app.py

import gradio as gr
import os
import tempfile
import re
from pydub import AudioSegment  # Library to combine audio files
from openai import OpenAI

# Max character limit per API request
MAX_CHAR_LIMIT = 4096

def clean_text(text):
    # Replace newlines with spaces and multiple spaces with a single space
    cleaned_text = re.sub(r'\s+', ' ', text.strip())  # Replace multiple spaces and newlines with a single space
    return cleaned_text

def split_text(text, limit=MAX_CHAR_LIMIT):
    # Split text into chunks of <= MAX_CHAR_LIMIT characters
    words = text.split(' ')
    chunks = []
    current_chunk = ""
    
    for word in words:
        # Add words to the current chunk without exceeding the character limit
        if len(current_chunk) + len(word) + 1 <= limit:  # +1 for space
            current_chunk += word + " "
        else:
            chunks.append(current_chunk.strip())  # Append the current chunk
            current_chunk = word + " "  # Start a new chunk
    
    if current_chunk:
        chunks.append(current_chunk.strip())  # Add the last chunk
    
    return chunks

def tts(text, model, voice, speed, api_key, base_url):
    if api_key == '':
        raise gr.Error('Please enter your Key')
    
    cleaned_text = clean_text(text)
    chunks = split_text(cleaned_text)
    
    audio_segments = []

    try:
        client = OpenAI(api_key=api_key, base_url=base_url+'/v1')  # Use selected base_url
        
        # Process each chunk of text
        for chunk in chunks:
            response = client.audio.speech.create(
                model=model,  # "tts-1", "tts-1-hd"
                voice=voice,  # 'alloy', 'echo', 'fable', 'onyx', 'nova', 'shimmer'
                input=chunk,
                speed=speed
            )
            
            # Create a temp file to save the audio for each chunk
            with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as temp_file:
                temp_file.write(response.content)
                temp_file_path = temp_file.name
                audio_segments.append(AudioSegment.from_mp3(temp_file_path))
    
    except Exception as error:
        raise gr.Error("An error occurred while generating speech. Please check your API key and try again.")
    
    # Concatenate all audio chunks into one final audio file
    final_audio = sum(audio_segments)
    
    # Save the concatenated audio to a final file
    with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as final_temp_file:
        final_audio.export(final_temp_file.name, format="mp3")
        final_audio_path = final_temp_file.name

    return final_audio_path


with gr.Blocks() as demo:
    gr.Markdown("# <center> OpenAI TTS Unlimited Character </center>")
    with gr.Row(variant='panel'):
        api_key = gr.Textbox(type='password', label='OpenAI API Key', placeholder='Enter your API key to access the TTS demo')
        model = gr.Dropdown(choices=['tts-1', 'tts-1-hd', 'tts-1-1106', 'tts-1-hd-1106'], label='Model', value='tts-1')
        voice = gr.Dropdown(choices=['alloy', 'echo', 'fable', 'onyx', 'nova', 'shimmer'], label='Voice Options', value='alloy')
        speed = gr.Slider(minimum=0.5, maximum=2.0, step=0.1, label="Speed", value=1.0)
        # Add dropdown for URL selection
        base_url = gr.Dropdown(choices=['https://gpt1.shupremium.com', 'https://gpt1.shupremium.com','https://gpt2.shupremium.com','https://gpt3.shupremium.com' ,'https://gpt4.shupremium.com', 'https://gpt5.shupremium.com'], label="API Endpoint", value='https://gpt5.shupremium.com')

    text = gr.Textbox(label="Input text", placeholder="Enter your text and then click on the 'Text-To-Speech' button, or simply press the Enter key.")
    char_counter = gr.Markdown("Character count: 0")
    btn = gr.Button("Text-To-Speech")
    output_audio = gr.Audio(label="Speech Output")

    def update_char_counter(text):
        cleaned_text = clean_text(text)  # Clean the text by removing extra spaces and newlines
        return f"Character count: {len(cleaned_text)}"

    text.change(fn=update_char_counter, inputs=text, outputs=char_counter)

    text.submit(fn=tts, inputs=[text, model, voice, speed, api_key, base_url], outputs=output_audio, api_name="tts_enter_key", concurrency_limit=None)
    btn.click(fn=tts, inputs=[text, model, voice, speed, api_key, base_url], outputs=output_audio, api_name="tts_button", concurrency_limit=None)

demo.launch()