Spaces:
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kz209
commited on
Commit
β’
01809c9
1
Parent(s):
08a24e4
update
Browse files- pages/leaderboard.py +52 -1
pages/leaderboard.py
CHANGED
@@ -5,6 +5,36 @@ import pandas as pd
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from pages.summarization_playground import custom_css
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with open("prompt/prompt.json", "r") as file:
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json_data = file.read()
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prompts = json.loads(json_data)# Sample data for the leaderboard
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@@ -16,7 +46,8 @@ data = {
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'Methods': [prompt['id'] for prompt in prompts],
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'Rouge Score': [prompt['metric']['Rouge'] for prompt in prompts],
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'Winning Rate': winning_rate,
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-
'Authors': [prompt['author'] for prompt in prompts]
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}
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df = pd.DataFrame(data)
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@@ -28,6 +59,20 @@ medals = ['π
', 'π₯', 'π₯']
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for i in range(3):
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df.loc[i, 'Authors'] = f"{medals[i]} {df.loc[i, 'Authors']}"
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def update_leaderboard(sort_by):
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# In a real implementation, this would filter the data based on the category
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sorted_df = df.sort_values(by=sort_by, ascending=False, ignore_index=True)
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@@ -35,6 +80,12 @@ def update_leaderboard(sort_by):
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# Update ranks based on new sorting
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sorted_df['Rank'] = range(1, len(sorted_df) + 1)
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# Convert DataFrame to HTML with clickable headers for sorting
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html = sorted_df.to_html(index=False, escape=False)
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from pages.summarization_playground import custom_css
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css = '''
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.tooltip-wrapper {
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position: relative;
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display: inline-block;
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border-bottom: 1px dotted black;
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}
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.tooltip-wrapper .tooltip {
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visibility: hidden;
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width: 120px;
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background-color: black;
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color: #fff;
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text-align: center;
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border-radius: 6px;
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padding: 5px 0;
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position: absolute;
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z-index: 1;
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bottom: 125%;
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left: 50%;
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margin-left: -60px;
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opacity: 0;
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transition: opacity 0.3s;
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}
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.tooltip-wrapper:hover .tooltip {
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visibility: visible;
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opacity: 1;
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}
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'''
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with open("prompt/prompt.json", "r") as file:
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json_data = file.read()
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prompts = json.loads(json_data)# Sample data for the leaderboard
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'Methods': [prompt['id'] for prompt in prompts],
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'Rouge Score': [prompt['metric']['Rouge'] for prompt in prompts],
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'Winning Rate': winning_rate,
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'Authors': [prompt['author'] for prompt in prompts],
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'Prompts': [prompt['prompt'] for prompt in prompts]
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}
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df = pd.DataFrame(data)
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for i in range(3):
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df.loc[i, 'Authors'] = f"{medals[i]} {df.loc[i, 'Authors']}"
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def create_html_with_tooltip(text, tooltip):
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return f'''
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<div class="tooltip-wrapper">
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{text}
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<span class="tooltip">{tooltip}</span>
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</div>
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'''
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def show_tooltip():
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text_with_tooltip = create_html_with_tooltip("Hover over me", "This is a tooltip!")
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return text_with_tooltip
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def update_leaderboard(sort_by):
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# In a real implementation, this would filter the data based on the category
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sorted_df = df.sort_values(by=sort_by, ascending=False, ignore_index=True)
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# Update ranks based on new sorting
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sorted_df['Rank'] = range(1, len(sorted_df) + 1)
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# Create hover effect for Methods column
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sorted_df['Methods'] = sorted_df.apply(lambda row: create_html_with_tooltip(row['Methods'], row['Prompts']), axis=1)
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# Drop the 'Prompts' column as we don't want to display it directly
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sorted_df = sorted_df.drop(columns=['Prompts'])
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# Convert DataFrame to HTML with clickable headers for sorting
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html = sorted_df.to_html(index=False, escape=False)
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