Spaces:
Running
on
T4
Running
on
T4
MCP server updates
Browse files
app.py
CHANGED
@@ -79,6 +79,15 @@ class FileCleaner:
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#file_cleaner = FileCleaner()
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def toggle_audio_src(choice):
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"""
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Toggle the audio input source between microphone and file upload.
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@@ -239,30 +248,30 @@ def load_melody_filepath(melody_filepath, title, assigned_model, topp, temperatu
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return gr.update(value=melody_name), gr.update(maximum=MAX_PROMPT_INDEX, value=-1), gr.update(value=assigned_model, interactive=True), gr.update(value=topp), gr.update(value=temperature), gr.update(value=cfg_coef), gr.update(maximum=MAX_OVERLAP)
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def predict(model, text, melody_filepath, duration, dimension, topk, topp, temperature, cfg_coef, background, title, settings_font, settings_font_color, seed, overlap=1, prompt_index = 0, include_title = True, include_settings = True, harmony_only = False, profile = gr.OAuthProfile, segment_length = 30, settings_font_size=28, settings_animate_waveform=False, video_orientation="Landscape", excerpt_duration=3.5, progress=gr.Progress(track_tqdm=True)):
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"""
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Generate music and video based on the provided parameters and model.
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Args:
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model (str): Model name to use for generation.
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text (str): Prompt describing the music.
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melody_filepath (str): Path to melody conditioning file. default to None.
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duration (int): Total duration in seconds.
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dimension (int): Audio stacking/concatenation dimension.
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topk (int): Top-k sampling value.
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topp (float): Top-p sampling value.
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temperature (float): Sampling temperature.
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cfg_coef (float): Classifier-free guidance coefficient.
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background (str): Path to background image.
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title (str): Song title.
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settings_font (str): Path to font file.
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settings_font_color (str): Font color for settings text.
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seed (int): Random seed.
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overlap (int, optional): Segment overlap in seconds.
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prompt_index (int, optional): Melody segment index.
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include_title (bool, optional): Whether to add title to video.
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include_settings (bool, optional): Whether to add settings to video.
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harmony_only (bool, optional): Whether to use harmony only.
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profile (gr.OAuthProfile): User profile.
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segment_length (int, optional): Segment length in seconds.
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settings_font_size (int, optional): Font size for settings text.
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@@ -618,7 +627,7 @@ def ui(**kwargs):
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with gr.Row():
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with gr.Column():
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radio = gr.Radio(["file", "mic"], value="file", label="Condition on a melody (optional) File or Mic")
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melody_filepath = gr.Audio(sources=["upload"], type="filepath", label="Melody Condition (optional)", interactive=True, elem_id="melody-input", key="melody_input")
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with gr.Column():
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harmony_only = gr.Radio(label="Use Harmony Only",choices=["No", "Yes"], value="No", interactive=True, info="Remove Drums?", key="use_harmony")
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prompt_index = gr.Slider(label="Melody Condition Sample Segment", minimum=-1, maximum=MAX_PROMPT_INDEX, step=1, value=-1, interactive=True, info="Which 10-30 second segment to condition with, - 1 = align with conditioning melody", key="melody_index")
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@@ -749,6 +758,9 @@ def ui(**kwargs):
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launch_kwargs['favicon_path'] = "./assets/favicon.ico"
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launch_kwargs['mcp_server'] = True
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demo.queue(max_size=10, api_open=True).launch(**launch_kwargs)
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#file_cleaner = FileCleaner()
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def ping():
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"""
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return the value true
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Returns:
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boolean: true
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"""
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return True
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def toggle_audio_src(choice):
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"""
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Toggle the audio input source between microphone and file upload.
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return gr.update(value=melody_name), gr.update(maximum=MAX_PROMPT_INDEX, value=-1), gr.update(value=assigned_model, interactive=True), gr.update(value=topp), gr.update(value=temperature), gr.update(value=cfg_coef), gr.update(maximum=MAX_OVERLAP)
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def predict(model, text, melody_filepath = None, duration=10, dimension=2, topk=200, topp=0, temperature=1.0, cfg_coef=4.0, background = None, title="UnlimitedMusicGen", settings_font="./assets/arial.ttf", settings_font_color = "#c87f05", seed=-1, overlap=1, prompt_index = 0, include_title = True, include_settings = True, harmony_only = False, profile = gr.OAuthProfile, segment_length = 30, settings_font_size=28, settings_animate_waveform=False, video_orientation="Landscape", excerpt_duration=3.5, progress=gr.Progress(track_tqdm=True)):
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"""
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Generate music and video based on the provided parameters and model.
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Args:
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model (str): Model name to use for generation.
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text (str): Prompt describing the music.
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melody_filepath (str, optional): Path to melody conditioning file. default to None.
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duration (int): Total duration in seconds.
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dimension (int): Audio stacking/concatenation dimension.
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topk (int): Top-k sampling value.
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topp (float): Top-p sampling value.
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temperature (float): Sampling temperature.
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cfg_coef (float): Classifier-free guidance coefficient.
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background (str, optional): Path to background image. Default to "./assets/background.png".
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title (str, optional): Song title. Default to "UnlimitedMusicGen".
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settings_font (str, optional): Path to font file. Default to "./assets/arial.ttf".
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settings_font_color (str, optional): Font color for settings text. Default to "
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seed (int, optional): Random seed. Default to -1.
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overlap (int, optional): Segment overlap in seconds. Default to 1.
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prompt_index (int, optional): Melody segment index. Default to 0.
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include_title (bool, optional): Whether to add title to video. Default to True.
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include_settings (bool, optional): Whether to add settings to video. Default to True.
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harmony_only (bool, optional): Whether to use harmony only. Default to False.
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profile (gr.OAuthProfile): User profile.
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segment_length (int, optional): Segment length in seconds.
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settings_font_size (int, optional): Font size for settings text.
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with gr.Row():
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with gr.Column():
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radio = gr.Radio(["file", "mic"], value="file", label="Condition on a melody (optional) File or Mic")
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melody_filepath = gr.Audio(value=None,sources=["upload"], type="filepath", label="Melody Condition (optional)", interactive=True, elem_id="melody-input", key="melody_input")
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with gr.Column():
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harmony_only = gr.Radio(label="Use Harmony Only",choices=["No", "Yes"], value="No", interactive=True, info="Remove Drums?", key="use_harmony")
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prompt_index = gr.Slider(label="Melody Condition Sample Segment", minimum=-1, maximum=MAX_PROMPT_INDEX, step=1, value=-1, interactive=True, info="Which 10-30 second segment to condition with, - 1 = align with conditioning melody", key="melody_index")
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launch_kwargs['favicon_path'] = "./assets/favicon.ico"
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launch_kwargs['mcp_server'] = True
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gr.api (
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ping, api_name="ping"
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)
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demo.queue(max_size=10, api_open=True).launch(**launch_kwargs)
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