""" This script implements a Gradio interface for text-to-speech conversion using OpenAI's API. Users can input text, select a model and voice, and receive an audio output of the synthesized speech. Dependencies: - gradio - openai Usage: Run the script to launch a web interface for text-to-speech conversion. Note: - Ensure that you have installed the required packages: pip install gradio openai - Obtain a valid OpenAI API key with access to the necessary services. """ import gradio as gr import tempfile import openai from typing import Tuple def tts(input_text: str, model: str, voice: str, api_key: str) -> str: """ Convert input text to speech using OpenAI's Text-to-Speech API. :param input_text: The text to be converted to speech. :type input_text: str :param model: The model to use for synthesis (e.g., 'tts-1', 'tts-1-hd'). :type model: str :param voice: The voice profile to use (e.g., 'alloy', 'echo', 'fable', etc.). :type voice: str :param api_key: OpenAI API key. :type api_key: str :return: File path to the generated audio file. :rtype: str :raises ValueError: If input parameters are invalid. :raises openai.error.OpenAIError: If API call fails. """ if not input_text.strip(): raise ValueError("Input text cannot be empty.") if not api_key.strip(): raise ValueError("API key is required.") openai.api_key = api_key try: response = openai.audio.speech.create( input=input_text, voice=voice, model=model ) except openai.error.OpenAIError as e: raise e if not hasattr(response, 'content'): raise Exception("Invalid response from OpenAI API. The response does not contain audio content.") with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as temp_file: temp_file.write(response.content) temp_file_path = temp_file.name return temp_file_path def on_convert_click(input_text: str, model: str, voice: str, api_key: str) -> Tuple[str, str]: """ Callback function to handle the click event for text-to-speech conversion. :param input_text: Text input from the user. :type input_text: str :param model: Selected model. :type model: str :param voice: Selected voice. :type voice: str :param api_key: User's OpenAI API key. :type api_key: str :return: Tuple containing the file path to the generated audio file and an error message. :rtype: Tuple[str, str] """ try: file_path = tts(input_text, model, voice, api_key) return file_path, "" except Exception as e: return None, str(e) def main(): """ Main function to create and launch the Gradio interface. """ # Define model and voice options MODEL_OPTIONS = ["tts-1", "tts-1-hd"] VOICE_OPTIONS = ["alloy", "echo", "fable", "onyx", "nova", "shimmer"] with gr.Blocks() as demo: with gr.Row(): with gr.Column(scale=1): api_key_input = gr.Textbox( label="API Key", type="password", placeholder="Enter your OpenAI API Key" ) model_dropdown = gr.Dropdown( choices=MODEL_OPTIONS, label="Model", value="tts-1" ) voice_dropdown = gr.Dropdown( choices=VOICE_OPTIONS, label="Voice Options", value="echo" ) with gr.Column(scale=2): input_textbox = gr.Textbox( label="Input Text", lines=10, placeholder="Type your text here..." ) submit_button = gr.Button("Convert Text to Speech", variant="primary") with gr.Column(scale=1): output_audio = gr.Audio(label="Output Audio") error_output = gr.Textbox( label="Error Message", interactive=False, visible=False ) # Define the event handler for the submit button submit_button.click( fn=on_convert_click, inputs=[input_textbox, model_dropdown, voice_dropdown, api_key_input], outputs=[output_audio, error_output] ) # Allow pressing Enter in the input textbox to trigger the conversion input_textbox.submit( fn=on_convert_click, inputs=[input_textbox, model_dropdown, voice_dropdown, api_key_input], outputs=[output_audio, error_output] ) demo.launch() if __name__ == "__main__": main()