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jonathanagustin
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app.py
CHANGED
@@ -3,16 +3,26 @@ import tempfile
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import openai
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import requests
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import os
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"""
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Convert input text to speech using OpenAI's Text-to-Speech API.
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Parameters:
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input_text (str): The text to be converted to speech.
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model (str): The model to use for synthesis (e.g., 'tts-1', 'tts-1-hd').
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voice (str): The voice
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api_key (str): OpenAI API key.
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Returns:
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str: File path to the generated audio file.
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@@ -28,34 +38,61 @@ def tts(input_text: str, model: str, voice: str, api_key: str) -> str:
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if not input_text.strip():
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raise gr.Error("Input text cannot be empty.")
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try:
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response =
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except Exception as e:
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# Catch any other exceptions
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raise gr.Error(f"An unexpected error occurred: {e}")
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if not hasattr(response, "audio"):
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raise gr.Error(
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"Invalid response from OpenAI API. The response does not contain audio content."
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)
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temp_file_path = temp_file.name
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return temp_file_path
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def main():
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"""
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Main function to create and launch the Gradio interface.
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"""
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MODEL_OPTIONS = ["tts-1", "tts-1-hd"]
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VOICE_OPTIONS = ["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
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# Predefine voice previews URLs
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VOICE_PREVIEW_URLS = {
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@@ -81,58 +118,67 @@ def main():
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VOICE_PREVIEW_FILES[voice] = local_file_path
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# Set static paths for Gradio to serve
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gr.set_static_paths([PREVIEW_DIR])
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with gr.Blocks(title="OpenAI - Text to Speech") as demo:
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with gr.Row():
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with gr.Column(scale=1):
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gr.
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value=None,
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visible=True,
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autoplay=True,
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)
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# A function to update the preview_audio component
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def play_voice_sample(voice):
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return gr.update(value=VOICE_PREVIEW_FILES[voice])
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# Create buttons for each voice inside a grid
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for voice in VOICE_OPTIONS:
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# Create a button for each voice
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voice_button = gr.Button(
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value=f"{voice.capitalize()}",
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variant="secondary",
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size="sm",
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)
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#
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)
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with gr.Column(scale=1):
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api_key_input = gr.Textbox(
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label="OpenAI API Key",
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info="https://platform.openai.com/account/api-keys",
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type="password",
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placeholder="Enter your OpenAI API Key",
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)
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model_dropdown = gr.Dropdown(
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choices=MODEL_OPTIONS,
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label="Model",
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value="tts-1",
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)
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voice_dropdown = gr.Dropdown(
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choices=VOICE_OPTIONS,
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label="Voice Options",
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value="echo",
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)
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with gr.Column(scale=2):
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input_textbox = gr.Textbox(
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@@ -140,6 +186,21 @@ def main():
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lines=10,
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placeholder="Type your text here...",
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)
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submit_button = gr.Button(
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"Convert Text to Speech",
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variant="primary",
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output_audio = gr.Audio(label="Output Audio")
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# Define the event handler for the submit button with error handling
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def on_submit(
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return audio_file
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# Trigger the conversion when the submit button is clicked
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submit_button.click(
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fn=on_submit,
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inputs=[
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outputs=output_audio,
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)
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# Launch the Gradio app with error display enabled
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demo.launch(show_error=True)
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if __name__ == "__main__":
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main()
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import openai
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import requests
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import os
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from functools import partial
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def tts(
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input_text: str,
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model: str,
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voice: str,
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api_key: str,
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response_format: str = "mp3",
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speed: float = 1.0,
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) -> str:
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"""
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Convert input text to speech using OpenAI's Text-to-Speech API.
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Parameters:
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input_text (str): The text to be converted to speech.
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model (str): The model to use for synthesis (e.g., 'tts-1', 'tts-1-hd').
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voice (str): The voice to use when generating the audio.
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api_key (str): OpenAI API key.
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response_format (str): Format of the output audio. Defaults to 'mp3'.
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speed (float): Speed of the generated audio. Defaults to 1.0.
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Returns:
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str: File path to the generated audio file.
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if not input_text.strip():
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raise gr.Error("Input text cannot be empty.")
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if len(input_text) > 4096:
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raise gr.Error("Input text exceeds the maximum length of 4096 characters.")
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if speed < 0.25 or speed > 4.0:
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raise gr.Error("Speed must be between 0.25 and 4.0.")
