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Update app.py
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app.py
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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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# %% auto 0
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__all__ = ['columns_to_click', 'title', 'description', 'dtypes', 'get_data']
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# %% app.ipynb 0
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import gradio as gr
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import pandas as pd
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# %% app.ipynb 1
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columns_to_click = ["Paper / Repo", "Playground"]
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def get_data():
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df = pd.read_csv(
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"https://docs.google.com/spreadsheets/d/e/2PACX-1vSC40sszorOjHfozmNqJT9lFiJhG94u3fbr3Ss_7fzcU3xqqJQuW1Ie_SNcWEB-uIsBi9NBUK7-ddet/pub?output=csv",
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skiprows=1,
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)
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#
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df = df.copy()[~df["Model"].isna()]
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# %% app.ipynb 3
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# Drop TBA models
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df = df.copy()[df["Parameters \n(B)"] != "TBA"]
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#
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def make_clickable_cell(cell):
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if pd.isnull(cell):
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return ""
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else:
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return f'<a target="_blank" href="{cell}">{cell}</a>'
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# %% app.ipynb 7
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for col in columns_to_click:
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df[col] = df[col].apply(make_clickable_cell)
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return df
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#
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"""
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# %% app.ipynb 3
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dtypes = ["str" if c not in columns_to_click else "markdown" for c in get_data().columns]
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#
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with gr.Blocks() as demo:
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gr.DataFrame(get_data, datatype=dtypes, every=60)
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import gradio as gr
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import pandas as pd
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# Assuming columns_to_click are the columns which contain URLs that you want to make clickable
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columns_to_click = ["Paper / Repo", "Playground"]
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def get_data():
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# Load the CSV file into a DataFrame
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df = pd.read_csv(
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"https://docs.google.com/spreadsheets/d/e/2PACX-1vSC40sszorOjHfozmNqJT9lFiJhG94u3fbr3Ss_7fzcU3xqqJQuW1Ie_SNcWEB-uIsBi9NBUK7-ddet/pub?output=csv",
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skiprows=1,
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)
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# Drop rows where the 'Model' column is NaN
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df.dropna(subset=['Model'], inplace=True)
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# Drop rows where the 'Parameters \n(B)' column is 'TBA'
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df = df[df["Parameters \n(B)"] != "TBA"]
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# Apply make_clickable_cell to the specified columns
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for col in columns_to_click:
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df[col] = df[col].apply(make_clickable_cell)
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return df
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def make_clickable_cell(cell):
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if pd.isnull(cell) or not isinstance(cell, str):
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return ""
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else:
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return f'<a target="_blank" href="{cell}">{cell}</a>'
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# Load the data to get the columns for setting up datatype
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dataframe = get_data()
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dtypes = ["str" if c not in columns_to_click else "html" for c in dataframe.columns]
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# Gradio app setup
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with gr.Blocks() as demo:
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# Markdown and DataFrame components
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...
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# Launch the Gradio app
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demo.launch()
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