Spaces:
Running
on
Zero
Running
on
Zero
add mcp compatiblity
Browse files
app.py
CHANGED
@@ -52,18 +52,22 @@ def generate_tts_audio(
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cfgw_input: float
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) -> tuple[int, np.ndarray]:
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"""
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-
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Args:
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text_input: The text to synthesize (
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audio_prompt_path_input:
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exaggeration_input:
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temperature_input:
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seed_num_input: Random seed (0 for random)
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cfgw_input: CFG/Pace weight.
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Returns:
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A tuple containing the sample rate (int) and the audio waveform (numpy.ndarray)
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"""
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current_model = get_or_load_model()
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@@ -133,4 +137,4 @@ with gr.Blocks() as demo:
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outputs=[audio_output],
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)
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demo.launch()
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cfgw_input: float
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) -> tuple[int, np.ndarray]:
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"""
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+
Generate high-quality speech audio from text using ChatterboxTTS model with reference audio styling.
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+
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This tool synthesizes natural-sounding speech from input text, using a reference audio file
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to capture the speaker's voice characteristics and speaking style. The generated audio
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maintains the prosody, tone, and vocal qualities of the reference speaker.
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Args:
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text_input (str): The text to synthesize into speech (maximum 300 characters)
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audio_prompt_path_input (str): File path or URL to the reference audio file that defines the target voice style
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exaggeration_input (float): Controls speech expressiveness (0.25-2.0, neutral=0.5, extreme values may be unstable)
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temperature_input (float): Controls randomness in generation (0.05-5.0, higher=more varied, default=0.8)
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seed_num_input (int): Random seed for reproducible results (0 for random generation)
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cfgw_input (float): CFG/Pace weight controlling generation guidance (0.2-1.0, default=0.5)
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Returns:
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tuple[int, np.ndarray]: A tuple containing the sample rate (int) and the generated audio waveform (numpy.ndarray)
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"""
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current_model = get_or_load_model()
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outputs=[audio_output],
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)
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demo.launch(mcp_server=True)
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