import spaces
import tempfile
import wave
import gradio as gr
import os
from whisperspeech.pipeline import Pipeline
import torch
import soundfile as sf
import numpy as np
import torch.nn.functional as F
from whisperspeech.languages import LANGUAGES
from whisperspeech.pipeline import Pipeline
from whisperspeech.utils import resampler

title = """# 🙋🏻‍♂️ Welcome to🌟Tonic's🌬️💬📝WhisperSpeech

You can use this ZeroGPU Space to test out the current model [🌬️💬📝collabora/whisperspeech](https://huggingface.co/collabora/whisperspeech). 🌬️💬📝collabora/whisperspeech is An Open Source text-to-speech system built by inverting Whisper. Previously known as spear-tts-pytorch. It's like Stable Diffusion but for speech – both powerful and easily customizable.
You can also use 🌬️💬📝WhisperSpeech by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/laion-whisper?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> 
Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻  [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [Poly](https://github.com/tonic-ai/poly) 🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
"""

@spaces.GPU
def whisper_speech_demo(text, lang, speaker_audio, mix_lang, mix_text):
    print(f"Text: {text}, Lang: {lang}, Speaker Audio: {speaker_audio}, Mix Lang: {mix_lang}, Mix Text: {mix_text}")
    pipe = Pipeline()
    speaker_url = speaker_audio if speaker_audio is not None else None

    if mix_lang and mix_text:
        mixed_langs = mix_lang 
        mixed_texts = mix_text.split(',')
        stoks = pipe.t2s.generate(mixed_texts, lang=mixed_langs)
        audio_data = pipe.generate(stoks, speaker_url, lang=mixed_langs[0])
    else:
        audio_data = pipe.generate(text, speaker_url, lang)

    resample_audio = resampler(newsr=24000)
    audio_data_resampled = next(resample_audio([{'sample_rate': 24000, 'samples': audio_data.cpu()}]))['samples_24k']
    # Normalize audio
    audio_np = audio_data_resampled.cpu().numpy()
    audio_np = audio_np / np.max(np.abs(audio_np))
    
    # Ensure audio data is in the correct format
    audio_np = np.asarray(audio_np, dtype=np.float32)
    
    # Create stereo audio by duplicating the mono channel
    audio_stereo = np.stack((audio_np, audio_np), axis=-1)
    
    # Debugging: Inspect the shape and dtype of the audio array
    print("Audio Array Shape:", audio_stereo.shape)
    print("Audio Array Dtype:", audio_stereo.dtype)
    
    # Save to a temporary WAV file as stereo
    with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp_file:
        # Write the stereo data with a sample rate of 24000 Hz
        sf.write(tmp_file.name, audio_stereo, 24000, format='WAV', subtype='PCM_16')
    return tmp_file.name

with gr.Blocks() as demo:
    gr.Markdown(title)

    with gr.Tabs():
        with gr.TabItem("🌬️💬📝Standard TTS"):
            with gr.Row():
                text_input_standard = gr.Textbox(label="Enter text")
                lang_input_standard = gr.Dropdown(choices=list(LANGUAGES.keys()), label="Language")
                speaker_input_standard = gr.Audio(label="Upload or Record Speaker Audio (optional)", sources=["upload", "microphone"], type="filepath")
                placeholder_mix_lang = gr.Textbox(visible=False) 
                placeholder_mix_text = gr.Textbox(visible=False) 
                generate_button_standard = gr.Button("Generate Speech")
            output_audio_standard = gr.Audio(label="🌬️💬📝WhisperSpeech")
    
            generate_button_standard.click(
                whisper_speech_demo,
                inputs=[text_input_standard, lang_input_standard, speaker_input_standard, placeholder_mix_lang, placeholder_mix_text],
                outputs=output_audio_standard
            )
    
        with gr.TabItem("🌬️💬📝Mixed Language TTS"):
            with gr.Row():
                placeholder_text_input = gr.Textbox(visible=False)
                placeholder_lang_input = gr.Dropdown(choices=[], visible=False)  
                placeholder_speaker_input = gr.Audio(visible=False)  
                mix_lang_input_mixed = gr.CheckboxGroup(choices=list(LANGUAGES.keys()), label="Select Languages")
                mix_text_input_mixed = gr.Textbox(label="Enter mixed language text", placeholder="e.g., Hello, Cześć")
                generate_button_mixed = gr.Button("Generate Mixed Speech")
            output_audio_mixed = gr.Audio(label="Mixed🌬️💬📝WhisperSpeech")
    
            generate_button_mixed.click(
                whisper_speech_demo,
                inputs=[placeholder_text_input, placeholder_lang_input, placeholder_speaker_input, mix_lang_input_mixed, mix_text_input_mixed],
                outputs=output_audio_mixed
            )

demo.launch()