model to convert text to speech
        if self.tts is not None:
            output_audio = self.tts.tts(text)
            return output_audio  # Return the generated audio
        else:
            return "TTS model not loaded!"

# Create the Gradio interface
def create_interface():
    cloner = VoiceCloner()
    
    with gr.Blocks() as demo:
        gr.Markdown("## Voice Cloning and TTS Application")

        # User uploads their .npz file
        npz_file = gr.File(label="Upload Your .npz Voice Model")
        audio_input = gr.Audio(source="upload", type="filepath", label="Upload Original Audio")
        text_input = gr.Textbox(label="Text Input for TTS")
        
        output_audio = gr.Audio(label="Cloned Voice Output or TTS Output")

        upload_button = gr.Button("Load Model")
        
        # Button to clone voice
        clone_button = gr.Button("Clone Voice")
        
        # Button to convert text to speech
        tts_button = gr.Button("Convert Text to Speech")
        
        # Load the model when the user uploads the .npz file
        def load_and_initialize(npz):
            cloner.load_model(npz.name)  # Use the file path to load the model
            cloner.load_tts_model()  # Load the TTS model
            return "Model Loaded!"

        upload_button.click(fn=load_and_initialize, inputs=npz_file, outputs="text")

        # Clone the voice when the button is pressed
        clone_button.click(fn=cloner.clone_voice, inputs=audio_input, outputs=output_audio)
        
        # Convert text to speech when the button is pressed
        tts_button.click(fn=cloner.text_to_speech, inputs=text_input, outputs=output_audio)

    return demo

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