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import gradio as gr
import pandas as pd
from src.about import (
CITATION_BUTTON_LABEL,
CITATION_BUTTON_TEXT,
EVALUATION_QUEUE_TEXT,
INTRODUCTION_TEXT,
LLM_BENCHMARKS_TEXT,
TITLE,
)
# Simplified DataFrame for the leaderboard
data = {
"Model": [
"Handwritten TAG",
"Zero-shot Text2SQL",
"Zero-shot Text2SQL + LM Generation",
"RAG (E5)",
"RAG (E5) + LM Rerank",
],
"Execution Accuracy": ["55%", "17%", "13%", "0%", "2%"],
}
# Create a DataFrame
leaderboard_df = pd.DataFrame(data)
# Convert Execution Accuracy to numeric for sorting
leaderboard_df["Execution Accuracy (numeric)"] = (
leaderboard_df["Execution Accuracy"].str.rstrip("%").astype(float)
)
leaderboard_df = leaderboard_df.sort_values(
"Execution Accuracy (numeric)", ascending=False
).reset_index(drop=True)
# Add the Rank column
leaderboard_df.insert(0, "Rank", leaderboard_df.index + 1)
# Drop the numeric column for display
leaderboard_df = leaderboard_df.drop(columns=["Execution Accuracy (numeric)"])
# Add hyperlinks to the Model column
def hyperlink_model(model):
base_url = "https://github.com/TAG-Research/TAG-Bench/tree/main"
return f'<a href="{base_url}" target="_blank">{model}</a>'
leaderboard_df["Model"] = leaderboard_df["Model"].apply(hyperlink_model)
# Simplified Gradio app
with gr.Blocks() as demo:
gr.HTML(
"""
<div style="text-align: center;">
<h1 style="font-size: 2.5rem; margin-bottom: 0.5rem;">TAG Leaderboard</h1>
<p style="font-size: 1.25rem; color: gray;">Comparing baseline approaches for structured data queries</p>
</div>
"""
)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
# Highlight the top row in green for "Handwritten TAG"
with gr.Row():
gr.Dataframe(
value=leaderboard_df,
headers=["Model", "Code", "Execution Accuracy"],
datatype=["str", "html", "str"],
row_count=(5, "dynamic"),
wrap=True,
elem_id="leaderboard",
type="pandas"
)
with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
with gr.TabItem("🚀 Submission Instructions ", elem_id="llm-benchmark-tab-table", id=3):
gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
demo.launch()
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