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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data = {
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"model": model,
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"input": input_text,
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"voice": voice,
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"response_format": response_format,
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"speed": speed,
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}
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try:
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response = requests.post(
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"https://api.openai.com/v1/audio/speech",
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headers=headers,
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json=data,
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)
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response.raise_for_status()
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except requests.exceptions.HTTPError as http_err:
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raise gr.Error(f"HTTP error occurred: {http_err} - {response.text}")
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except Exception as err:
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raise gr.Error(f"An error occurred: {err}")
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# The content will be the audio file content
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audio_content = response.content
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file_extension = response_format.lower()
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# PCM is raw data, so it does not have a standard file extension
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if file_extension == "pcm":
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file_extension = "raw"
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with tempfile.NamedTemporaryFile(
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suffix=f".{file_extension}", delete=False
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) as temp_file:
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temp_file.write(audio_content)
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temp_file_path = temp_file.name
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return temp_file_path
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def main():
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"""
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Main function to create and launch the Gradio interface.
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"""
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MODEL_OPTIONS = ["tts-1", "tts-1-hd"]
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VOICE_OPTIONS = ["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
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RESPONSE_FORMAT_OPTIONS = ["mp3", "opus", "aac", "flac", "wav", "pcm"]
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# Predefine voice previews URLs
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VOICE_PREVIEW_URLS = {
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VOICE_PREVIEW_FILES[voice] = local_file_path
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# Set static paths for Gradio to serve
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gr.static(PREVIEW_DIR)
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with gr.Blocks(title="OpenAI - Text to Speech") as demo:
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gr.Markdown("# OpenAI Text-to-Speech Demo")
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Group():
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preview_audio = gr.Audio(
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interactive=False,
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label="Preview Audio",
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value=None,
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visible=True,
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)
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# Function to play the selected voice sample
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def play_voice_sample(voice):
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return gr.update(value=VOICE_PREVIEW_FILES[voice])
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# Create buttons for each voice
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for voice in VOICE_OPTIONS:
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voice_button = gr.Button(
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value=f"{voice.capitalize()}",
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variant="secondary",
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size="sm",
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)
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voice_button.click(
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fn=partial(play_voice_sample, voice=voice),
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outputs=preview_audio,
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)
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with gr.Column(scale=1):
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api_key_input = gr.Textbox(
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label="OpenAI API Key",
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info="https://platform.openai.com/account/api-keys",
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type="password",
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placeholder="Enter your OpenAI API Key",
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)
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model_dropdown = gr.Dropdown(
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choices=MODEL_OPTIONS,
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label="Model",
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value="tts-1",
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info="Select tts-1 for speed or tts-1-hd for quality.",
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)
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voice_dropdown = gr.Dropdown(
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choices=VOICE_OPTIONS,
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label="Voice Options",
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value="echo",
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info="The voice to use when generating the audio.",
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)
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response_format_dropdown = gr.Dropdown(
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choices=RESPONSE_FORMAT_OPTIONS,
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label="Response Format",
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value="mp3",
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)
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speed_slider = gr.Slider(
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minimum=0.25,
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maximum=4.0,
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step=0.05,
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label="Voice Speed",
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value=1.0,
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)
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with gr.Column(scale=2):
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input_textbox = gr.Textbox(
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lines=10,
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placeholder="Type your text here...",
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)
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# Add a character counter below the input textbox
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char_count_text = gr.Markdown("0 / 4096")
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# Function to update the character count
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def update_char_count(input_text):
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char_count = len(input_text)
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return f"**{char_count} / 4096**"
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# Update character count when the user stops typing
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input_textbox.change(
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fn=update_char_count,
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inputs=input_textbox,
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outputs=char_count_text,
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)
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submit_button = gr.Button(
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"Convert Text to Speech",
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variant="primary",
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output_audio = gr.Audio(label="Output Audio")
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# Define the event handler for the submit button with error handling
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def on_submit(
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input_text, model, voice, api_key, response_format, speed
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):
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audio_file = tts(
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input_text, model, voice, api_key, response_format, speed
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)
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return audio_file
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# Trigger the conversion when the submit button is clicked
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submit_button.click(
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fn=on_submit,
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inputs=[
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input_textbox,
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model_dropdown,
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voice_dropdown,
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api_key_input,
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response_format_dropdown,
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speed_slider,
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],
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outputs=output_audio,
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)
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# Launch the Gradio app with error display enabled
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demo.launch(show_error=True)
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if __name__ == "__main__":
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main()
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