Spaces:
Running
on
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Running
on
Zero
Create app-backup.py
Browse files- app-backup.py +117 -0
app-backup.py
ADDED
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import os
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import gradio as gr
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import outetts
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from outetts.version.v2.interface import _DEFAULT_SPEAKERS
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import torch
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import spaces
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def get_available_speakers():
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speakers = list(_DEFAULT_SPEAKERS.keys())
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return speakers
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@spaces.GPU
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def generate_tts(text, temperature, repetition_penalty, speaker_selection, reference_audio):
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model_config = outetts.HFModelConfig_v2(
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model_path="OuteAI/OuteTTS-0.3-1B",
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tokenizer_path="OuteAI/OuteTTS-0.3-1B",
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dtype=torch.bfloat16,
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device="cuda"
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)
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interface = outetts.InterfaceHF(model_version="0.3", cfg=model_config)
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try:
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if reference_audio:
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speaker = interface.create_speaker(reference_audio)
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elif speaker_selection and speaker_selection != "None":
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speaker = interface.load_default_speaker(speaker_selection)
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else:
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speaker = None
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gen_cfg = outetts.GenerationConfig(
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text=text,
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temperature=temperature,
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repetition_penalty=repetition_penalty,
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max_length=4096,
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speaker=speaker,
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)
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output = interface.generate(config=gen_cfg)
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if output.audio is None:
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raise ValueError("Model failed to generate audio. This may be due to input length constraints or early EOS token.")
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output_path = "output.wav"
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output.save(output_path)
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return output_path, None
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except Exception as e:
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return None, str(e)
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with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange") as demo:
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gr.Markdown("# Voice Clone Multilingual TTS")
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error_box = gr.Textbox(label="Error Messages", visible=False)
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with gr.Row():
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with gr.Column(scale=1):
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text_input = gr.Textbox(
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label="Text to Synthesize",
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placeholder="Enter text here...",
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lines=8
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)
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submit_button = gr.Button("Generate Speech")
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with gr.Column(scale=1):
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audio_output = gr.Audio(
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label="Generated Audio",
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type="filepath"
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)
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with gr.Group():
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speaker_dropdown = gr.Dropdown(
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choices=get_available_speakers(),
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value="en_male_1",
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label="Speaker Selection"
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)
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temperature = gr.Slider(
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0.1, 1.0,
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value=0.1,
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label="Temperature (lower = more stable tone, higher = more expressive)"
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)
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repetition_penalty = gr.Slider(
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0.5, 2.0,
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value=1.1,
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label="Repetition Penalty"
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)
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reference_audio = gr.Audio(
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label="Reference Audio (for voice cloning)",
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type="filepath"
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)
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gr.Markdown("""
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### Voice Cloning Guidelines:
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- Use around 7-10 seconds of clear, noise-free audio
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- For transcription interface will use Whisper turbo to transcribe the audio file
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- Longer audio clips will reduce maximum output length
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- Custom speaker overrides speaker selection
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""")
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submit_button.click(
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fn=generate_tts,
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inputs=[
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text_input,
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temperature,
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repetition_penalty,
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speaker_dropdown,
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reference_audio,
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],
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outputs=[audio_output, error_box]
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).then(
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fn=lambda x: gr.update(visible=bool(x)),
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inputs=[error_box],
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outputs=[error_box]
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)
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demo.launch()
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