import json
import gradio as gr
with open("results.json") as f:
raw_data = json.load(f)
# Extract task info
task_name = raw_data.get("task", "Leaderboard")
task_description = raw_data.get("description", "")
# Extract rows from the new format
data = raw_data["datasets"][0]["sota"]["rows"]
# Sort by driving score
data = sorted(data, key=lambda x: float(x["metrics"]["Driving Score"]), reverse=True)
rows_html = ""
for idx, d in enumerate(data, 1):
# Extract paper info
paper_title = d.get("paper_title", "")
paper_url = d.get("paper_url", "")
paper = f'📄 {paper_title}' if paper_url and paper_title else ""
# Extract repository info
code_links = d.get("code_links", [])
if code_links and len(code_links) > 0:
repo_url = code_links[0]["url"]
repo = f''
else:
repo = "-"
row_class = "row-even" if idx % 2 == 0 else "row-odd"
rows_html += f"""
{d["model_name"]}
{d["metrics"]["Driving Score"]}
{paper}
{repo}
"""
html = f"""
{task_name}
{task_description}
Model Name
Driving Score ↑
Paper Title
Repository
{rows_html}
"""
with gr.Blocks(css="""
#component-0 {
max-width: 1400px;
margin: auto;
padding: 40px 20px;
}
""") as demo:
gr.HTML(html)
demo.launch()