Spaces:
Running
on
T4
Running
on
T4
Updating Docstrings for MCP
Browse files- app.py +93 -3
- modules/user_history.py +37 -6
app.py
CHANGED
@@ -80,22 +80,48 @@ class FileCleaner:
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#file_cleaner = FileCleaner()
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def toggle_audio_src(choice):
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if choice == "mic":
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return gr.update(source="microphone", value=None, label="Microphone")
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else:
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return gr.update(source="upload", value=None, label="File")
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def get_waveform(*args, **kwargs):
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be = time.time()
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with warnings.catch_warnings():
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warnings.simplefilter('ignore')
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out = gr.make_waveform(*args, **kwargs)
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print("Make a video took", time.time() - be)
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return out
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-
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def load_model(version, progress=gr.Progress(track_tqdm=True)):
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global MODEL, MODELS, UNLOAD_MODEL
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print("Loading model", version)
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@@ -131,6 +157,12 @@ def get_melody(melody_filepath):
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return melody
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def git_tag():
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try:
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return subprocess.check_output([git, "describe", "--tags"], shell=False, encoding='utf8').strip()
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except Exception:
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@@ -143,12 +175,36 @@ def git_tag():
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return "<none>"
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def load_background_filepath(video_orientation):
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if video_orientation == "Landscape":
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return "./assets/background.png"
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else:
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return "./assets/background_portrait.png"
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-
def load_melody_filepath(melody_filepath, title, assigned_model,topp, temperature, cfg_coef, segment_length = 30):
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# get melody filename
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#$Union[str, os.PathLike]
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symbols = ['_', '.', '-']
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@@ -184,6 +240,40 @@ def load_melody_filepath(melody_filepath, title, assigned_model,topp, temperatur
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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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global MODEL, INTERRUPTED, INTERRUPTING, MOVE_TO_CPU
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output_segments = None
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melody_name = "Not Used"
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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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Args:
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choice (str): The selected audio source, either 'mic' or 'upload'.
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Returns:
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gr.Update: Gradio update object to change the audio input component.
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"""
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if choice == "mic":
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return gr.update(source="microphone", value=None, label="Microphone")
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else:
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return gr.update(source="upload", value=None, label="File")
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def get_waveform(*args, **kwargs):
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"""
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Generate a waveform video for the given audio input.
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Args:
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melody_filepath (str): Path to the melody audio file.
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Returns:
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tuple: (sample_rate, audio_data) loaded from the file.
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"""
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be = time.time()
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with warnings.catch_warnings():
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warnings.simplefilter('ignore')
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out = gr.make_waveform(*args, **kwargs)
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print("Make a video took", time.time() - be)
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return out
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def load_model(version, progress=gr.Progress(track_tqdm=True)):
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"""
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Load a MusicGen model by version name, optionally showing progress.
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Args:
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version (str): The model version to load.
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progress (gr.Progress, optional): Gradio progress tracker.
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Returns:
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MusicGen: The loaded MusicGen model instance.
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"""
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global MODEL, MODELS, UNLOAD_MODEL
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print("Loading model", version)
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return melody
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def git_tag():
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"""
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Get the current git tag or fallback to the first line of CHANGELOG.md if unavailable.
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Returns:
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str: The current git tag or '<none>' if not available.
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"""
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try:
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return subprocess.check_output([git, "describe", "--tags"], shell=False, encoding='utf8').strip()
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except Exception:
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return "<none>"
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def load_background_filepath(video_orientation):
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"""
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Get the background image path based on video orientation.
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Args:
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video_orientation (str): Either 'Landscape' or 'Portait'.
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Returns:
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str: Path to the background image file.
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"""
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if video_orientation == "Landscape":
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return "./assets/background.png"
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else:
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return "./assets/background_portrait.png"
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def load_melody_filepath(melody_filepath, title, assigned_model, topp, temperature, cfg_coef, segment_length = 30):
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"""
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Update melody-related UI fields based on the selected melody file and settings.
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Args:
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melody_filepath (str): Path to the melody file.
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title (str): The song title.
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assigned_model (str): The selected model name.
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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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segment_length (int, optional): Segment length in seconds.
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Returns:
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tuple: Updated values for title, prompt_index, model, topp, temperature, cfg_coef, overlap.
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"""
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# get melody filename
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#$Union[str, os.PathLike]
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symbols = ['_', '.', '-']
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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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settings_animate_waveform (bool, optional): Animate waveform in video.
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video_orientation (str, optional): Video orientation.
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excerpt_duration (float, optional): Excerpt duration for style conditioning.
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progress (gr.Progress, optional): Gradio progress tracker.
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Returns:
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tuple: (waveform_video_path, wave_file_path, seed_used)
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"""
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global MODEL, INTERRUPTED, INTERRUPTING, MOVE_TO_CPU
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output_segments = None
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melody_name = "Not Used"
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modules/user_history.py
CHANGED
@@ -18,7 +18,7 @@ Useful links:
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Update by Surn (Charles Fettinger)
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"""
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-
__version__ = "0.3.
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import json
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import os
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@@ -46,9 +46,16 @@ from tqdm import tqdm
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user_profile = gr.State(None)
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def get_profile() -> gr.OAuthProfile | None:
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return user_profile
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def setup(folder_path: str | Path | None = None, display_type: str = "image_path") -> None:
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def _fetch_user_history(profile: gr.OAuthProfile | None) -> List[Tuple[str, str]]:
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"""
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# Cannot load history for logged out users
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global user_profile
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if profile is None:
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def _export_user_history(profile: gr.OAuthProfile | None) -> Dict | None:
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"""
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# Cannot load history for logged out users
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if profile is None:
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return None
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def _delete_user_history(profile: gr.OAuthProfile | None) -> None:
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"""
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# Cannot load history for logged out users
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if profile is None:
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return
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Update by Surn (Charles Fettinger)
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"""
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__version__ = "0.3.5"
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import json
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import os
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user_profile = gr.State(None)
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def get_profile() -> gr.OAuthProfile | None:
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"""
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Retrieve the currently logged-in user's profile.
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This function returns the user profile stored in the global Gradio state.
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If no user is logged in, it returns None.
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Returns:
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gr.OAuthProfile | None: The currently logged-in user's profile, or None if no user is logged in.
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"""
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global user_profile
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return user_profile
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def setup(folder_path: str | Path | None = None, display_type: str = "image_path") -> None:
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def _fetch_user_history(profile: gr.OAuthProfile | None) -> List[Tuple[str, str]]:
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"""
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Return saved history for the given user.
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Args:
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profile (gr.OAuthProfile | None): The user profile.
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Returns:
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List[Tuple[str, str]]: A list of tuples, where each tuple contains the path to an image and its label.
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"""
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# Cannot load history for logged out users
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global user_profile
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if profile is None:
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def _export_user_history(profile: gr.OAuthProfile | None) -> Dict | None:
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"""
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Zip all history for the given user, if it exists, and return it as a downloadable file.
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Args:
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profile (gr.OAuthProfile | None): The user profile.
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Returns:
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Dict | None: A Gradio update dictionary with the path to the zip file if successful, or None if the user is not logged in or user history is not initialized.
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"""
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# Cannot load history for logged out users
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if profile is None:
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return None
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def _delete_user_history(profile: gr.OAuthProfile | None) -> None:
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"""
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Delete all history for the given user.
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Args:
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profile (gr.OAuthProfile | None): The user profile.
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Returns:
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None
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"""
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# Cannot load history for logged out users
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if profile is None:
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return
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