app.py

import gradio as gr
import tempfile
import openai
import requests
import os
from functools import partial

def tts(
    input_text: str,
    model: str,
    voice: str,
    api_key: str,
    response_format: str = "mp3",
    speed: float = 1.0,
) -> str:
    """
    Convert input text to speech using OpenAI's Text-to-Speech API.

    Parameters:
        input_text (str): The text to be converted to speech.
        model (str): The model to use for synthesis (e.g., 'tts-1', 'tts-1-hd').
        voice (str): The voice profile to use (e.g., 'alloy', 'echo', 'fable', etc.).
        api_key (str): OpenAI API key.
        response_format (str): The audio format of the output file (default is 'mp3').
        speed (float): The speed of the synthesized speech.

    Returns:
        str: File path to the generated audio file.

    Raises:
        gr.Error: If input parameters are invalid or API call fails.
    """
    if not api_key.strip():
        raise gr.Error(
            "API key is required. Get an API key at: https://platform.openai.com/account/api-keys"
        )

    if not input_text.strip():
        raise gr.Error("Input text cannot be empty.")

    openai.api_key = api_key

    try:
        response = openai.Audio.create(
            text=input_text,
            voice=voice,
            model=model,
            response_format=response_format,
            speed=speed,
        )
    except openai.OpenAIError as e:
        # Catch-all for OpenAI exceptions
        raise gr.Error(f"An OpenAI error occurred: {e}")
    except Exception as e:
        # Catch any other exceptions
        raise gr.Error(f"An unexpected error occurred: {e}")

    if not hasattr(response, "audio"):
        raise gr.Error(
            "Invalid response from OpenAI API. The response does not contain audio content."
        )

    # Save the audio content to a temporary file
    audio_content = response.audio
    file_extension = f".{response_format}"
    with tempfile.NamedTemporaryFile(suffix=file_extension, delete=False) as temp_file:
        temp_file.write(audio_content)
        temp_file_path = temp_file.name

    return temp_file_path

def main():
    """
    Main function to create and launch the Gradio interface.
    """
    MODEL_OPTIONS = ["tts-1", "tts-1-hd"]
    VOICE_OPTIONS = ["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
    RESPONSE_FORMAT_OPTIONS = ["mp3", "opus", "aac", "flac", "wav", "pcm"]

    # Predefine voice previews URLs
    VOICE_PREVIEW_URLS = {
        voice: f"https://cdn.openai.com/API/docs/audio/{voice}.wav"
        for voice in VOICE_OPTIONS
    }

    # Download audio previews to disk before initiating the interface
    PREVIEW_DIR = "voice_previews"
    os.makedirs(PREVIEW_DIR, exist_ok=True)

    VOICE_PREVIEW_FILES = {}
    for voice, url in VOICE_PREVIEW_URLS.items():
        local_file_path = os.path.join(PREVIEW_DIR, f"{voice}.wav")
        if not os.path.exists(local_file_path):
            try:
                response = requests.get(url)
                response.raise_for_status()
                with open(local_file_path, "wb") as f:
                    f.write(response.content)
            except requests.exceptions.RequestException as e:
                print(f"Failed to download {voice} preview: {e}")
        VOICE_PREVIEW_FILES[voice] = local_file_path

    # Set static paths for Gradio to serve
    gr.set_static_paths(paths=[PREVIEW_DIR])

    # Create the 'preview_audio' component
    preview_audio = gr.Audio(
        interactive=False,
        label="Echo",
        value=VOICE_PREVIEW_FILES['echo'],
        visible=True,
        show_download_button=False,
        show_share_button=False,
        autoplay=True,
    )

    with gr.Blocks(title="OpenAI - Text to Speech") as demo:
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("### Voice Preview")

                # Function to play the selected voice sample
                def play_voice_sample(voice):
                    return gr.update(
                        value=VOICE_PREVIEW_FILES[voice],
                        label=voice.capitalize(),
                    )

                # Create buttons for each voice
                for voice in VOICE_OPTIONS:
                    voice_button = gr.Button(
                        value=f"{voice.capitalize()}",
                        variant="secondary",
                        size="sm",
                    )
                    voice_button.click(
                        fn=partial(play_voice_sample, voice=voice),
                        outputs=preview_audio,
                    )

                # Place the audio player below the buttons
                preview_audio.render()

            with gr.Column(scale=1):
                api_key_input = gr.Textbox(
                    label="OpenAI API Key",
                    info="https://platform.openai.com/account/api-keys",
                    type="password",
                    placeholder="Enter your OpenAI API Key",
                )
                model_dropdown = gr.Dropdown(
                    choices=MODEL_OPTIONS,
                    label="Model",
                    value="tts-1",
                    info="Select tts-1 for speed or tts-1-hd for quality.",
                )
                voice_dropdown = gr.Dropdown(
                    choices=VOICE_OPTIONS,
                    label="Voice Options",
                    value="echo",
                    info="The voice to use when generating the audio.",
                )
                response_format_dropdown = gr.Dropdown(
                    choices=RESPONSE_FORMAT_OPTIONS,
                    label="Response Format",
                    value="mp3",
                )
                speed_slider = gr.Slider(
                    minimum=0.25,
                    maximum=4.0,
                    step=0.05,
                    label="Voice Speed",
                    value=1.0,
                )

            with gr.Column(scale=2):
                # Initialize the input textbox with the desired label
                input_textbox = gr.Textbox(
                    label="Input Text (0000 / 4096 chars)",
                    lines=10,
                    placeholder="Type your text here...",
                )

                # Function to update the label with the character count
                def update_label(input_text):
                    char_count = len(input_text)
                    new_label = f"Input Text ({char_count:04d} / 4096 chars)"
                    return gr.update(label=new_label)

                # Update the label when the text changes, with progress hidden
                input_textbox.change(
                    fn=update_label,
                    inputs=input_textbox,
                    outputs=input_textbox,
                    show_progress='hidden',  # Hide the progress indicator
                )

                submit_button = gr.Button(
                    "Convert Text to Speech",
                    variant="primary",
                )
            with gr.Column(scale=1):
                output_audio = gr.Audio(label="Output Audio")

        # Define the event handler for the submit button with error handling
        def on_submit(
            input_text, model, voice, api_key, response_format, speed
        ):
            audio_file = tts(
                input_text, model, voice, api_key, response_format, speed
            )
            return audio_file

        # Trigger the conversion when the submit button is clicked
        submit_button.click(
            fn=on_submit,
            inputs=[
                input_textbox,
                model_dropdown,
                voice_dropdown,
                api_key_input,
                response_format_dropdown,
                speed_slider,
            ],
            outputs=output_audio,
        )

    # Launch the Gradio app with error display enabled
    demo.launch(show_error=True)

if __name__ == "__main__":
    main()