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Delete api.py

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- # It is helpful if you want to use it in a voice assistant project.
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- # Know more about {your gradio app url}/?view=api. Example: http://127.0.0.1:7860/?view=api
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- import shutil
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- import os
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- from gradio_client import Client
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-
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- # Ensure the output directory exists
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- output_dir = "api_output"
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- os.makedirs(output_dir, exist_ok=True)
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-
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- # Initialize the Gradio client
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- api_url = "http://127.0.0.1:7860/"
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- client = Client(api_url)
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-
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-
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-
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-
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- def text_to_speech(
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- text="Hello!!",
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- model_name="kokoro-v0_19.pth",
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- voice_name="af_bella",
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- speed=1,
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- pad_between_segments=0,
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- remove_silence=False,
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- minimum_silence=0.05,
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- custom_voicepack=None,
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- ):
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- """
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- Generates speech from text using a specified model and saves the audio file.
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-
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- Parameters:
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- text (str): The text to convert to speech.
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- model_name (str): The name of the model to use for synthesis.
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- voice_name (str): The name of the voice to use.
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- speed (float): The speed of speech.
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- pad_between_segments (int): Padding between audio segments.
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- remove_silence (bool): Whether to remove silence from the audio.
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- minimum_silence (float): Minimum silence duration to consider.
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- custom_voicepack (str): Path to the custom voice pack to use.
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- Returns:
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- str: Path to the saved audio file.
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- """
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- # Call the API with provided parameters
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- result = client.predict(
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- text=text,
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- model_name=model_name,
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- voice_name=voice_name,
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- speed=speed,
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- pad_between_segments=pad_between_segments,
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- remove_silence=remove_silence,
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- minimum_silence=minimum_silence,
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- custom_voicepack=custom_voicepack,
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- api_name="/text_to_speech"
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- )
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- # Save the audio file in the specified directory
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- save_at = f"{output_dir}/{os.path.basename(result)}"
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- shutil.move(result, save_at)
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- print(f"Saved at {save_at}")
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-
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- return save_at
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-
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- # Example usage
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- if __name__ == "__main__":
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- text="This is Kokoro TTS. I am a text-to-speech model and Super Fast."
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- model_name="kokoro-v0_19.pth" #kokoro-v0_19-half.pth
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- voice_name="af_bella" #get voice names
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- speed=1
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- add_silence_between_segments=0 #it use in large text
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- remove_silence=False
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- keep_silence_upto=0.05 #in seconds
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- custom_voicepack=None
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- audio_path = text_to_speech(text=text, model_name=model_name,
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- voice_name=voice_name, speed=speed,
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- pad_between_segments=add_silence_between_segments,
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- remove_silence=remove_silence,
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- minimum_silence=keep_silence_upto)
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- print(f"Audio file saved at: {audio_path}")